case study report on risk management

Enterprise Risk Management Case Studies: Heroes and Zeros

By Andy Marker | April 7, 2021

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We’ve compiled more than 20 case studies of enterprise risk management programs that illustrate how companies can prevent significant losses yet take risks with more confidence.   

Included on this page, you’ll find case studies and examples by industry , case studies of major risk scenarios (and company responses), and examples of ERM successes and failures .

Enterprise Risk Management Examples and Case Studies

With enterprise risk management (ERM) , companies assess potential risks that could derail strategic objectives and implement measures to minimize or avoid those risks. You can analyze examples (or case studies) of enterprise risk management to better understand the concept and how to properly execute it.

The collection of examples and case studies on this page illustrates common risk management scenarios by industry, principle, and degree of success. For a basic overview of enterprise risk management, including major types of risks, how to develop policies, and how to identify key risk indicators (KRIs), read “ Enterprise Risk Management 101: Programs, Frameworks, and Advice from Experts .”

Enterprise Risk Management Framework Examples

An enterprise risk management framework is a system by which you assess and mitigate potential risks. The framework varies by industry, but most include roles and responsibilities, a methodology for risk identification, a risk appetite statement, risk prioritization, mitigation strategies, and monitoring and reporting.

To learn more about enterprise risk management and find examples of different frameworks, read our “ Ultimate Guide to Enterprise Risk Management .”

Enterprise Risk Management Examples and Case Studies by Industry

Though every firm faces unique risks, those in the same industry often share similar risks. By understanding industry-wide common risks, you can create and implement response plans that offer your firm a competitive advantage.

Enterprise Risk Management Example in Banking

Toronto-headquartered TD Bank organizes its risk management around two pillars: a risk management framework and risk appetite statement. The enterprise risk framework defines the risks the bank faces and lays out risk management practices to identify, assess, and control risk. The risk appetite statement outlines the bank’s willingness to take on risk to achieve its growth objectives. Both pillars are overseen by the risk committee of the company’s board of directors.  

Risk management frameworks were an important part of the International Organization for Standardization’s 31000 standard when it was first written in 2009 and have been updated since then. The standards provide universal guidelines for risk management programs.  

Risk management frameworks also resulted from the efforts of the Committee of Sponsoring Organizations of the Treadway Commission (COSO). The group was formed to fight corporate fraud and included risk management as a dimension. 

Once TD completes the ERM framework, the bank moves onto the risk appetite statement. 

The bank, which built a large U.S. presence through major acquisitions, determined that it will only take on risks that meet the following three criteria:

• The risk fits the company’s strategy, and TD can understand and manage those risks. 
• The risk does not render the bank vulnerable to significant loss from a single risk.
• The risk does not expose the company to potential harm to its brand and reputation. 

Some of the major risks the bank faces include strategic risk, credit risk, market risk, liquidity risk, operational risk, insurance risk, capital adequacy risk, regulator risk, and reputation risk. Managers detail these categories in a risk inventory. 

The risk framework and appetite statement, which are tracked on a dashboard against metrics such as capital adequacy and credit risk, are reviewed annually. 

TD uses a three lines of defense (3LOD) strategy, an approach widely favored by ERM experts, to guard against risk. The three lines are as follows:

• A business unit and corporate policies that create controls, as well as manage and monitor risk
• Standards and governance that provide oversight and review of risks and compliance with the risk appetite and framework 
• Internal audits that provide independent checks and verification that risk-management procedures are effective

Enterprise Risk Management Example in Pharmaceuticals

Drug companies’ risks include threats around product quality and safety, regulatory action, and consumer trust. To avoid these risks, ERM experts emphasize the importance of making sure that strategic goals do not conflict. 

For Britain’s GlaxoSmithKline, such a conflict led to a breakdown in risk management, among other issues. In the early 2000s, the company was striving to increase sales and profitability while also ensuring safe and effective medicines. One risk the company faced was a failure to meet current good manufacturing practices (CGMP) at its plant in Cidra, Puerto Rico. 

CGMP includes implementing oversight and controls of manufacturing, as well as managing the risk and confirming the safety of raw materials and finished drug products. Noncompliance with CGMP can result in escalating consequences, ranging from warnings to recalls to criminal prosecution. 

GSK’s unit pleaded guilty and paid $750 million in 2010 to resolve U.S. charges related to drugs made at the Cidra plant, which the company later closed. A fired GSK quality manager alerted regulators and filed a whistleblower lawsuit in 2004. In announcing the consent decree, the U.S. Department of Justice said the plant had a history of bacterial contamination and multiple drugs created there in the early 2000s violated safety standards.

According to the whistleblower, GSK’s ERM process failed in several respects to act on signs of non-compliance with CGMP. The company received warning letters from the U.S. Food and Drug Administration in 2001 about the plant’s practices, but did not resolve the issues. 

Additionally, the company didn’t act on the quality manager’s compliance report, which advised GSK to close the plant for two weeks to fix the problems and notify the FDA. According to court filings, plant staff merely skimmed rejected products and sold them on the black market. They also scraped by hand the inside of an antibiotic tank to get more product and, in so doing, introduced bacteria into the product.

Enterprise Risk Management Example in Consumer Packaged Goods

Mars Inc., an international candy and food company, developed an ERM process. The company piloted and deployed the initiative through workshops with geographic, product, and functional teams from 2003 to 2012. 

Driven by a desire to frame risk as an opportunity and to work within the company’s decentralized structure, Mars created a process that asked participants to identify potential risks and vote on which had the highest probability. The teams listed risk mitigation steps, then ranked and color-coded them according to probability of success. 

Larry Warner, a Mars risk officer at the time, illustrated this process in a case study . An initiative to increase direct-to-consumer shipments by 12 percent was colored green, indicating a 75 percent or greater probability of achievement. The initiative to bring a new plant online by the end of Q3 was coded red, meaning less than a 50 percent probability of success. 

The company’s results were hurt by a surprise at an operating unit that resulted from a so-coded red risk identified in a unit workshop. Executives had agreed that some red risk profile was to be expected, but they decided that when a unit encountered a red issue, it must be communicated upward when first identified. This became a rule. 

This process led to the creation of an ERM dashboard that listed initiatives in priority order, with the profile of each risk faced in the quarter, the risk profile trend, and a comment column for a year-end view. 

According to Warner, the key factors of success for ERM at Mars are as follows:

• The initiative focused on achieving operational and strategic objectives rather than compliance, which refers to adhering to established rules and regulations.
• The program evolved, often based on requests from business units, and incorporated continuous improvement. 
• The ERM team did not overpromise. It set realistic objectives.
• The ERM team periodically surveyed business units, management teams, and board advisers.

Enterprise Risk Management Example in Retail

Walmart is the world’s biggest retailer. As such, the company understands that its risk makeup is complex, given the geographic spread of its operations and its large number of stores, vast supply chain, and high profile as an employer and buyer of goods. 

In the 1990s, the company sought a simplified strategy for assessing risk and created an enterprise risk management plan with five steps founded on these four questions:

• What are the risks?
• What are we going to do about them?
• How will we know if we are raising or decreasing risk?
• How will we show shareholder value?

The process follows these five steps:

• Risk Identification: Senior Walmart leaders meet in workshops to identify risks, which are then plotted on a graph of probability vs. impact. Doing so helps to prioritize the biggest risks. The executives then look at seven risk categories (both internal and external): legal/regulatory, political, business environment, strategic, operational, financial, and integrity. Many ERM pros use risk registers to evaluate and determine the priority of risks. You can download templates that help correlate risk probability and potential impact in “ Free Risk Register Templates .”
• Risk Mitigation: Teams that include operational staff in the relevant area meet. They use existing inventory procedures to address the risks and determine if the procedures are effective.
• Action Planning: A project team identifies and implements next steps over the several months to follow.
• Performance Metrics: The group develops metrics to measure the impact of the changes. They also look at trends of actual performance compared to goal over time.
• Return on Investment and Shareholder Value: In this step, the group assesses the changes’ impact on sales and expenses to determine if the moves improved shareholder value and ROI.

To develop your own risk management planning, you can download a customizable template in “ Risk Management Plan Templates .”

Enterprise Risk Management Example in Agriculture

United Grain Growers (UGG), a Canadian grain distributor that now is part of Glencore Ltd., was hailed as an ERM innovator and became the subject of business school case studies for its enterprise risk management program. This initiative addressed the risks associated with weather for its business. Crop volume drove UGG’s revenue and profits. 

In the late 1990s, UGG identified its major unaddressed risks. Using almost a century of data, risk analysts found that extreme weather events occurred 10 times as frequently as previously believed. The company worked with its insurance broker and the Swiss Re Group on a solution that added grain-volume risk (resulting from weather fluctuations) to its other insured risks, such as property and liability, in an integrated program. 

The result was insurance that protected grain-handling earnings, which comprised half of UGG’s gross profits. The greater financial stability significantly enhanced the firm’s ability to achieve its strategic objectives. 

Since then, the number and types of instruments to manage weather-related risks has multiplied rapidly. For example, over-the-counter derivatives, such as futures and options, began trading in 1997. The Chicago Mercantile Exchange now offers weather futures contracts on 12 U.S. and international cities. 

Weather derivatives are linked to climate factors such as rainfall or temperature, and they hedge different kinds of risks than do insurance. These risks are much more common (e.g., a cooler-than-normal summer) than the earthquakes and floods that insurance typically covers. And the holders of derivatives do not have to incur any damage to collect on them.

These weather-linked instruments have found a wider audience than anticipated, including retailers that worry about freak storms decimating Christmas sales, amusement park operators fearing rainy summers will keep crowds away, and energy companies needing to hedge demand for heating and cooling.

This area of ERM continues to evolve because weather and crop insurance are not enough to address all the risks that agriculture faces. Arbol, Inc. estimates that more than $1 trillion of agricultural risk is uninsured. As such, it is launching a blockchain-based platform that offers contracts (customized by location and risk parameters) with payouts based on weather data. These contracts can cover risks associated with niche crops and small growing areas.

Enterprise Risk Management Example in Insurance

Switzerland’s Zurich Insurance Group understands that risk is inherent for insurers and seeks to practice disciplined risk-taking, within a predetermined risk tolerance. 

The global insurer’s enterprise risk management framework aims to protect capital, liquidity, earnings, and reputation. Governance serves as the basis for risk management, and the framework lays out responsibilities for taking, managing, monitoring, and reporting risks. 

The company uses a proprietary process called Total Risk Profiling (TRP) to monitor internal and external risks to its strategy and financial plan. TRP assesses risk on the basis of severity and probability, and helps define and implement mitigating moves. 

Zurich’s risk appetite sets parameters for its tolerance within the goal of maintaining enough capital to achieve an AA rating from rating agencies. For this, the company uses its own Zurich economic capital model, referred to as Z-ECM. The model quantifies risk tolerance with a metric that assesses risk profile vs. risk tolerance. 

To maintain the AA rating, the company aims to hold capital between 100 and 120 percent of capital at risk. Above 140 percent is considered overcapitalized (therefore at risk of throttling growth), and under 90 percent is below risk tolerance (meaning the risk is too high). On either side of 100 to 120 percent (90 to 100 percent and 120 to 140 percent), the insurer considers taking mitigating action. 

Zurich’s assessment of risk and the nature of those risks play a major role in determining how much capital regulators require the business to hold. A popular tool to assess risk is the risk matrix, and you can find a variety of templates in “ Free, Customizable Risk Matrix Templates .”

In 2020, Zurich found that its biggest exposures were market risk, such as falling asset valuations and interest-rate risk; insurance risk, such as big payouts for covered customer losses, which it hedges through diversification and reinsurance; credit risk in assets it holds and receivables; and operational risks, such as internal process failures and external fraud.

Enterprise Risk Management Example in Technology

Financial software maker Intuit has strengthened its enterprise risk management through evolution, according to a case study by former Chief Risk Officer Janet Nasburg. 

The program is founded on the following five core principles:

• Use a common risk framework across the enterprise.
• Assess risks on an ongoing basis.
• Focus on the most important risks.
• Clearly define accountability for risk management.
• Commit to continuous improvement of performance measurement and monitoring. 

ERM programs grow according to a maturity model, and as capability rises, the shareholder value from risk management becomes more visible and important. 

The maturity phases include the following:

• Ad hoc risk management addresses a specific problem when it arises.
• Targeted or initial risk management approaches risks with multiple understandings of what constitutes risk and management occurs in silos. 
• Integrated or repeatable risk management puts in place an organization-wide framework for risk assessment and response. 
• Intelligent or managed risk management coordinates risk management across the business, using common tools. 
• Risk leadership incorporates risk management into strategic decision-making. 

Intuit emphasizes using key risk indicators (KRIs) to understand risks, along with key performance indicators (KPIs) to gauge the effectiveness of risk management. 

Early in its ERM journey, Intuit measured performance on risk management process participation and risk assessment impact. For participation, the targeted rate was 80 percent of executive management and business-line leaders. This helped benchmark risk awareness and current risk management, at a time when ERM at the company was not mature.

Conduct an annual risk assessment at corporate and business-line levels to plot risks, so the most likely and most impactful risks are graphed in the upper-right quadrant. Doing so focuses attention on these risks and helps business leaders understand the risk’s impact on performance toward strategic objectives. 

In the company’s second phase of ERM, Intuit turned its attention to building risk management capacity and sought to ensure that risk management activities addressed the most important risks. The company evaluated performance using color-coded status symbols (red, yellow, green) to indicate risk trend and progress on risk mitigation measures.

In its third phase, Intuit moved to actively monitoring the most important risks and ensuring that leaders modified their strategies to manage risks and take advantage of opportunities. An executive dashboard uses KRIs, KPIs, an overall risk rating, and red-yellow-green coding. The board of directors regularly reviews this dashboard.

Over this evolution, the company has moved from narrow, tactical risk management to holistic, strategic, and long-term ERM.

Enterprise Risk Management Case Studies by Principle

ERM veterans agree that in addition to KPIs and KRIs, other principles are equally important to follow. Below, you’ll find examples of enterprise risk management programs by principles.

ERM Principle #1: Make Sure Your Program Aligns with Your Values

Raytheon Case Study U.S. defense contractor Raytheon states that its highest priority is delivering on its commitment to provide ethical business practices and abide by anti-corruption laws.

Raytheon backs up this statement through its ERM program. Among other measures, the company performs an annual risk assessment for each function, including the anti-corruption group under the Chief Ethics and Compliance Officer. In addition, Raytheon asks 70 of its sites to perform an anti-corruption self-assessment each year to identify gaps and risks. From there, a compliance team tracks improvement actions. 

Every quarter, the company surveys 600 staff members who may face higher anti-corruption risks, such as the potential for bribes. The survey asks them to report any potential issues in the past quarter.

Also on a quarterly basis, the finance and internal controls teams review higher-risk profile payments, such as donations and gratuities to confirm accuracy and compliance. Oversight and compliance teams add other checks, and they update a risk-based audit plan continuously.

ERM Principle #2: Embrace Diversity to Reduce Risk

State Street Global Advisors Case Study In 2016, the asset management firm State Street Global Advisors introduced measures to increase gender diversity in its leadership as a way of reducing portfolio risk, among other goals. 

The company relied on research that showed that companies with more women senior managers had a better return on equity, reduced volatility, and fewer governance problems such as corruption and fraud. 

Among the initiatives was a campaign to influence companies where State Street had invested, in order to increase female membership on their boards. State Street also developed an investment product that tracks the performance of companies with the highest level of senior female leadership relative to peers in their sector. 

In 2020, the company announced some of the results of its effort. Among the 1,384 companies targeted by the firm, 681 added at least one female director.

ERM Principle #3: Do Not Overlook Resource Risks

Infosys Case Study India-based technology consulting company Infosys, which employees more than 240,000 people, has long recognized the risk of water shortages to its operations. 

India’s rapidly growing population and development has increased the risk of water scarcity. A 2020 report by the World Wide Fund for Nature said 30 cities in India faced the risk of severe water scarcity over the next three decades. 

Infosys has dozens of facilities in India and considers water to be a significant short-term risk. At its campuses, the company uses the water for cooking, drinking, cleaning, restrooms, landscaping, and cooling. Water shortages could halt Infosys operations and prevent it from completing customer projects and reaching its performance objectives. 

In an enterprise risk assessment example, Infosys’ ERM team conducts corporate water-risk assessments while sustainability teams produce detailed water-risk assessments for individual locations, according to a report by the World Business Council for Sustainable Development .

The company uses the COSO ERM framework to respond to the risks and decide whether to accept, avoid, reduce, or share these risks. The company uses root-cause analysis (which focuses on identifying underlying causes rather than symptoms) and the site assessments to plan steps to reduce risks. 

Infosys has implemented various water conservation measures, such as water-efficient fixtures and water recycling, rainwater collection and use, recharging aquifers, underground reservoirs to hold five days of water supply at locations, and smart-meter usage monitoring. Infosys’ ERM team tracks metrics for per-capita water consumption, along with rainfall data, availability and cost of water by tanker trucks, and water usage from external suppliers. 

In the 2020 fiscal year, the company reported a nearly 64 percent drop in per-capita water consumption by its workforce from the 2008 fiscal year. 

The business advantages of this risk management include an ability to open locations where water shortages may preclude competitors, and being able to maintain operations during water scarcity, protecting profitability.

ERM Principle #4: Fight Silos for Stronger Enterprise Risk Management

U.S. Government Case Study The terrorist attacks of September 11, 2001, revealed that the U.S. government’s then-current approach to managing intelligence was not adequate to address the threats — and, by extension, so was the government’s risk management procedure. Since the Cold War, sensitive information had been managed on a “need to know” basis that resulted in data silos. 

In the case of 9/11, this meant that different parts of the government knew some relevant intelligence that could have helped prevent the attacks. But no one had the opportunity to put the information together and see the whole picture. A congressional commission determined there were 10 lost operational opportunities to derail the plot. Silos existed between law enforcement and intelligence, as well as between and within agencies. 

After the attacks, the government moved toward greater information sharing and collaboration. Based on a task force’s recommendations, data moved from a centralized network to a distributed model, and social networking tools now allow colleagues throughout the government to connect. Staff began working across agency lines more often.

Enterprise Risk Management Examples by Scenario

While some scenarios are too unlikely to receive high-priority status, low-probability risks are still worth running through the ERM process. Robust risk management creates a culture and response capacity that better positions a company to deal with a crisis.

In the following enterprise risk examples, you will find scenarios and details of how organizations manage the risks they face.

Scenario: ERM and the Global Pandemic While most businesses do not have the resources to do in-depth ERM planning for the rare occurrence of a global pandemic, companies with a risk-aware culture will be at an advantage if a pandemic does hit. 

These businesses already have processes in place to escalate trouble signs for immediate attention and an ERM team or leader monitoring the threat environment. A strong ERM function gives clear and effective guidance that helps the company respond.

A report by Vodafone found that companies identified as “future ready” fared better in the COVID-19 pandemic. The attributes of future-ready businesses have a lot in common with those of companies that excel at ERM. These include viewing change as an opportunity; having detailed business strategies that are documented, funded, and measured; working to understand the forces that shape their environments; having roadmaps in place for technological transformation; and being able to react more quickly than competitors. 

Only about 20 percent of companies in the Vodafone study met the definition of “future ready.” But 54 percent of these firms had a fully developed and tested business continuity plan, compared to 30 percent of all businesses. And 82 percent felt their continuity plans worked well during the COVID-19 crisis. Nearly 50 percent of all businesses reported decreased profits, while 30 percent of future-ready organizations saw profits rise. 

Scenario: ERM and the Economic Crisis  The 2008 economic crisis in the United States resulted from the domino effect of rising interest rates, a collapse in housing prices, and a dramatic increase in foreclosures among mortgage borrowers with poor creditworthiness. This led to bank failures, a credit crunch, and layoffs, and the U.S. government had to rescue banks and other financial institutions to stabilize the financial system.

Some commentators said these events revealed the shortcomings of ERM because it did not prevent the banks’ mistakes or collapse. But Sim Segal, an ERM consultant and director of Columbia University’s ERM master’s degree program, analyzed how banks performed on 10 key ERM criteria. 

Segal says a risk-management program that incorporates all 10 criteria has these characteristics: 

• Risk management has an enterprise-wide scope.
• The program includes all risk categories: financial, operational, and strategic. 
• The focus is on the most important risks, not all possible risks. 
• Risk management is integrated across risk types.
• Aggregated metrics show risk exposure and appetite across the enterprise.
• Risk management incorporates decision-making, not just reporting.
• The effort balances risk and return management.
• There is a process for disclosure of risk.
• The program measures risk in terms of potential impact on company value.
• The focus of risk management is on the primary stakeholder, such as shareholders, rather than regulators or rating agencies.

In his book Corporate Value of Enterprise Risk Management , Segal concluded that most banks did not actually use ERM practices, which contributed to the financial crisis. He scored banks as failing on nine of the 10 criteria, only giving them a passing grade for focusing on the most important risks. 

Scenario: ERM and Technology Risk  The story of retailer Target’s failed expansion to Canada, where it shut down 133 loss-making stores in 2015, has been well documented. But one dimension that analysts have sometimes overlooked was Target’s handling of technology risk. 

A case study by Canadian Business magazine traced some of the biggest issues to software and data-quality problems that dramatically undermined the Canadian launch. 

As with other forms of ERM, technology risk management requires companies to ask what could go wrong, what the consequences would be, how they might prevent the risks, and how they should deal with the consequences. 

But with its technology plan for Canada, Target did not heed risk warning signs. 

In the United States, Target had custom systems for ordering products from vendors, processing items at warehouses, and distributing merchandise to stores quickly. But that software would need customization to work with the Canadian dollar, metric system, and French-language characters. 

Target decided to go with new ERP software on an aggressive two-year timeline. As Target began ordering products for the Canadian stores in 2012, problems arose. Some items did not fit into shipping containers or on store shelves, and information needed for customs agents to clear imported items was not correct in Target's system. 

Target found that its supply chain software data was full of errors. Product dimensions were in inches, not centimeters; height and width measurements were mixed up. An internal investigation showed that only about 30 percent of the data was accurate. 

In an attempt to fix these errors, Target merchandisers spent a week double-checking with vendors up to 80 data points for each of the retailer’s 75,000 products. They discovered that the dummy data entered into the software during setup had not been altered. To make any corrections, employees had to send the new information to an office in India where staff would enter it into the system. 

As the launch approached, the technology errors left the company vulnerable to stockouts, few people understood how the system worked, and the point-of-sale checkout system did not function correctly. Soon after stores opened in 2013, consumers began complaining about empty shelves. Meanwhile, Target Canada distribution centers overflowed due to excess ordering based on poor data fed into forecasting software. 

The rushed launch compounded problems because it did not allow the company enough time to find solutions or alternative technology. While the retailer fixed some issues by the end of 2014, it was too late. Target Canada filed for bankruptcy protection in early 2015. 

Scenario: ERM and Cybersecurity System hacks and data theft are major worries for companies. But as a relatively new field, cyber-risk management faces unique hurdles.

For example, risk managers and information security officers have difficulty quantifying the likelihood and business impact of a cybersecurity attack. The rise of cloud-based software exposes companies to third-party risks that make these projections even more difficult to calculate. 

As the field evolves, risk managers say it’s important for IT security officers to look beyond technical issues, such as the need to patch a vulnerability, and instead look more broadly at business impacts to make a cost benefit analysis of risk mitigation. Frameworks such as the Risk Management Framework for Information Systems and Organizations by the National Institute of Standards and Technology can help.  

Health insurer Aetna considers cybersecurity threats as a part of operational risk within its ERM framework and calculates a daily risk score, adjusted with changes in the cyberthreat landscape. 

Aetna studies threats from external actors by working through information sharing and analysis centers for the financial services and health industries. Aetna staff reverse-engineers malware to determine controls. The company says this type of activity helps ensure the resiliency of its business processes and greatly improves its ability to help protect member information.

For internal threats, Aetna uses models that compare current user behavior to past behavior and identify anomalies. (The company says it was the first organization to do this at scale across the enterprise.) Aetna gives staff permissions to networks and data based on what they need to perform their job. This segmentation restricts access to raw data and strengthens governance. 

Another risk initiative scans outgoing employee emails for code patterns, such as credit card or Social Security numbers. The system flags the email, and a security officer assesses it before the email is released.

Examples of Poor Enterprise Risk Management

Case studies of failed enterprise risk management often highlight mistakes that managers could and should have spotted — and corrected — before a full-blown crisis erupted. The focus of these examples is often on determining why that did not happen. 

ERM Case Study: General Motors

In 2014, General Motors recalled the first of what would become 29 million cars due to faulty ignition switches and paid compensation for 124 related deaths. GM knew of the problem for at least 10 years but did not act, the automaker later acknowledged. The company entered a deferred prosecution agreement and paid a $900 million penalty. 

Pointing to the length of time the company failed to disclose the safety problem, ERM specialists say it shows the problem did not reside with a single department. “Rather, it reflects a failure to properly manage risk,” wrote Steve Minsky, a writer on ERM and CEO of an ERM software company, in Risk Management magazine. 

“ERM is designed to keep all parties across the organization, from the front lines to the board to regulators, apprised of these kinds of problems as they become evident. Unfortunately, GM failed to implement such a program, ultimately leading to a tragic and costly scandal,” Minsky said.

Also in the auto sector, an enterprise risk management case study of Toyota looked at its problems with unintended acceleration of vehicles from 2002 to 2009. Several studies, including a case study by Carnegie Mellon University Professor Phil Koopman , blamed poor software design and company culture. A whistleblower later revealed a coverup by Toyota. The company paid more than $2.5 billion in fines and settlements.

ERM Case Study: Lululemon

In 2013, following customer complaints that its black yoga pants were too sheer, the athletic apparel maker recalled 17 percent of its inventory at a cost of $67 million. The company had previously identified risks related to fabric supply and quality. The CEO said the issue was inadequate testing. 

Analysts raised concerns about the company’s controls, including oversight of factories and product quality. A case study by Stanford University professors noted that Lululemon’s episode illustrated a common disconnect between identifying risks and being prepared to manage them when they materialize. Lululemon’s reporting and analysis of risks was also inadequate, especially as related to social media. In addition, the case study highlighted the need for a system to escalate risk-related issues to the board. 

ERM Case Study: Kodak 

Once an iconic brand, the photo film company failed for decades to act on the threat that digital photography posed to its business and eventually filed for bankruptcy in 2012. The company’s own research in 1981 found that digital photos could ultimately replace Kodak’s film technology and estimated it had 10 years to prepare. 

Unfortunately, Kodak did not prepare and stayed locked into the film paradigm. The board reinforced this course when in 1989 it chose as CEO a candidate who came from the film business over an executive interested in digital technology. 

Had the company acknowledged the risks and employed ERM strategies, it might have pursued a variety of strategies to remain successful. The company’s rival, Fuji Film, took the money it made from film and invested in new initiatives, some of which paid off. Kodak, on the other hand, kept investing in the old core business.

Case Studies of Successful Enterprise Risk Management

Successful enterprise risk management usually requires strong performance in multiple dimensions, and is therefore more likely to occur in organizations where ERM has matured. The following examples of enterprise risk management can be considered success stories. 

ERM Case Study: Statoil 

A major global oil producer, Statoil of Norway stands out for the way it practices ERM by looking at both downside risk and upside potential. Taking risks is vital in a business that depends on finding new oil reserves. 

According to a case study, the company developed its own framework founded on two basic goals: creating value and avoiding accidents.

The company aims to understand risks thoroughly, and unlike many ERM programs, Statoil maps risks on both the downside and upside. It graphs risk on probability vs. impact on pre-tax earnings, and it examines each risk from both positive and negative perspectives. 

For example, the case study cites a risk that the company assessed as having a 5 percent probability of a somewhat better-than-expected outcome but a 10 percent probability of a significant loss relative to forecast. In this case, the downside risk was greater than the upside potential.

ERM Case Study: Lego 

The Danish toy maker’s ERM evolved over the following four phases, according to a case study by one of the chief architects of its program:

• Traditional management of financial, operational, and other risks. Strategic risk management joined the ERM program in 2006. 
• The company added Monte Carlo simulations in 2008 to model financial performance volatility so that budgeting and financial processes could incorporate risk management. The technique is used in budget simulations, to assess risk in its credit portfolio, and to consolidate risk exposure. 
• Active risk and opportunity planning is part of making a business case for new projects before final decisions.
• The company prepares for uncertainty so that long-term strategies remain relevant and resilient under different scenarios. 

As part of its scenario modeling, Lego developed its PAPA (park, adapt, prepare, act) model. 

• Park: The company parks risks that occur slowly and have a low probability of happening, meaning it does not forget nor actively deal with them.
• Adapt: This response is for risks that evolve slowly and are certain or highly probable to occur. For example, a risk in this category is the changing nature of play and the evolution of buying power in different parts of the world. In this phase, the company adjusts, monitors the trend, and follows developments.
• Prepare: This category includes risks that have a low probability of occurring — but when they do, they emerge rapidly. These risks go into the ERM risk database with contingency plans, early warning indicators, and mitigation measures in place.
• Act: These are high-probability, fast-moving risks that must be acted upon to maintain strategy. For example, developments around connectivity, mobile devices, and online activity are in this category because of the rapid pace of change and the influence on the way children play. 

Lego views risk management as a way to better equip itself to take risks than its competitors. In the case study, the writer likens this approach to the need for the fastest race cars to have the best brakes and steering to achieve top speeds.

ERM Case Study: University of California 

The University of California, one of the biggest U.S. public university systems, introduced a new view of risk to its workforce when it implemented enterprise risk management in 2005. Previously, the function was merely seen as a compliance requirement.

ERM became a way to support the university’s mission of education and research, drawing on collaboration of the system’s employees across departments. “Our philosophy is, ‘Everyone is a risk manager,’” Erike Young, deputy director of ERM told Treasury and Risk magazine. “Anyone who’s in a management position technically manages some type of risk.”

The university faces a diverse set of risks, including cybersecurity, hospital liability, reduced government financial support, and earthquakes.  

The ERM department had to overhaul systems to create a unified view of risk because its information and processes were not linked. Software enabled both an organizational picture of risk and highly detailed drilldowns on individual risks. Risk managers also developed tools for risk assessment, risk ranking, and risk modeling. 

Better risk management has provided more than $100 million in annual cost savings and nearly $500 million in cost avoidance, according to UC officials. 

UC drives ERM with risk management departments at each of its 10 locations and leverages university subject matter experts to form multidisciplinary workgroups that develop process improvements.

APQC, a standards quality organization, recognized UC as a top global ERM practice organization, and the university system has won other awards. The university says in 2010 it was the first nonfinancial organization to win credit-rating agency recognition of its ERM program.

Examples of How Technology Is Transforming Enterprise Risk Management

Business intelligence software has propelled major progress in enterprise risk management because the technology enables risk managers to bring their information together, analyze it, and forecast how risk scenarios would impact their business.

ERM organizations are using computing and data-handling advancements such as blockchain for new innovations in strengthening risk management. Following are case studies of a few examples.

ERM Case Study: Bank of New York Mellon 

In 2021, the bank joined with Google Cloud to use machine learning and artificial intelligence to predict and reduce the risk that transactions in the $22 trillion U.S. Treasury market will fail to settle. Settlement failure means a buyer and seller do not exchange cash and securities by the close of business on the scheduled date. 

The party that fails to settle is assessed a daily financial penalty, and a high level of settlement failures can indicate market liquidity problems and rising risk. BNY says that, on average, about 2 percent of transactions fail to settle.

The bank trained models with millions of trades to consider every factor that could result in settlement failure. The service uses market-wide intraday trading metrics, trading velocity, scarcity indicators, volume, the number of trades settled per hour, seasonality, issuance patterns, and other signals. 

The bank said it predicts about 40 percent of settlement failures with 90 percent accuracy. But it also cautioned against overconfidence in the technology as the model continues to improve. 

AI-driven forecasting reduces risk for BNY clients in the Treasury market and saves costs. For example, a predictive view of settlement risks helps bond dealers more accurately manage their liquidity buffers, avoid penalties, optimize their funding sources, and offset the risks of failed settlements. In the long run, such forecasting tools could improve the health of the financial market. 

ERM Case Study: PwC

Consulting company PwC has leveraged a vast information storehouse known as a data lake to help its customers manage risk from suppliers.

A data lake stores both structured or unstructured information, meaning data in highly organized, standardized formats as well as unstandardized data. This means that everything from raw audio to credit card numbers can live in a data lake. 

Using techniques pioneered in national security, PwC built a risk data lake that integrates information from client companies, public databases, user devices, and industry sources. Algorithms find patterns that can signify unidentified risks.

One of PwC’s first uses of this data lake was a program to help companies uncover risks from their vendors and suppliers. Companies can violate laws, harm their reputations, suffer fraud, and risk their proprietary information by doing business with the wrong vendor. 

Today’s complex global supply chains mean companies may be several degrees removed from the source of this risk, which makes it hard to spot and mitigate. For example, a product made with outlawed child labor could be traded through several intermediaries before it reaches a retailer. 

PwC’s service helps companies recognize risk beyond their primary vendors and continue to monitor that risk over time as more information enters the data lake.

ERM Case Study: Financial Services

As analytics have become a pillar of forecasting and risk management for banks and other financial institutions, a new risk has emerged: model risk . This refers to the risk that machine-learning models will lead users to an unreliable understanding of risk or have unintended consequences.

For example, a 6 percent drop in the value of the British pound over the course of a few minutes in 2016 stemmed from currency trading algorithms that spiralled into a negative loop. A Twitter-reading program began an automated selling of the pound after comments by a French official, and other selling algorithms kicked in once the currency dropped below a certain level.

U.S. banking regulators are so concerned about model risk that the Federal Reserve set up a model validation council in 2012 to assess the models that banks use in running risk simulations for capital adequacy requirements. Regulators in Europe and elsewhere also require model validation.

A form of managing risk from a risk-management tool, model validation is an effort to reduce risk from machine learning. The technology-driven rise in modeling capacity has caused such models to proliferate, and banks can use hundreds of models to assess different risks. 

Model risk management can reduce rising costs for modeling by an estimated 20 to 30 percent by building a validation workflow, prioritizing models that are most important to business decisions, and implementing automation for testing and other tasks, according to McKinsey.

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Table of Contents

Understanding project risk management, definition and explanation of project risk management, 4 key components of project risk management, risk identification, risk assessment, risk response planning, risk monitoring and control, 5 project risk management case studies, gordie howe international bridge project, fujitsu’s early-career project managers, vodafone’s complex technology project, fehmarnbelt project, lend lease project, project risk management at designveloper, how we manage project risks, advancements in project risk management, project risk management: 5 case studies you should not miss.

May 21, 2024

Exploring project risk management, one can see how vital it is in today’s business world. This article from Designveloper, “Project Risk Management: 5 Case Studies You Should Not Miss”, exists in order to shed light on this important component of project management.

We’ll reference some new numbers and facts that highlight the significance of risk management in projects. These data points are based on legit reports and will help create a good basis of understanding on the subject matter.

In addition, we will discuss specific case studies when risk management was successfully applied and when it was not applied in project management. These real world examples are very much important for project managers and teams.

It is also important to keep in mind that each project has associated risks. However through project risk management these risks can be identified, analyzed, prioritized and managed in order to make the project achieve its objectives. Well then, let’s take this journey of understanding together. Watch out for an analysis of the five case studies you must not miss.

Risk management is a very critical component of any project. Risk management is a set of tools that allow determining the potential threats to the success of a project and how to address them. Let’s look at some more recent stats and examples to understand this better.

Statistics show that as high as 70% of all projects are unsuccessful . This high failure rate highlights the need for efficient project risk management. Surprisingly, organizations that do not attach much importance to project risk management face 50% chances of their project failure. This results in huge losses of money and untapped business potential.

Additionally, poor performance leads to approximated 10% loss of every dollar spent on projects. This translates to a loss of $99 for every $1 billion invested. These statistics demonstrate the importance of project risk management in improving project success rates and minimizing waste.

Let us consider a project management example to demonstrate the relevance of the issue discussed above. Consider a new refinery being constructed in the Middle East. The project is entering a key phase: purchasing. Poor risk management could see important decisions surrounding procurement strategy, or the timing of the tendering process result in project failure.

Project risk management in itself is a process that entails the identification of potential threats and their mitigation. It is not reactionary but proactive.

This process begins with the identification of potential risks. These could be any time from budget overruns to delayed deliveries. After the risks are identified they are then analyzed. This involves estimating the probability of each risk event and the potential consequences to the project.

The next stage is risk response planning. This could be in the form of risk reduction, risk shifting or risk acceptance. The goal here is to reduce the impact of risks on the project.

Finally, the process entails identifying and tracking these risks throughout the life of a project. This helps in keeping the project on course and any new risks that might arise are identified and managed.

Let’s dive into the heart of project risk management: its four key components. These pillars form the foundation of any successful risk management strategy. They are risk identification, risk analysis, risk response planning, and risk monitoring and control. Each plays a crucial role in ensuring project success. This section will provide a detailed explanation of each component, backed by data and real-world examples. So, let’s embark on this journey to understand the four key components of project risk management.

Risk identification is the first process in a project risk management process. It’s about proactively identifying risks that might cause a project to fail. This is very important because a recent study has shown that 77% of companies had operational surprises due to unidentified risks.

There are different approaches to risk identification such as brainstorming, Delphi technique, SWOT analysis, checklist analysis, flowchart. These techniques assist project teams in identifying all potential risks.

Risk identification is the second stage of the project risk management process. It is a systematic approach that tries to determine the probability of occurrence and severity of identified risks. This step is very important; it helps to rank the identified risks and assists in the formation of risk response strategies.

Risk assessment involves two key elements: frequency and severity of occurrence. As for risk probability, it estimates the chances of a risk event taking place, and risk impact measures the impact associated with the risk event.

This is the third component of project risk management. It deals with planning the best ways to deal with the risks that have been identified. This step is important since it ensures that the risk does not have a substantial effect on the project.

One of the statistics stated that nearly three-quarters of organizations have an incident response plan and 63 percent of these organizations conduct the plan regularly. This explains why focusing only on risks’ identification and analysis without a plan of action is inadequate.

Risk response planning involves four key strategies: risk acceptance, risk sharing, risk reduction, and risk elimination. Each strategy is selected depending on the nature and potential of the risk.

Risk monitoring and control is the last step of project risk management. It’s about monitoring and controlling the identified risks and making sure that they are being addressed according to the plan.

Furthermore, risk control and management involve managing identified risks, monitoring the remaining risk, identifying new risks, implementing risk strategies, and evaluating their implementation during the project life cycle.

It is now high time to approach the practical side of project risk management. This section provides selected five case studies that explain the need and application of project risk management. Each case study gives an individual approach revealing how risk management can facilitate success of the project. Additionally, these case studies include construction projects, technology groups, among other industries. They show how effective project risk management can be, by allowing organizations to respond to uncertainties and successfully accomplish their project objectives. Let us now examine these case studies and understand the concept of risk in project management.

The Gordie Howe International Bridge is one of the projects that demonstrate the principles of project risk management. This is one of the biggest infrastructure projects in North America which includes the construction of a 6 lane bridge at the busiest commercial border crossing point between the U.S. and Canada.

The project scope can be summarized as: New Port of Entry and Inspection facilities for the Canadian and US governments; Tolls Collection Facilities; Projects and modifications to multiple local bridges and roadways. The project is administered via Windsor-Detroit Bridge Authority, a nonprofit Canadian Crown entity.

Specifically, one of the project challenges associated with the fact that the project was a big one in terms of land size and the community of interests involved in the undertaking. Governance and the CI were fundamental aspects that helped the project team to overcome these challenges.

The PMBOK® Guide is the contractual basis for project management of the project agreement. This dedication to following the best practices for project management does not end with bridge construction: It spreads to all other requirements.

However, the project is making steady progress to the objective of finishing the project in 2024. This case study clearly demonstrates the role of project risk management in achieving success with large and complicated infrastructure projects.

Fujitsu is an international company that deals with the provision of a total information and communication technology system as well as its products and services. The typical way was to employ a few college and school leavers and engage them in a two-year manual management training and development course. Nevertheless, this approach failed in terms of the following.

Firstly, the training was not comprehensive in its coverage of project management and was solely concerned with generic messaging – for example, promoting leadership skills and time management. Secondly it was not effectively reaching out to the need of apprentices. Thirdly the two year time frame was not sufficient to allow for a deep approach to the development of the required project management skills for this job. Finally the retention problems of employees in the train program presented a number of issues.

To tackle these issues, Fujitsu UK adopted a framework based on three dimensions: structured learning, learning from others, and rotation. This framework is designed to operate for the first five years of a participant’s career and is underpinned by the 70-20-10 model for learning and development. Rogers’ model acknowledges that most learning occurs on the job.

The initial training process starts with a three-week formal learning and induction program that includes the initial orientation to the organization and its operations, the fundamentals of project management, and business in general. Lastly, the participants are put on a rotational assignment in the PMO of the program for the first six to eight months.

Vodafone is a multinational mobile telecommunications group that manages telecommunications services in 28 countries across five continents and decided to undertake a highly complex technology project to replace an existing network with a fully managed GLAN in 42 locations. This project was much complex and thus a well grounded approach to risk management was needed.

The project team faced a long period of delay in signing the contract and frequent changes after the contract was signed until the project is baselined. These challenges stretched the time frame of the project and enhanced the project complexity.

In order to mitigate the risks, Vodafone employed PMI standards for their project management structure. This approach included conducting workshops, developing resource and risk management plan and tailoring project documentations as well as conducting regular lesson learned.

Like any other project, the Vodafone GLAN project was not an easy one either but it was completed on time and in some cases ahead of the schedule that the team had anticipated to complete the project. At the first stage 90% of migrated sites were successfully migrated at the first attempt and 100% – at second.

The Fehmarnbelt project is a real-life example of the strategic role of project risk management. It provides information about a mega-project to construct the world’s longest immersed tunnel between Germany and Denmark. It will be a four-lane highway and two-rail electrified tunnel extending for 18 kilometers and it will be buried 40 meters under the Baltic Sea.

This project is managed by Femern A/S which is a Danish government-owned company with construction value over more than €7 billion (£8. 2 billion). It is estimated to provide jobs for 3,000 workers directly in addition to 10,000 in the suppliers. Upon its completion, its travel between Denmark and Germany will be cut to 10 minutes by automobile and 7 minutes by rail.

The Femern risk management functions and controls in particular the role of Risk Manager Bo Nygaard Sørensen then initiated the process and developed some clear key strategic objectives for the project. They formulated a simple, dynamic, and comprehensive risk register to give a more complete risk view of the mega-project. They also created a risk index in order to assess all risks in a consistent and predictable manner, classify them according to their importance, and manage and overcome the risks in an appropriate and timely manner.

Predict! is a risk assessment and analysis tool that came in use by the team, which helps determine the effect of various risks on the cost of the construction of the link and to calculate the risk contingency needed for the project. This way they were able to make decisions on whether an immersed tunnel could be constructed instead of a bridge.

Lend Lease is an international property and infrastructure group that operates in over 20 countries in the world; the company offers a better example of managing project risks. The company has established a complex framework called the Global Minimum Requirements (GMRs) to identify risks to which it is exposed.

The GMRs have scope for the phase of the project before a decision to bid for a job is taken. This framework includes factors related to flooding, heat, biodiversity, land or soil subsidence, water, weathering, infrastructure and insurance.

The GMRs are organized into five main phases in line with the five main development stages of a project. These stages guarantee that vital decisions are made at the ideal time. The stages include governance, investment, design and procurement, establishment, and delivery.

For instance, during the design and procurement stage, the GMRs identify requisite design controls that will prevent environment degradation during design as well as fatal risk elimination during planning and procurement. This approach aids in effective management of risks and delivery of successful projects in Lend Lease.

Let’s take a closer look at what risk management strategies are used here at Designveloper – a top web & software development firm in Vietnam. We also provide a range of other services, so it is essential that we manage risks on all our projects in similar and effective ways. The following part of the paper will try to give a glimpse of how we manage project risk in an exemplary manner using research from recent years and include specific cases.

The following steps explain the risk management process that we use—from the identification of potential risks to managing them: Discovering the risks. We will also mention here how our experience and expertise has helped us in this area.

Risk management as a function in project delivery is well comprehended at Designveloper. Our method of managing the project risk is proactive and systematic, which enables us to predict possible problems and create successful solutions to overcome them.

One of the problems we frequently encounter is the comprehension of our clients’ needs. In most cases, clients come to us with a basic idea or concept. To convert these ideas into particular requirements and feature lists, the business analysts of our company have to collaborate with the client. The whole process is often a time-waster, and having a chance is missed.

To solve this problem, we’ve created a library of features with their own time and cost estimate. This library is based on data of previous projects that we have documented, arranged, and consolidated. At the present time when a client approaches us with a request, we can search for similar features in our library and give an initial quote. This method has considerably cut the period of providing the first estimations to our clients and saving the time for all participants.

This is only one of the techniques we use to mitigate project risks at Designveloper. The focus on effective project risk management has been contributing significantly to our successful operation as a leading company in web and software development in Vietnam. It is a mindset that enables us to convert challenges into opportunities and provide outstanding results for our clients.

In Designveloper, we always aim at enhancing our project risk management actions. Below are a couple examples of the advancements we’ve made.

To reduce the waiting time, we have adopted continuous deployment. This enables us to provide value fast and effectively. We release a minimum feature rather than a big feature. It helps us to collect the input from our customers and keep on improving. What this translates into for our customers is that they start to derive value from the product quickly and that they have near-continuous improvement rather than have to wait for a “perfect” feature.

We also hold regular “sync-up” meetings between teams to keep the information synchronized and transparent from input (requirements) to output (product). Changes are known to all teams and thus teams can prepare to respond in a flexible and best manner.

Some of these developments in project risk management have enabled us to complete projects successfully, and be of an excellent service to our clients. They show our support of the never-ending improving and our capability to turn threats into opportunities. The strength of Designveloper is largely attributed to the fact that we do not just control project risks – we master them.

To conclude, project risk management is an important element of nearly all successful projects. It is all about identification of possible problems and organization necessary measures that will result in the success of the project. The case studies addressed in this article illustrate the significance and implementation of project risk management in different settings and fields. They show what efficient risk management can result in.

We have witnessed the advantages of solid project risk management at Designveloper. The combination of our approach, powered by our track record and professionalism, has enabled us to complete projects that met all client’s requirements. We are not only managing project risks but rather mastering them.

We trust you have found this article helpful in understanding project risk management and its significance in the fast-changing, complicated project environment of today. However, one needs to mind that proper project management is not only about task and resource management but also risk management. And at Designveloper, our team is there to guide you through those risks and to help you realize your project’s objectives.

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Increasing Value and Resilience Through Project Risk Management: A Case Study in the IT Consulting Sector

• First Online: 19 March 2024

Cite this chapter

• Raffaele Testorelli 3 ,
• Anna Tiso 3 &
• Chiara Verbano 3  

Part of the book series: Management for Professionals ((MANAGPROF))

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In the current dynamic and uncertain business environment, small- and medium-sized enterprises (SMEs) are struggling to enhance their ability to adapt and resist to the changes while pursuing their strategic objectives. In particular, projects are gaining a crucial role for companies’ success, as the main vehicles for managing change and creating innovation. Consequently, Project Risk Management (PRM) is a widely used approach to foster the effect of positive events opportunities while mitigating those related to negative ones, with the final aim of creating value and resilience. For these reasons, there is growing interest in PRM as a value generation process for multiple project stakeholders. This research presents a case study conducted in an SME based in Italy and operating in the information technology (IT) consulting sector, addressing the literature gaps about the creation of value through PRM. From an academic perspective, it provides an overview of the topic, proposing a framework for the analysis of the relationships between the characteristics of the context, the PRM system implemented, and the value generated. Moreover, it supports practitioners with a new measurement system for the value generated through PRM and with guidelines to enhance value generation and resilience.

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The authors gratefully acknowledge the Grant VERB_SID19_01 funded by the University of Padova.

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Testorelli, R., Tiso, A., Verbano, C. (2024). Increasing Value and Resilience Through Project Risk Management: A Case Study in the IT Consulting Sector. In: Durst, S., Henschel, T. (eds) Small and Medium-Sized Enterprise (SME) Resilience. Management for Professionals. Springer, Cham. https://doi.org/10.1007/978-3-031-50836-3_13

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Fehmarnbelt Case Study

The next-generation transport mega-project connecting europe, fehmarnbelt tunnel key facts.

• The Fehmarnbelt tunnel will comprise a four-lane motorway and two electrified rail tracks. It consists of 79 individual elements, each 217 metres long and weighing 73,000 tonnes, equivalent to 14,000 elephants.
• Building the Fehmarnbelt tunnel will directly employ 3,000 people with many more in the supply chain.
• The link means it will now only take 10 minutes to travel from Denmark to Germany by car and 7 minutes by train. The project opens up the ScanMed Corridor, 1of 9 prioritised transport corridors within the EU.
• The Fehmarnbelt Tunnel contributes to the EU 2050 climate goals

A mega-project to transform the region

Femern A/S is breaking new ground in global transport systems with the Fehmarnbelt link. After a decade of planning, the world’s longest immersed tunnel will link Germany and Denmark and slash journey times from 2029.

Forty meters beneath the Baltic Sea, at 18 kilometres, it is Northern Europe’s largest construction project with a construction budget of over €7 billion ($8.2 billion). Critically, this mega-project has been designed to drive new levels of sustainability, efficiency and economic opportunities for the region.

Developing a risk strategy

The Femern executive management team, led by Bo Nygaard Sørensen , Risk Manager, set out key project goals for risk management process and culture:

• An easy to use, integrated and dynamic risk register together with a full risk picture across the mega-project.
• Develop a risk index to identify, categorise, manage and mitigate all risk in a structured, transparent and timely way. Underpinning this was an adherence to Danish government regulations and compliance.
• Establish an agreed level of risk management competency and knowledge across all Femern A/S employees.
• Capture all internal and external risks via Predict! to provide a real-time and accurate view of exposure, together with treatment plans.
• Drive thinking, strategies and culture with robust, regular reporting.

Growing risk maturity

Femern A/S engaged with Risk Decisions right from the outset; using the integrated Predict! risk database and Monte Carlo analysis platform to inform the decision-making on whether to build an immersed tunnel rather than a bridge.

The Femern A/S team were committed to leading a risk positive culture as risk maturity in construction evolved. Using a software programme like Predict! for the first time meant shifting from spreadsheets to a flexible, integrated tool.

Bo explains, “Our dedicated risk leaders believed in the cultural impact of the Predict! software. A mega-project like Fehmarnbelt required a risk management system integrated into the organisation, providing structure and cohesion.”

He adds, “Risk management demands a behaviour shift. We ensured buy-in by delivering specific training with Risk Decisions for risk owners and department heads, embedding learning with doing. Next steps were to support and fine-tune any gaps to motivate and empower the team.”

Embedding risk as a positive force

All strategic shifts involve challenges. Many organisations have a reactive approach to risk management. Femern have had risk management on top of their minds from the onset, implementing Predict! from the very beginning of the project. As the project evolved, so did Predict!’s capability. It is a never-ending process as the project and thus, the risks changes all the time.

Bo explains, “With previous mega-projects, risks were handled when they “appeared” from a management perspective. The process lacked structure and management and meant mitigation could only be partly transparent and documented.”

Implementing Predict! embedded risk thinking into processes and systems essential to managing timings. As Bo explains, “Anything that could postpone the project and disrupt the critical path and schedule is a risk. Putting a cost on risk makes people listen and time is often the most expensive part of projects at this scale. Yes, there are other risks, but the single most important factor is anything that interferes with time.”

Bo’s further cultivated a culture of positive risk with risk owners, “Everyone’s invested in this project being a success, so we don’t see risk as a negative,” he says. “Instead, it’s important to identify, mitigate and work with risks. Of course, historically, it has been seen as an admin burden, but now we show risk owners how it can be seen as the line of success running through the project.”

Leading a culture of risk management

Predict! provides an essential framework for Femern’s mega-project as, after ten years of planning, the main part of the construction starts.

For Bo, embedding risk management across the organisation “ensures we do the work we’re supposed to do.” Tying risk effectiveness back to core organisational values was a key implementation strategy and a significant win for Femern and Risk Decisions’ collaborative approach.

“Continuous improvement is a core value for us. With Predict! we can demonstrate governance, oversight, and management across all risk touchpoints to the board. And how this leads to continuous improvement,” says Bo. “It gives complete confidence to the executive management team and reassures everybody that the framework works, as it should. Ultimately, it delivers the results they want to see.”

Compliance is also essential, especially for projects of this profile and scale. “Predict! fulfils all the requirements of how we work with risk and how we document it, in line with ISO 31000 – as long as we’re using Predict! we’re compliant.”

Having the right risk partner helped the Femern team stay on track with their risk strategy. Bo explains, “The Risk Decisions team understood what we were trying to achieve and were able to respond quickly in terms of scaling any needs to this mega-project. That direction has really supported the outcomes.”

Bo concludes “The single most important issue is the support from the executive management, most of all the CEO. It’s the senior buy-in and understanding of the strategic value that risk brings that leads to success.”

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13 case studies on how risk managers are assessing their risk culture

Continuing on from last week's post, There’s no such thing as risk culture, or is there? , this is the third in a series of blogs in which we are summarising key insights gained from about 50 risk managers and CROs interviewed between December 2019 and May 2020.

There are various techniques and different mindsets on how to assess and measure risk culture. We round-up the very best case studies, tools and templates used by risk managers around the world.

To survey or not to survey?

If you start from a base of assuming you need a survey (or perhaps you have an executive or board who want one), then you are faced with two main choices:

• Include a number of questions in a larger employee engagement/culture survey, probably being run by HR (as one of our Member organisations did, only to discover the results didn’t align with their anecdotal feedback and experiences)
• Conduct a dedicated risk culture survey, which might later be re-run as a benchmark (as one former CRO at an international airline did upon joining the organisation).

However, not everyone believes a survey is the way to go. Or at least, not a survey in isolation.

It’s a self-assessment tool, for one thing, as former Bank of Queensland CRO Peter Deans pointed out in a recent Intelligence contribution (Members: access this here ). You may not get the true risk picture you need, if you are only asking people if they believe they are making risk-aware decisions and are satisfied with the culture.

UK risk consultant Roger Noon shared with us a variety of tools risk managers can use in-house to help understand behaviours and diagnose culture (Members: access these tools here) . Of quantitative risk culture surveys, he says: “Survey instruments can also be used so long as you and your sponsors recognise that they are typically very blunt tools, often with poor validity. They're very ‘point in time and context’ driven, and they don't really provide you with objective observable output. 

“However, they can be used to generate interesting data that creates helpful dialogue at the senior management table. They’re also useful to build engagement with the people that are part of the culture, and as part of a wider, triangulated set of data.”

In other instances, risk managers found it was not employees they initially needed to survey, but their board. Across different industries, different understandings of risk culture exist. If your board is asking about risk culture, it can be a good idea to check in that you (and they, among themselves) are all on the same page before beginning any broader projects. (Members: take a look at some sample questions about risk culture for the board here .)

So overt it’s covert

When it comes to an organisation’s overall approach to assessing and changing risk culture, there are also a few fundamentally different mindsets.

For some companies, the ‘culture overhaul’ needs to be a large project with lots of publicity and a big push from the top. In such cases, when it comes to driving change, extensive engagement and communications programs are planned, potentially including video.

We collected one case study, however, that stood out for its far more subtle and positive approach. In it, the head of risk at a large organisation with a few thousand staff spread across nine departments said there were a lot of preconceptions and quite a bit of nervousness around the idea of ‘working on risk culture’. This risk manager had therefore developed a different kind of self-assessment tool, which helped participants map their own risk culture using evidence-based attributes. 

At the end of the initial meeting (which took no more than an hour and a half), participants had identified their own areas for improvement and incorporated culture elements into their future risk planning. (Members: access this case study here .)

Sometimes risk managers reach a point where they simply have to be realistic about their resources and prospects for implementing large scale change.

In another example from the Middle East, an expat risk manager found it was a case of trying to move his company’s risk culture at different ‘clock speeds’ across the organisation’s verticals, catering to different levels of appetite, awareness and need for change between delivery teams and the C-Suite. (Members: access this case study here .)

And, finally, sometimes risk managers reach a point where they simply have to be realistic about their resources and prospects for implementing large scale change. If there’s no appetite from the top for a risk culture shift, the risk manager will have an uphill battle. We’ve collected ideas from the former risk leader at a government utility, who devised tactics for embedding changes into existing systems and processes to deliver better risk outcomes for the business. (Members: access these ideas here .)

Measuring, reporting and dashboards

We found that the facet of culture where everybody most wanted to know what everybody else was measuring and what they were doing in terms of reporting and dashboards.

Again, there were a number of different methods shared by our Members and contributors, as well as contrasting views on what actually should be measured.

For example, is it redundant to actually measure ‘risk culture’? After all, isn’t the entire point of improving risk culture to improve risk outcomes? Why not just focus on measuring the risk outcomes, with culture change happening in the background to facilitate? 

Certainly, this was the view of the former risk manager at a prominent United States government organisation, who spoke to us about building up their organisation’s risk capability over several years. (Members: read more on this here .)

Is it redundant to actually measure ‘risk culture’? After all, isn’t the entire point of improving risk culture to improve risk outcomes?

However, others saw value in tracking specific culture metrics, even if these goals were a means to an end. A scorecard or dashboard became a talking point to launch difficult conversations with different managers or executives, and the ability to show progress over time helped maintain momentum and commitment.

Over time, Peter Deans at BOQ developed and refined a ‘basket of risk culture measures’ along the same lines as the consumer price index, which he regularly updated and used to give leadership a ‘big picture view’ of how risk culture was doing.

Other contributing risk managers shared their scorecards and dashboards with us as templates, such as a scorecard example using a traffic light system across nine key risk indicators. We also collected ideas for dashboard metrics and a spreadsheet-based sunburst tool, alongside risk culture pillars.

On a final note, UK risk advisor Danny Wong shared a detailed case study on how to use data to drive an impactful risk narrative. For any risk managers who are striving to bring risk into line with many other functions in contemporary business – such as product development, sales, operations, and others that regularly use data strategically to inform decision making and best practice – this piece is essential reading. (Members: access this piece here .)

Risk Leadership Network’s Intelligence platform – our searchable database of peer-contributed case-studies, tools and templates – delves deeper into risk culture with more on diagnosing culture , addressing culture and ethics , and building a risk culture survey of boards . (Members only)

Are you an in-house risk manager who could benefit from collaborating with a global network of senior risk professionals talk to us about becoming a member today ., related posts you may be interested in.

There’s no such thing as risk culture, or is there?

5 ways to become a better leader in risk culture

Three useful tools to optimise a risk culture review

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Behavioural Risk Management

By René Doff

First published:

ISBN:  9781782724230

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Case Studies on Risk Management Failure

An Introduction to Behavioural Risk Management

Risk Management Context

Value-at-Risk as the Dominant Risk Management Tool in the Financial Industry

The Role of Regulation in Risk Management

Advances in Behavioural Economics and Finance

Behavioural Issues with Probability

Systems Theory

Using Scenarios

Making Robust Decisions

Advances in the Risk Management Process

Behavioural Risk Management in the Financial Markets

Countervailing Power

Behavioural Risk Management: Closing Thoughts

Appendix: Selective list of Behavioural Biases

Bibliography

Having understood the advantages and disadvantages of traditional risk management in the previous chapter, this chapter will analyse five case studies. In each of them, traditional risk management activities fell short because unwanted risks materialised with significant financial effect. The chapter will also provide some generic guidance that will help prepare us for the analysis in the remainder of this book. Despite the knowledge of hindsight, it is worth emphasising that none of the stakeholders involved in these examples would have stated at the time that risk management was unimportant for them. They all practiced some form of risk management to keep abreast of developments, and what really matters is the underlying belief of how risk management would be practised.

CASE STUDY 1: LEHMAN BROTHERS

Amid the global financial crisis, Lehman Brothers filed for bankruptcy on September 15, 2008. It is said to be the largest and most complex bankruptcy in US history. At the time, Lehman Brothers was the fourth largest investment bank in the world and was over 150 years old, being founded as a trading company in 1850. It evolved well and played an important role in the creation

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Innovative Case Study Simulates Risk Management Consultancy

May 22, 2019

HypoCom, a Madison-based steel widget company, has a global reputation with operations in France, Mexico, and Indonesia. Publicly traded, the company plans to acquire competitors and expand its market share. With so much at stake, it’s hard to believe the company has no risk management strategy.

That’s because HypoCom is the name of a fictional company, the brainchild of Tyler Leverty, an associate professor of risk and insurance and the Gerald D. Stephens CPCU Distinguished Chair in Risk Management and Insurance at the Wisconsin School of Business. Thanks to support from the John and Anne Oros Distinguished Chair for Inspired Learning in Business, an award that honors faculty innovation, Leverty has been able to bring his idea to life.

“I’m grateful to the generosity of the donors because this is something that I’ve wanted to do for a long time,” Leverty says.

Launched in Fall 2018 in Leverty’s risk financing course, the project asks students to put themselves in the shoes of risk consultants invited by HypoCom’s board of directors. HypoCom is a hypothetical case, but it is drawn from real-world elements that students would encounter in professional risk and insurance positions. As consultants, students must take the project from start to finish, tackling the initial assessments, final recommendations, and everything in between.

“The course title is risk financing, but this is really a class on corporate risk management,” Leverty says. “In the past, risk managers looked at each risk separately. With enterprise risk management (ERM), the way to manage risk is holistically, looking at risks and identifying the connection between them.”

According to Leverty, there are three main challenges with teaching a class that covers risk in a holistic manner: every company is different; it is difficult to understand all the risks inherent in a company and how they interact; and it is not possible to put one’s risk management plan to the test.

“The purpose of the HypoCom project is to overcome these limitations in important ways,” he says.

HypoCom case study design

Working in small teams, students are given an extensive profile about the company with data and information to assess, including corporate structure, operations, competitive environment, and risk management options. Students must address four specific risks facing HypoCom: warehouse fire risk, fluctuations in the price of steel, union strikes, and new entrants (competitors) into the field. Students also need to consider the correlations among these four risks.

Students use software called @Risk to create a simulation model to analyze each risk and its impact on the firm’s value, as well as identify appropriate risk management strategies. The teams are then tasked with writing a comprehensive final report that includes recommendations for HypoCom to follow.

Ryan Thielen (MBA ’19) says going through the case study process is valuable because it allows students to “simulate real-world experience in a classroom setting.”

“The HypoCom case offers a unique experience where students are able to function as consultants to evaluate a risk management problem and provide a strategic recommendation for how a company might best finance multiple risks,” Thielen says. “The case provides an opportunity to simulate and practice crucial skills including risk measurement, critical thinking, working in teams, and business writing.”

Prioritizing outcomes over answers

By working through the case study process, students are challenged with navigating uncertainty, building communication within their teams and through written reports, and using and interpreting data. Leverty says the mix of students taking the course—undergraduate and graduate students from business and other disciplines—also creates an environment where students can help each other and strengthen their skills while working in teams. Students with strong quantitative skills may shine with data analysis, for example, while other students may have strong written communication skills.

“The outcome that sets this case apart from anything else out there is that the students actually get to put what they’ve learned in practice by testing their own risk management plan.”

–Associate Professor Tyler Leverty

Leverty says learning to navigate uncertainty is probably the hardest aspect for students to grasp. The HypoCom case is intentionally designed with no single right answer. “There may be multiple routes, and to get to the final segment, they have to go out on a limb and make some assumptions,” he says.

“Bridging that gap from observing a case study to actually being able to implement one and do it on their own, that’s a huge piece,” Leverty says. “The outcome that sets this case apart from anything else out there is that the students actually get to put what they’ve learned in practice by testing their own risk management plan.”

A blueprint for the future

Leverty hopes to transfer what he’s created at WSB to other institutions. This semester, he’s been creating the materials to guide other instructors in incorporating the case study and tailoring it to their own classrooms.

Students like Jenna Herr (MBA ’19) have also found the project to be a blueprint they can take with them as they move forward into professional jobs.

“The opportunity to use the analysis to recommend appropriate risk management and to demonstrate risk management’s financial impact is what makes this assignment truly valuable,” Herr says. “I fully expect to use the process I developed through HypoCom to recommend risk management solutions in my future risk management roles.”

Since 2015, the Inspired Learning Chair and Inspired Learning Professorship awards support, recognize, and reward extraordinary scholars who advance business education at the Wisconsin School of Business.

Read about previous Inspired Learning projects:

• New Research-Based Course Inspires Real Conversation About Diversity in Organizations
• Flipping the Classroom, Inspired Learning Chair Paul Hoban Helps Students Move From Data to Insights

• Introduction
• Conclusions
• Article Information

ADHD indicates attention-deficit/hyperactivity disorder; CVD, cardiovascular disease.

a Controls were derived from the same base cohort as the cases; thus, a case with a later date of CVD diagnosis could potentially serve as a control for another case in the study.

Crude odds ratios (ORs) were based on cases and controls matched on age, sex, and calendar time. Adjusted ORs (AORs) were based on cases and controls matched on age, sex, and calendar time and adjusted for country of birth, educational level, somatic comorbidities (type 2 diabetes, obesity, dyslipidemia, and sleep disorders), and psychiatric comorbidities (anxiety disorders, autism spectrum disorder, bipolar disorder, conduct disorder, depressive disorder, eating disorders, intellectual disability, personality disorders, schizophrenia, and substance use disorders).

The solid lines represent the adjusted odds ratios, and the shaded areas represent the 95% CIs. In restricted cubic splines analysis, knots were placed at the 10th, 50th, and 90th percentiles of ADHD medication use.

eTable 1. International Classification of Diseases (ICD) Codes from the Swedish National Inpatient Register

eTable 2. Type of Cardiovascular Disease in Cases

eTable 3. Risk of CVD Associated With ADHD Medication Use Across Different Average Defined Daily Doses

eTable 4. Risk of CVD Associated With Cumulative Duration of Use of Different Types of ADHD Medications

eTable 5. Sensitivity Analyses of CVD Risk Associated With Cumulative Use of ADHD Medications, Based On Different Cohort, Exposure, and Outcome Definitions

eFigure. Risk of CVD Associated With Cumulative Use of ADHD Medications, Stratified by Sex

Data Sharing Statement

• Long-Term ADHD Medications and Cardiovascular Disease Risk JAMA Medical News in Brief December 26, 2023 Emily Harris
• Long-Term Cardiovascular Effects of Medications for ADHD—Balancing Benefits and Risks of Treatment JAMA Psychiatry Editorial February 1, 2024 Samuele Cortese, MD, PhD; Cristiano Fava, MD, PhD

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Zhang L , Li L , Andell P, et al. Attention-Deficit/Hyperactivity Disorder Medications and Long-Term Risk of Cardiovascular Diseases. JAMA Psychiatry. 2024;81(2):178–187. doi:10.1001/jamapsychiatry.2023.4294

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Attention-Deficit/Hyperactivity Disorder Medications and Long-Term Risk of Cardiovascular Diseases

• 1 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
• 2 Unit of Cardiology, Heart and Vascular Division, Department of Medicine, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
• 3 School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
• 4 Department of Applied Health Science, School of Public Health, Indiana University, Bloomington
• 5 Department of Psychological and Brain Sciences, Indiana University, Bloomington
• Editorial Long-Term Cardiovascular Effects of Medications for ADHD—Balancing Benefits and Risks of Treatment Samuele Cortese, MD, PhD; Cristiano Fava, MD, PhD JAMA Psychiatry
• Medical News in Brief Long-Term ADHD Medications and Cardiovascular Disease Risk Emily Harris JAMA

Question   Is long-term use of attention-deficit/hyperactivity disorder (ADHD) medication associated with an increased risk of cardiovascular disease (CVD)?

Findings   In this case-control study of 278 027 individuals in Sweden aged 6 to 64 years who had an incident ADHD diagnosis or ADHD medication dispensation, longer cumulative duration of ADHD medication use was associated with an increased risk of CVD, particularly hypertension and arterial disease, compared with nonuse.

Meaning   Findings of this study suggest that long-term exposure to ADHD medications was associated with an increased risk of CVD; therefore, the potential risks and benefits of long-term ADHD medication use should be carefully weighed.

Importance   Use of attention-deficit/hyperactivity disorder (ADHD) medications has increased substantially over the past decades. However, the potential risk of cardiovascular disease (CVD) associated with long-term ADHD medication use remains unclear.

Objective   To assess the association between long-term use of ADHD medication and the risk of CVD.

Design, Setting, and Participants   This case-control study included individuals in Sweden aged 6 to 64 years who received an incident diagnosis of ADHD or ADHD medication dispensation between January 1, 2007, and December 31, 2020. Data on ADHD and CVD diagnoses and ADHD medication dispensation were obtained from the Swedish National Inpatient Register and the Swedish Prescribed Drug Register, respectively. Cases included individuals with ADHD and an incident CVD diagnosis (ischemic heart diseases, cerebrovascular diseases, hypertension, heart failure, arrhythmias, thromboembolic disease, arterial disease, and other forms of heart disease). Incidence density sampling was used to match cases with up to 5 controls without CVD based on age, sex, and calendar time. Cases and controls had the same duration of follow-up.

Exposure   Cumulative duration of ADHD medication use up to 14 years.

Main Outcomes and Measures   The primary outcome was incident CVD. The association between CVD and cumulative duration of ADHD medication use was measured using adjusted odds ratios (AORs) with 95% CIs.

Results   Of 278 027 individuals with ADHD aged 6 to 64 years, 10 388 with CVD were identified (median [IQR] age, 34.6 [20.0-45.7] years; 6154 males [59.2%]) and matched with 51 672 control participants without CVD (median [IQR] age, 34.6 [19.8-45.6] years; 30 601 males [59.2%]). Median (IQR) follow-up time in both groups was 4.1 (1.9-6.8) years. Longer cumulative duration of ADHD medication use was associated with an increased risk of CVD compared with nonuse (0 to ≤1 year: AOR, 0.99 [95% CI, 0.93-1.06]; 1 to ≤2 years: AOR, 1.09 [95% CI, 1.01-1.18]; 2 to ≤3 years: AOR, 1.15 [95% CI, 1.05-1.25]; 3 to ≤5 years: AOR, 1.27 [95% CI, 1.17-1.39]; and >5 years: AOR, 1.23 [95% CI, 1.12-1.36]). Longer cumulative ADHD medication use was associated with an increased risk of hypertension (eg, 3 to ≤5 years: AOR, 1.72 [95% CI, 1.51-1.97] and >5 years: AOR, 1.80 [95% CI, 1.55-2.08]) and arterial disease (eg, 3 to ≤5 years: AOR, 1.65 [95% CI, 1.11-2.45] and >5 years: AOR, 1.49 [95% CI, 0.96-2.32]). Across the 14-year follow-up, each 1-year increase of ADHD medication use was associated with a 4% increased risk of CVD (AOR, 1.04 [95% CI, 1.03-1.05]), with a larger increase in risk in the first 3 years of cumulative use (AOR, 1.08 [95% CI, 1.04-1.11]) and stable risk over the remaining follow-up. Similar patterns were observed in children and youth (aged <25 years) and adults (aged ≥25 years).

Conclusions and Relevance   This case-control study found that long-term exposure to ADHD medications was associated with an increased risk of CVDs, especially hypertension and arterial disease. These findings highlight the importance of carefully weighing potential benefits and risks when making treatment decisions about long-term ADHD medication use. Clinicians should regularly and consistently monitor cardiovascular signs and symptoms throughout the course of treatment.

Attention-deficit/hyperactivity disorder (ADHD) is a common psychiatric disorder characterized by developmentally inappropriate inattentiveness, impulsivity, and hyperactivity. 1 , 2 Pharmacological therapy, including both stimulants and nonstimulants, is recommended as the first-line treatment for ADHD in many countries. 1 , 3 The use of ADHD medication has increased greatly in both children and adults during the past decades. 4 Although the effectiveness of ADHD medications has been demonstrated in randomized clinical trials (RCTs) and other studies, 5 , 6 concerns remain regarding their potential cardiovascular safety. 7 Meta-analyses of RCTs have reported increases in heart rate and blood pressure associated with both stimulant and nonstimulant ADHD medications. 5 , 7 - 9

As RCTs typically evaluate short-term effects (average treatment duration of 75 days), 7 it remains uncertain whether and to what extent the increases in blood pressure and heart rate associated with ADHD medication lead to clinically significant cardiovascular disease (CVD) over time. Longitudinal observational studies 10 - 12 examining the association between ADHD medication use and serious cardiovascular outcomes have emerged in recent years, but the findings have been mixed. A meta-analysis 13 of observational studies found no statistically significant association between ADHD medication and risk of CVD. However, the possibility of a modest risk increase cannot be ruled out due to several methodological limitations in these studies, including confounding by indication, immortal time bias, and prevalent user bias. Additionally, most of these studies had an average follow-up time of no more than 2 years. 13 , 14 Thus, evidence regarding the long-term cardiovascular risk of ADHD medication use is still lacking.

Examining the long-term cardiovascular risk associated with ADHD medicine use is clinically important given that individuals with a diagnosis of ADHD, regardless of whether they receive treatment, face an elevated risk of CVD. 15 Additionally, a substantial proportion of young individuals with ADHD continues to have impairing symptoms in adulthood, 16 necessitating prolonged use of ADHD medication. Notably, studies have indicated a rising trend in the long-term use of ADHD medications, with approximately half of individuals using ADHD medication for over 5 years. 17 Furthermore, evidence is lacking regarding how cardiovascular risk may vary based on factors such as type of CVD, type of ADHD medication, age, and sex. 13 Therefore, there is a need for long-term follow-up studies to address these knowledge gaps and provide a more comprehensive understanding of the cardiovascular risks associated with ADHD medication use. This information is also crucial from a public health perspective, particularly due to the increasing number of individuals receiving ADHD medications worldwide. 4

This study aimed to assess the association between cumulative use of ADHD medication up to 14 years and the risk of CVD by using nationwide health registers in Sweden. We hypothesized that longer cumulative use of ADHD medication would be associated with increased CVD risk. In addition, we aimed to examine whether the associations differ across types of ADHD medication, types of CVD, sex, and age groups.

We used data from several Swedish nationwide registers linked through unique personal identification numbers. 18 Diagnoses were obtained from the National Inpatient Register, 19 which contains data on inpatient diagnoses since 1973 and outpatient diagnoses since 2001. Information on prescribed medications was retrieved from the Swedish Prescribed Drug Register, which contains all dispensed medications in Sweden since July 2005 and includes information on drug identity based on the Anatomical Therapeutic Chemical (ATC) classification, 20 dispensing dates, and free-text medication prescriptions. Socioeconomic factors were obtained from the Longitudinal Integrated Database for Health Insurance and Labour Market studies. 21 Information on death was retrieved from the Swedish Cause of Death Register, 22 which contains information on all deaths since 1952. The study was approved by the Swedish Ethical Review Authority. Informed patient consent is not required for register-based studies in Sweden. The study followed the Reporting of Studies Conducted Using Observational Routinely Collected Health Data–Pharmacoepidemiological Research ( RECORD-PE ) guideline. 23

We conducted a nested case-control study of all individuals residing in Sweden aged 6 to 64 years who received an incident diagnosis of ADHD or ADHD medication dispensation 15 between January 1, 2007, and December 31, 2020. The diagnosis of ADHD ( International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ ICD-10 ] code F90) was identified from the National Inpatient Register. Incident ADHD medication dispensation was identified from the Swedish Prescribed Drug Register and was defined as a dispensation after at least 18 months without any ADHD medication dispensation. 24 Baseline (ie, cohort entry) was defined as the date of incident ADHD diagnosis or ADHD medication dispensation, whichever came first. Individuals with ADHD medication prescriptions for indications other than ADHD 25 and individuals who emigrated, died, or had a history of CVD before baseline were excluded from the study. The cohort was followed until the case index date (ie, the date of CVD diagnosis), death, migration, or the study end date (December 31, 2020), whichever came first.

Within the study cohort, we identified cases as individuals with an incident diagnosis of any CVD (including ischemic heart diseases, cerebrovascular diseases, hypertension, heart failure, arrhythmias, thromboembolic disease, arterial disease, and other forms of heart disease; eTable 1 in Supplement 1 ) during follow-up. For each case, the date of their CVD diagnosis was assigned as the index date. Using incidence density sampling, 26 up to 5 controls without CVD were randomly selected for each case from the base cohort of individuals with ADHD. The matching criteria included age, sex, and calendar time, ensuring that cases and controls had the same duration of follow-up from baseline to index date. Controls were eligible for inclusion if they were alive, living in Sweden, and free of CVD at the time when their matched case received a diagnosis of CVD, with the index date set as the date of CVD diagnosis of the matched case ( Figure 1 ). Controls were derived from the same base cohort as the cases. Thus, a case with a later date of CVD diagnosis could potentially serve as a control for another case in the study. 26

The main exposure was cumulative duration of ADHD medication use, which included all ADHD medications approved in Sweden during the study period, including stimulants (methylphenidate [ATC code N06BA04], amphetamine [ATC code N06BA01], dexamphetamine [ATC code N06BA02], and lisdexamfetamine [ATC code N06BA12]) as well as nonstimulants (atomoxetine [ATC code N06BA09] and guanfacine [ATC code C02AC02]). Duration of ADHD medication use was derived from a validated algorithm that estimates treatment duration from free text in prescription records. 25 The cumulative duration of ADHD medication use was calculated by summing all days covered by ADHD medication between baseline and 3 months prior to the index date. The last 3 months before the index date were excluded to reduce reverse causation, as clinicians’ perception of potential cardiovascular risks may influence ADHD medication prescription. This time window was chosen because routine psychiatric practice in Sweden limits a prescription to a maximum 3 months at a time. 27 Individuals with follow-up of less than 3 months were excluded.

We conducted conditional logistic regression analyses to estimate odds ratios (ORs) for the associations between cumulative durations of ADHD medication use and incident CVD. Crude ORs were adjusted for all matching variables (age, sex, and calendar time) by design. Adjusted ORs (AORs) were additionally controlled for country of birth (Sweden vs other), highest educational level (primary or lower secondary, upper secondary, postsecondary or postgraduate, or unknown; individuals aged <16 years were included as a separate category), and diagnoses of somatic (type 2 diabetes, obesity, dyslipidemia, and sleep disorders) and psychiatric comorbidities (anxiety disorders, autism spectrum disorder, bipolar disorder, conduct disorder, depressive disorder, eating disorders, intellectual disability, personality disorders, schizophrenia, and substance use disorders; eTable 1 in Supplement 1 ) before baseline. The association between cumulative ADHD medication use and incident CVD was assessed using both continuous and categorical measures (no ADHD medication use, 0 to ≤1, 1 to ≤2, 2 to ≤3, 3 to ≤5, and >5 years). To capture potential nonlinear associations, we used restricted cubic splines to examine ADHD medication use as a continuous measure throughout follow-up. 28 The associations were examined in the full sample and stratified by age at baseline, that is, children or youth (<25 years old) and adults (≥25 years old). Furthermore, to evaluate the association with dosage of ADHD medication, we estimated the risk of CVD associated with each 1-year increase in use of ADHD medication across different dosage groups categorized by the average defined daily dose (DDD; for instance, 1 DDD of methylphenidate equals 30 mg) during follow-up. 29

In subgroup analyses, we examined the associations between ADHD medication use and specific CVDs, including arrhythmias, arterial disease, cerebrovascular disease, heart failure, hypertension, ischemic heart disease, and thromboembolic disease (eTable 1 in Supplement 1 ). Additionally, we investigated the associations with CVD risk for the most commonly prescribed ADHD medications in Sweden, ie, methylphenidate, lisdexamfetamine, and atomoxetine, while adjusting for other ADHD medication use. We also examined sex-specific associations.

To further examine the robustness of our findings, we conducted 4 sensitivity analyses. First, we restricted the sample to ever users of ADHD medication to reduce unmeasured confounding between ADHD medication users and nonusers. Second, we assessed ADHD medication exposure over the entire follow-up period without excluding the 3 months prior to the index date. Third, to capture fatal cardiovascular events, we additionally included death by CVD in the outcome definition. Finally, we constructed a conditional logistic regression model that adjusted for propensity scores of ADHD medication use. Data management was performed using SAS, version 9.4 (SAS Institute Inc) and all analyses were performed using R, version 4.2.3 (R Foundation for Statistical Computing).

The study cohort consisted of 278 027 individuals with ADHD aged 6 to 64 years. The incidence rate of CVD was 7.34 per 1000 person-years. After applying exclusion criteria and matching, the analysis included 10 388 cases (median [IQR] age at baseline, 34.6 (20.0-45.7) years; 6154 males [59.2%] and 4234 females [40.8%]) and 51 672 matched controls (median [IQR] age at baseline, 34.6 [19.8-45.6] years; 30 601 males [59.2%] and 21 071 females [40.8%]) ( Figure 1 and Table 1 ). Median (IQR) follow-up in both groups was 4.1 (1.9-6.8) years. Among the controls, 3363 had received a CVD diagnosis after their index dates. The most common types of CVD in cases were hypertension (4210 cases [40.5%]) and arrhythmias (1310 cases [12.6%]; eTable 2 in Supplement 1 ). Table 1 presents the sociodemographic information and somatic and psychiatric comorbidities in cases and controls. In general, cases had higher rates of somatic and psychiatric comorbidities and a lower level of educational attainment compared with controls.

A similar proportion of cases (83.9%) and controls (83.5%) used ADHD medication during follow-up, with methylphenidate being the most commonly dispensed type, followed by atomoxetine and lisdexamfetamine. Longer cumulative duration of ADHD medication use was associated with an increased risk of CVD compared with nonuse (0 to ≤1 year: AOR, 0.99 [95% CI, 0.93-1.06]; 1 to ≤2 years: AOR, 1.09 [95% CI, 1.01-1.18]; 2 to ≤3 years: AOR, 1.15 [95% CI, 1.05-1.25]; 3 to ≤5 years: AOR, 1.27 [95% CI, 1.17-1.39]; and >5 years: AOR, 1.23 [95% CI, 1.12-1.36]) ( Figure 2 ). The restricted cubic spline model suggested a nonlinear association, with the AORs increasing rapidly for the first 3 cumulative years of ADHD medication use and then becoming stable thereafter ( Figure 3 ). Throughout the entire follow-up, each 1-year increase in the use of ADHD medication was associated with a 4% increased risk of CVD (AOR, 1.04 [95% CI, 1.03-1.05]), and the corresponding increase for the first 3 years was 8% (AOR, 1.08 [95% CI, 1.04-1.11]). We observed similar results when examining children or youth and adults separately ( Figure 2 ). The restricted cubic spline model suggested a similar nonlinear association, with higher AORs in children or youth than in adults, but the 95% CIs largely overlapped ( Figure 3 ). Furthermore, similar associations were observed for females and males (eFigure in Supplement 1 ). The dosage analysis showed that the risk of CVD associated with each 1 year of ADHD medication use increased with higher average DDDs. The risk was found to be statistically significant only among individuals with a mean dose of at least 1.5 times the DDD (eTable 3 in Supplement 1 ). For example, among individuals with a mean DDD of 1.5 to 2 or less (eg, for methylphenidate, 45 to ≤60 mg), each 1-year increase in ADHD medication use was associated with a 4% increased risk of CVD (AOR, 1.04 [95% CI, 1.02-1.05]). Among individuals with a mean DDD >2 (eg, for methylphenidate >60 mg), each 1-year increase in ADHD medication use was associated with 5% increased risk of CVD (AOR, 1.05 [95% CI, 1.03-1.06]).

When examining the risk for specific CVDs, we found that long-term use of ADHD medication (compared with no use) was associated with an increased risk of hypertension (AOR, 1.72 [95% CI, 1.51-1.97] for 3 to ≤5 years; AOR, 1.80 [95% CI 1.55-2.08] for >5 years) ( Table 2 ), as well as arterial disease (AOR, 1.65 [95% CI, 1.11-2.45] for 3 to ≤5 years; AOR, 1.49 [95% CI 0.96-2.32] for >5 years). However, we did not observe any statistically significant increased risk for arrhythmias, heart failure, ischemic heart disease, thromboembolic disease, or cerebrovascular disease ( Table 2 ). Furthermore, long-term use of methylphenidate (compared with no use) was associated with an increased risk of CVD (AOR, 1.20 [95% CI, 1.10-1.31] for 3 to ≤5 years; AOR, 1.19 [95% CI, 1.08-1.31]) for >5 years; eTable 4 in Supplement 1 ). Compared with no use, lisdexamfetamine was also associated with an elevated risk of CVD (AOR, 1.23 [95% CI, 1.05-1.44] for 2 to ≤3 years; AOR, 1.17 [95% CI, 0.98-1.40] for >3 years), while the AOR for atomoxetine use was significant only for the first year of use (1.07 [95% CI 1.01-1.13]; eTable 4 in Supplement 1 ).

In sensitivity analyses, we observed a similar pattern of estimates when the analysis was restricted to ever users of ADHD medications. Significantly increased risk of CVD was found when comparing ADHD medication use for 1 year or less with use for 3 to 5 or less years (AOR, 1.28 (95% CI, 1.18-1.38) or for use for more than 5 years (AOR, 1.24 [95% CI, 1.13-1.36]) (eTable 5 in Supplement 1 ). When assessing ADHD medication use across the entire follow-up period, and compared with no use, the pattern of estimates was similar to the main analysis (3 to ≤5 years: AOR, 1.28 [95% CI, 1.18-1.39]; >5 years: AOR, 1.25 [95% CI, 1.14-1.37]) (eTable 5 in Supplement 1 ). The analysis that included cardiovascular death as a combined outcome also had results similar to the main analysis. Moreover, when adjusting for propensity scores of ADHD medication use, the findings remained consistent (eTable 5 in Supplement 1 ).

This large, nested case-control study found an increased risk of incident CVD associated with long-term ADHD medication use, and the risk increased with increasing duration of ADHD medication use. This association was statistically significant both for children and youth and for adults, as well as for females and males. The primary contributors to the association between long-term ADHD medication use and CVD risk was an increased risk of hypertension and arterial disease. Increased risk was also associated with stimulant medication use.

We found individuals with long-term ADHD medication use had an increased risk of incident CVD in a dose-response manner in the first 3 years of cumulative ADHD medication use. To our knowledge, few previous studies have investigated the association between long-term ADHD medication use and the risk of CVD with follow-up of more than 2 years. 13 The only 2 prior studies with long-term follow-up (median, 9.5 and 7.9 years 30 , 31 ) found an average 2-fold and 3-fold increased risk of CVD with ADHD medication use compared with nonuse during the study period, yet 1 of the studies 30 included only children, and participants in the other study 31 were not the general population of individuals with ADHD (including those with ADHD and long QT syndrome). Furthermore, both studies were subject to prevalent user bias. Results from the current study suggest that the CVD risk associated with ADHD medication use (23% increased risk for >5 years of ADHD medication use compared with nonuse) is lower than previously reported. 30 , 31 Furthermore, we observed that the increased risk stabilized after the first several years of medication use and persisted throughout the 14-year follow-up period.

The association between ADHD medication use and CVD was significant for hypertension and arterial disease, while no significant association was observed with other types of cardiovascular events. To our knowledge, only 1 previous study 12 has examined the association between ADHD medication use and clinically diagnosed hypertension, and it found an increased risk, although the increase was not statistically significant. Furthermore, increased blood pressure associated with ADHD medication use has been well documented. 7 , 9 One study 32 found that blood pressure was mainly elevated during the daytime, suggesting that the cardiovascular system may recover at night. However, the cross-sectional nature of that study cannot preclude a long-term risk of clinically diagnosed hypertension associated with ADHD medication use. We also identified an increased risk for arterial disease. To date, no previous study has explored the association between ADHD medication use and arterial disease. A few studies have reported that ADHD medication may be associated with changes in serum lipid profiles, but the results were not consistent. 33 , 34 Further research is needed on the potential implications of ADHD medications for individuals’ lipid profiles. We did not observe any association between ADHD medication use and the risk of arrhythmias. A recent systematic review of observational studies of ADHD medication use reported an elevated risk of arrhythmias, but the finding was not statistically significant. 13 A review of RCTs also found that the use of stimulants was associated with an average increase in heart rate of 5.7 beats/min, 9 but no evidence of prolonged QT interval or tachycardia was found based on electrocardiograms. 7 Additionally, it is worth noting that some individuals receiving ADHD medications might be prescribed antiarrhythmic β-blockers to alleviate palpitation symptoms, thus potentially attenuating an association between ADHD medications and arrhythmias. Nevertheless, the absence of an association between ADHD medication use and clinically diagnosed arrhythmias in the present study does not rule out an increased risk for mild arrhythmias or subclinical symptoms, as palpitations and sinus tachycardia are not routinely coded as arrhythmia diagnoses. Further research is necessary to replicate our findings.

Regarding types of ADHD medication, findings of the present study suggest that increasing cumulative durations of methylphenidate and lisdexamfetamine use were associated with incident CVD, while the associations for atomoxetine were statistically significant only for the first year of use. Previous RCTs have reported increased blood pressure and heart rate with methylphenidate, lisdexamfetamine, and atomoxetine, 5 , 35 , 36 but the mechanisms behind these adverse effects are still a topic of debate; there might be differences in cardiovascular adverse effects in stimulants vs nonstimulants. 37

We found that the association between cumulative duration of ADHD medication use and CVD was similar in females and males. Previous investigations exploring sex-specific association found higher point estimates in females, although the differences were not statistically significant. 13 Research has indicated that females diagnosed with ADHD may demonstrate different comorbidity patterns and potentially have different responses to stimulant medications compared with males. 38 - 40 Therefore, additional studies are needed to explore and better understand the potential sex-specific differences in cardiovascular responses to ADHD medications.

A strength of this study is that data on ADHD medication prescriptions and CVD diagnoses were recorded prospectively, so the results were not affected by recall bias. The findings should, however, be interpreted in the context of several limitations. First, our approach for identification of patients with CVD was based on recorded diagnoses and there could be under ascertainment of cardiovascular diagnoses in the registers used. This means that some controls may have had undiagnosed CVD that did not yet require medical care, which would tend to underestimate associations between ADHD medication use and CVD. Second, exposure misclassification may have occurred if patients did not take their medication as prescribed. This misclassification, if nondifferential, would tend to reduce ORs such that the estimates we observed were conservative. Third, while we accounted for a wide range of potential confounding variables, considering the observational nature of the study and the possibility of residual confounding, we could not prove causality. It is possible that the association observed might have been affected by time-varying confounders. For example, other psychotropic medications and lifestyle factors could have affected both ADHD medication use and the occurrence of cardiovascular events. 41 , 42 Confounding by ADHD severity is also a potential factor to consider, as individuals with more severe ADHD symptoms may have more comorbidities and a less healthy lifestyle, which could affect the risk of CVD. Fourth, the study did not examine the risk of CVD among individuals with preexisting CVD. Individuals with preexisting CVD represent a distinct clinical group that requires careful monitoring; thus, evaluating the risk among them necessitates a different study design that carefully considers the potential impact of prior knowledge and periodic monitoring. Finally, the results by type of ADHD medication and type of CVD need to be replicated by studies with larger sample sizes.

The results of this population-based case-control study with a longitudinal follow-up of 14 years suggested that long-term use of ADHD medication was associated with an increased risk of CVD, especially hypertension and arterial disease, and the risk was higher for stimulant medications. These findings highlight the importance of carefully weighing potential benefits and risks when making treatment decisions on long-term ADHD medication use. Clinicians should be vigilant in monitoring patients, particularly among those receiving higher doses, and consistently assess signs and symptoms of CVD throughout the course of treatment. Monitoring becomes even more crucial considering the increasing number of individuals engaging in long-term use of ADHD medication.

Accepted for Publication: August 29, 2023.

Published Online: November 22, 2023. doi:10.1001/jamapsychiatry.2023.4294

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Zhang L et al. JAMA Psychiatry .

Corresponding Authors: Zheng Chang, PhD ( [email protected] ) and Le Zhang, PhD ( [email protected] ), Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 171 65 Stockholm, Sweden.

Author Contributions: Dr Zhang and Prof Chang had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Zhang, Johnell, Larsson, Chang.

Acquisition, analysis, or interpretation of data: Zhang, Li, Andell, Garcia-Argibay, Quinn, D'Onofrio, Brikell, Kuja-Halkola, Lichtenstein, Johnell, Chang.

Drafting of the manuscript: Zhang.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Zhang, Li.

Obtained funding: Larsson, Chang.

Administrative, technical, or material support: Garcia-Argibay, D'Onofrio, Kuja-Halkola, Lichtenstein, Chang.

Supervision: Andell, Lichtenstein, Johnell, Larsson, Chang.

Conflict of Interest Disclosures: Dr Larsson reported receiving grants from Takeda Pharmaceuticals and personal fees from Takeda Pharmaceuticals, Evolan, and Medici Medical Ltd outside the submitted work. No other disclosures were reported.

Funding/Support: This study was supported by grants from the Swedish Research Council for Health, Working Life, and Welfare (2019-01172 and 2022-01111) (Dr Chang) and the European Union’s Horizon 2020 research and innovation program under grant agreement 965381 (Dr Larsson).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

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Banking on interest rates: A playbook for the new era of volatility

The recent accelerated rise in global interest rates, the fastest in decades, brought the curtain down on an extended period of cheap money but provided little clarity on the longer-term outlook. In 2024, competing forces of tepid growth, geopolitical tension, and regional conflict are creating nearly equal chances of higher-for-longer benchmark rates and rapid cuts. In the banking industry, this uncertainty presents both risks and opportunities. But in the absence of recent precedent, many institutions lack the necessary playbook to tackle the challenge.

As rates have risen from their record lows, banks have in general profited from rising net interest margins (NIMs). However, if policy makers switch swiftly into cutting mode, banks may see the opposite effect. For now, futures markets predict the start of that process toward the end of 2024. In that context, the question facing risk managers is how they can retain the benefit of higher rates while preparing for cuts and managing the potential for macroeconomic surprises.

The question facing risk managers is how they can retain the benefit of higher rates while preparing for cuts and managing the potential for macroeconomic surprises.

The volatility playing out in rates markets is reflected in bank deposit trends, with customers more actively managing their cash to make the most of shifting monetary conditions. In Europe, deposits reached 63 percent of available stable funding (ASF) in 2023, compared with 57 percent in 2021. 1 Monitoring of liquidity coverage ratio and net stable funding ratio implementation in the EU – third report, European Banking Authority, June 15, 2023. In the US, conversely, the share of deposits over total liabilities fell over a similar period as money migrated to investments such as money market funds.

In the face of accelerating deposit flows, McKinsey research shows that bank risk management and funding performance has been highly variable. Between 2021 and 2023, the best-performing US and EU banks saw interest rate expenses rise 70 percent less than at the worst-performing banks (Exhibit 1). Among the drivers were better deposit and interest rate management.

Alongside the impacts of deposit flows, funding has come under pressure from other factors, including the steady withdrawal of pandemic-related central bank liquidity facilities. Meanwhile, innovations such as instant payments have motivated customers to make faster and larger transfers. These withdrawals can happen quickly and be fueled by social media, creating a powerful new species of risk.

In the context of a more uncertain environment, regulatory authorities are doubling down on oversight of the potential impacts of rate volatility—for example, by asking banks to mitigate the potential effects of rate normalization, increasing overall scrutiny, and demanding evidence of methodology upgrades. Among European supervisory priorities for 2024–26, banks are advised to sharpen their governance and strategic frameworks to strengthen asset and liability management (ALM) and develop new funding plans and contingency measures for short-term liquidity shocks, including evaluating the adequacy of assumptions supporting some behavioral models. 2 “SSM Supervisory Priorities, 2024-2026,” in Supervisory priorities and assessment of risks and vulnerabilities , European Central Bank, 2023. In the same vein, the Basel Committee on Banking Supervision in 2023 proposed a recalibration of shocks for interest rate risk in the banking book. Banks can achieve this by extending the time series used in model calibration from the current December 2015 standard to December 2022, bringing more volatile rate distributions into the equation.

In a recent McKinsey roundtable, 40 percent of Europe, Middle East, and Africa bank treasurers said the topic that will attract most regulatory attention in the coming period is liquidity risk, followed by capital risk and interest rate risk in the banking book (IRRBB). With these risks in mind, 34 percent of treasurers said their top priorities with respect to rate risk were enhancing models and analytics, revising pricing strategies on loans and deposits, and beefing up ALM governance and monitoring capabilities.

Most participants also expected treasury teams to get more involved in strategic planning and board engagement and to engage business units more closely to define pricing strategies and product innovation (Exhibit 2).

In response to these dynamics, we expect to see many banks revisiting the role of the treasury function in the months ahead. For many, this will mean moving away from approaches designed for the low-rate era and toward those predicated on uncertainty. In this article, we discuss how forward-looking banks are redesigning their treasury functions to obtain deeper insights into probabilities around interest rates and their impacts on pricing, customer behavior, deposits, and liquidity.

Five steps to enhancing the treasury function

To manage volatile interest rates more effectively, leading banks are revisiting practices in the treasury function that evolved during the low-interest-rate period and may no longer be fit for purpose—or at least should be updated for the new environment. Pioneers have taken steps in five broad focus areas: steering and monitoring, risk measurement and capabilities, stress testing, bank funding, and hedging.

Build efficiency and sophistication

A precondition of effective oversight of interest rate business is to ensure decision makers have a clear view of the current state of play. Currently, the standard approach across the industry is somewhat passive, meaning it is based on static or seldom-reviewed pricing and risk management decisions, often taken by relationship managers. Models are fed with low-frequency data, and banks use static fund transfer pricing (FTP) to calculate net interest margins. Monitoring often reflects regulatory timelines rather than the desire to optimize decision making.

Forward-looking banks are tackling these challenges through a more hands-on approach to steering and monitoring, including the following measures:

• dynamic reviews of FTP, reflecting microsegment behaviors and pricing strategies tied to customer lifetime value and the opportunity cost of liquidity
• increased product innovation to boost funding from both corporate and retail clients
• ensuring access to high-quality, frequent, and granular data, with systems equipped to send early warning signals on potential changes in customer behaviors, especially to capture early signs of liquidity shifts
• use of risk limits and targets as active steering mechanisms, bolstered by links to incentives
• automation of reporting and monitoring, so liquidity and other events can be scaled internally much faster, backed by real-time data where possible

Upgrade IRRBB measurement and capabilities

Leading banks are getting a grip on IRRBB risk in areas such as balance sheet management, pricing, and collateral. Many have assembled dedicated teams to help them make more effective decisions. Given the threat to deposits, some are making greater use of scenario-based frameworks, bringing together liquidity and interest rate risk management. They are using real-time data to inform funding and pricing decisions.

To ensure they consider all aspects of rate risk, leading banks employ a cascade of models, feeding the outputs into steering and stress-testing frameworks, and capturing behavioral indicators that can inform balance sheet planning and hedging activities. Some banks are employing behavioral models to forecast loan acceptance rates and credit line drawings. Best practice involves using statistical grids differentiated by type of customer, product, and process phase.

When it comes to loans, some banks are leveraging AI to predict prepayments and their impacts on balance sheets and hedging requirements. Best practice in prepayments modeling is to move away from linear models and toward machine learning algorithms such as random forests to consider nonlinear relationships (for instance, between prepayments and interest rate variation) and loan features (for example, embedded options), as well as behavioral factors. We see five key steps:

• Customer segmentation . Banks can use AI to achieve granulated segmentation—for example, incorporating behavioral factors.
• Prepayment behavior . Banks can quantify constant prepayments and prepayments subject to criteria including interest rate levels, prepayment penalties, age of mortgage, and borrower characteristics. Leading banks establish a parent model and leverage customer segmentation to derive dedicated prepayment functions, taking into account customer protections such as statutory payment holidays.
• Interest rate scenarios . Banks can employ Monte Carlo simulations and other models to analyze a range of scenarios, including extreme and regulatory scenarios, and simulate potential prepayment behaviors for each scenario.
• Hedging ratios and strategy . Decision makers should evaluate the value of mortgages under different interest scenarios and derive sensitivities to economic value and P&L. They can then select hedging instruments with the aim of neutralizing scenario impacts.
• Pricing . Mortgage pricing can be adjusted based on maturity and potential prepayment behavior. Banks can use fund transfer pricing, with risks handled by a dedicated team in the treasury function.

Another important focus area is deposit decay. Many banks still prioritize moving-average approaches segmented by maturity and backed by expert judgment. A best practice would be to identify a core balance through a combined expert and statistical approach, looking at trends across customer segmentation, core balance modeling, deposit volume modeling, deposit beta and pass-through rates, and replicating portfolio/hedge strategies. This would mean leveraging AI and high-frequency data relating to transactions, to estimate each account’s non-operational liquidity, which customers may be more likely to move elsewhere (see sidebar “Case study: Deposit modeling to limit deposit erosion”). Some banks also use survival models to gauge non-linearities in deposit behaviors.

Case study: Deposit modeling to limit deposit erosion

One bank achieved an equivalent of €150 million to €200 million positive P&L impact on €30 billion of deposits by using AI techniques for repricing. The tool provided transparency on the following measures:

• the amount of liquidity at risk for each client—that is, the excess liquidity the client could potentially invest or move freely to other banks
• the churn probability for each client, or the probability the client would move the liquidity if the bank took no action, based on client sophistication, the quality and intensity of the client’s relationship with the bank, and the level of market competition
• the customer value at risk, an estimate of future revenues that would be at risk if the client moved the liquidity elsewhere (for example, including not only the opportunity cost of funding, but also revenues from related services)

Armed with this transparency, the bank was able to formulate client-specific strategies for repricing actions and product offerings (for example, investment products and transaction banking services), optimizing both its funding sources and profitability. New capabilities to support the effort included a deposits command center, producing a real-time dashboard for monitoring, including early warning triggers, sales team mobilization, and new product offering, especially for cash-rich corporate clients.

In the context of IRRBB strategy, leading banks are keeping a close eye on both deposit beta and pass-through rates (the portion of a change in the benchmark rate that is passed on to the deposit rate). They back their judgments with views on client stickiness, which they traditionally arrive at through expert judgment and market research. A more advanced approach is to derive regime-based elasticities, capturing data from historical economic cycles.

Better modeling enables more resilience: One bank’s story

A European global bank wanted to improve its forecasting in a rising-interest-rate context. Managers decided to focus more on customer behavior. They moved away from expert-judgment buffers to AI and stochastic modeling and a more focused approach to model calibration. They also updated scenario planning based on regulatory guidelines and best-in-class approaches, such as an interest rate risk in the banking book (IRRBB) dynamic balance sheet methodology. Through these changes, the bank was able to estimate its duration gap (between assets and liabilities) more accurately and thereby reduce delta economic value of equity (EVE). As a result, the bank recorded a 70-basis-point uplift in return on equity, resulting from capital savings on interest rate risk and a direct P&L impact from reduced hedging.

Finally, risks need to be optimally matched with hedges. The recent trend is to use stochastic models to support hedging decisions, enabling banks to gauge non-linearities. Forward-looking banks increasingly integrate deposit, prepayment, and pipeline modeling directly into their hedging strategies. They also ensure model risk is closely monitored, with models recalibrated frequently to reduce reliance on expert input (see sidebar “Better modeling enables more resilience: One bank’s story”).

Improve stress testing

Several players are integrating interest rate risk, credit spread risk, liquidity risk, and funding concentration risk in both regulatory and internal stress tests. Indeed, the IRRBB, liquidity risk, and market risk (credit spread risk in the banking book, or CSRBB) highlight the trade-off between capital and liquidity regulations. In short, higher capital requirements may reduce the need for excessive liquidity, and vice versa, for a bank with stable funding—a situation that remains a challenge to current regulatory frameworks.

Stress testing to measure interest rate risk is also evolving, with some banks adopting reverse stress testing (see sidebar “Enhancing Basel's interest rate risk measures: Exploring the efficacy of reverse stress testing and VAR”).

Enhancing Basel’s interest rate risk measures: Exploring the efficacy of reverse stress testing and VAR

Research conducted by a group of bank risk managers suggests that the current supervisory outlier tests for interest rate risk in the banking book (IRRBB) may not adequately address all significant risk scenarios. Specifically, the scenarios outlined in the BCBS 368 guidelines for stress-testing economic value of equity (EVE) and net interest income (NII) may fall short in identifying substantial IRRBB risks. This oversight could make it more difficult for banks to recognize material risks of loss, especially if they have complex or unconventional portfolios.

To identify more material risks, experts are recommending a shift in approach. Instead of focusing solely on extreme and plausible scenarios, they are advised to consider all possible scenarios and integrate reverse stress testing. This would involve simulating thousands of historical and hypothetical scenarios, covering almost the entire spectrum of possible yield curves. After computing NII and EVE, attention would be directed to the scenarios that could have the most adverse impact on the bank’s balance sheet.

In alignment with this proposed methodology, Australian banks will be mandated from 2025 to calculate IRRBB capital using measures of expected shortfall rather than value at risk (VAR). The change is intended to incorporate tail risk, with the new methodology utilizing data from the past seven years, coupled with a distinct one-year stress period.

In upgrading their stress-testing frameworks and interest rate strategies, banks need to balance net interest income (NII) and economic value of equity (EVE) risks that may materialize as a function of rate volatility. On NII, banks can productively apply scenario-based yield curve analysis across regulatory, market, and bank-specific variables and weigh these in the context of overall balance sheet exposures, hedges, and factors including deposits, prepayments, and committed credit lines. Additional economic risks include basis risk, option risk, and credit spread risk, which also should be measured.

Tailor planning

Bank funding plans are often generic, periodic, and spread across different frameworks and methodologies, including funding plans, capital plans, internal capital adequacy assessment processes (ICAAP), and internal liquidity adequacy assessment processes (ILAAP). They are often designed for a range of purposes and audiences and updated only when prompted by regulatory requirements. In future, banks will need dynamic, diversified, and granular funding plans—for example, tailored to products and regions. The plans should reflect flexible and contingent funding sources, central bank policies, and the trade-off between risks and costs.

Embrace dynamic hedging strategies

In the era of low rates, hedging of interest rate risk was a less prominent activity. Banks often employed simple, static, short-term, or isolated strategies, mostly aimed at protecting P&L. Few banks paid a great deal of attention to collateral management.

Now, in a more volatile rate environment, the potential for losses is much higher, suggesting banks need more sophisticated, agile, and frequent hedging to respond to shifts in interest rates, credit spreads, and customer deposit behaviors (Exhibit 3). Indeed, in 2023, the traded volume of euro-denominated interest rate derivatives increased by 3.4 times compared with 2020, according to the International Swaps and Derivatives Association. 3 “Interest rate derivatives US: Transaction data,” ISDA.

Hedging strategies are evolving to be dynamic, horizontally integrated across the organization, and wedded to risk appetite frameworks, so banks can balance P&L priorities and reductions in tail risk. On the ground, banks will likely need to recalibrate their strategies frequently, ideally leveraging a comprehensive scenario-based approach to reflect changes in the external environment. Many, for example, have already revisited hedging to reflect higher rates, but as rates fall, they will need to assess factors such as the impact of convexity on short positions. The objective of these exercises would ideally extend beyond risk mitigation to the optimization of NII (see sidebar “Replication and hedging: The upsides of NIM optimization”).

Replication and hedging: The upsides of NIM optimization

Broadly, banks may consider four approaches to replication and hedging, each of which offers benefits that will vary according to the bank’s unique asset base.

Static replication is a widely applied and robust approach that involves derivation and adjustment of cash flows from deposit volume models for deposit rate elasticity and pass-through rates. The remainder of cash flows are replicated with bonds, interest rate swaps, or loans. Future deposit growth can be incorporated if desired.

Dynamic hedging of present value of net interest margin (NIM) treats the deposit portfolio like a structured product. Banks calculate the present value of NIM arising from deposits, enabling derivation of present value sensitivity to changes in interest rates. The method supports dynamic hedging and can take into account negative convexity.

Static NIM optimization provides the recommended trade-off between granularity and sophistication on the one hand and usability on the other, and it is our preferred approach. It involves design of the fixed-income portfolio to replicate deposit balance dynamics over a sample period. The analyst then selects the portfolio yielding the most stable margin, represented by minimization of margin standard deviation of the spread between the portfolio return and deposit rate. The approach enables NIM maximization, with the caveat that shorter tenors tend to be preferred in periods of low benchmark rates.

Dynamic NIM optimization permits banks to model future interest rates with NIM and investment strategy optimized for a future horizon. Again, NIM can be maximized, but the approach requires assumptions on volume growth, and the optimization horizon may not extend to the full rate cycle.

A key principle of best-in-class hedging strategy is that a proactive, forward-looking approach tends to work best and will enable banks to hedge more points on the yield curve. And with forward-looking scenario analysis, they should be able to anticipate risks more effectively. Consider the case of a bank that was exposed to falling interest rates and did not meet the regulatory threshold for outliers under the new IRRBB rules for changes in NII. Through analysis of potential client migrations to other products and a push to help clients make those transfers, combined with a new multi-billion-dollar derivative hedging strategy, the bank brought itself within the threshold.

Banks should not view hedging as a stand-alone activity but rather as integrated with risk management, backed by investment in talent and education to ensure teams choose the right hedges for the right situation. These may be traditional interest rate derivatives but equally could be options or swaptions to bring more flexibility to the hedging strategy. AI will be table stakes to support decision making and identify risks before they materialize. A more automated approach to data analytics will likely be required. And collateral management should be a core element of hedging frameworks, with analytics employed to forecast collateral valuations and needs, optimize liquidity reserves, and mitigate margin call risk.

Next steps: Making change happen

To effectively implement change across the activities highlighted here, best practice would be to bring together modeling capabilities under a dedicated data strategy. The target state should be comprehensive capabilities, a unified and actionable scenario-based framework, and routine use of AI techniques and behavioral data for decisions around pricing and collateral. Most likely, a talent strategy also will be required to support capability building across analytics, trading, finance, pricing, and risk management.

Banks must marshal a broad range of market data to support effective modeling. The data will include all credit lines, including both on–balance sheet and off–balance sheet items, deposit lines, fixed-income assets and liabilities, capital items, and other items on the banking book. Ideally, banks would assemble 15 to 20 years of data, which would take in the previous period of rising interest rates from 2004 to 2007. Alongside these basic resources, banks need information on historical residual balances, amortization plans, optionality, currencies, indexing, counterparty information, behavioral insights, and a full set of macro data. Some cutting-edge models incorporate about 150 different features.

Armed with comprehensive data, banks can build behavioral models (for example, prepayments, deposits) to estimate parameters and infer behavioral effects in different scenarios. They can then integrate behavioral outputs into stress-testing simulations, alongside expert-based insights. Once macroeconomic data has been inputted, banks should be able to compute delta NII and EVE for three years. Visualization tools and hedging replica analysis can help teams clarify their insights and test their hedging strategies across risk factors.

Banks that have embraced the levers discussed here have set themselves on a course to more proactive and effective interest rate risk management. Through a sharper focus on high-quality data and the use of AI and scenario-based frameworks, banks have shown they can make better decisions, upgrade their hedging capabilities, optimize the cost of funding, and ensure they stay within regulatory thresholds. In short, they will be equipped to respond faster and more flexibly as interest rates enter a new era of volatility.

Andreas Bohn is a partner in McKinsey’s Frankfurt office, Sebastian Schneider is a senior partner in the Munich office, Enrique Briega is a knowledge expert in the Madrid office, and Mario Nargi is an associate partner in the Milan office.

The authors wish to thank Gonzalo Oliveira and Stefano Terra for their contributions to this article.

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How Retailers Became Ad Platforms

• Sebastian Gabel,
• Duncan Simester,
• Artem Timoshenko

It’s a major growth opportunity — if companies can navigate the strategic challenges.

Major retailers are today, most notably Amazon, are creating and operating their own advertising platforms — and they’re making millions doing it. McKinsey estimates that by 2026, retail media will add $1.3 trillion to enterprise values in the U.S. alone, with profit margins between 50% and 70%. In this article, the authors introduce readers to the main kinds of retail media, discuss three strategic challenges that they present, and provide guidance for effectively managing those challenges.

A rapidly growing number of major retailers are today creating and operating their own advertising platforms — a phenomenon widely referred to as retail media.  Nobody has had more success in the space than Amazon, which in 2023 earned $46.9 billion from advertising, comprised primarily of sponsored ads on its site. This figure exceeds the annual global revenue of Coca-Cola and makes Amazon the third-largest advertising platform in the United States, behind only Google and Facebook.

• SG Sebastian Gabel is an assistant professor of marketing at Erasmus University. His research focuses on developing deep learning for targeting applications in retailing. Prior to his academic career, Sebastian co-founded a retail-media services company that was sold to the Schwarz global retail group.
• DS Duncan Simester is the NTU Professor of Marketing at the MIT Sloan School of Management. His research focuses on marketing strategy, go-to-market strategies, and the use of artificial intelligence and experiments to improve business decisions. He regularly consults with companies on these topics.
• AT Artem Timoshenko is an assistant professor of marketing at the Kellogg School of Management, at Northwestern University. His research focuses on applications of AI to marketing analytics and customer insights.

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This paper is in the following e-collection/theme issue:

Published on 24.6.2024 in Vol 26 (2024)

Finding Medical Photographs of Patients Online: Randomized, Cross-Sectional Study

Authors of this article:

Original Paper

• Zack Marshall 1, 2 , MSW, PhD   ; 
• Maushumi Bhattacharjee 3 , LLB, LLM   ; 
• Meng Wang 1 , PhD   ; 
• Abdul Cadri 4 , MPH   ; 
• Hannah James 5   ; 
• Shabnam Asghari 6 , MD, MPH, PhD   ; 
• Rene Peltekian 7 , MSW   ; 
• Veronica Benz 1 , MSW   ; 
• Vanessa Finley-Roy 8 , SW, MSc   ; 
• Brynna Childs 2, 9 , BA, MISt   ; 
• Lauren Asaad 1 , BHSc   ; 
• Michelle Swab 10 , MA, MLIS   ; 
• Vivian Welch 11 , PhD   ; 
• Fern Brunger 12 , PhD   ; 
• Chris Kaposy 12 , PhD  

1 Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada

2 School of Social Work, McGill University, Montreal, QC, Canada

3 Faculty of Law, McGill University, Montreal, QC, Canada

4 Department of Family Medicine, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada

5 Department of Anatomy & Cell Biology, McGill University, Montreal, QC, Canada

6 Faculty of Medicine, Memorial University of Newfoundland, St John's, NL, Canada

7 Renison University College, University of Waterloo, Waterloo, ON, Canada

8 Faculty of Medicine, Universite de Montreal, Montreal, QC, Canada

9 CKUT 90.3FM Radio McGill, Montreal, QC, Canada

10 Health Sciences Library, Memorial University, St John's, NL, Canada

11 Bruyere Research Institute, Ottawa, ON, Canada

12 Division of Population Health and Applied Health Sciences, Faculty of Medicine, Memorial University, St John's, NL, Canada

Corresponding Author:

Zack Marshall, MSW, PhD

Department of Community Health Sciences

Cumming School of Medicine

University of Calgary

3280 Hospital Drive NW

Calgary, AB, T2N 4Z6

Phone: 1 4032206940

Email: [email protected]

Background: Photographs from medical case reports published in academic journals have previously been found in online image search results. This means that patient photographs circulate beyond the original journal website and can be freely accessed online. While this raises ethical and legal concerns, no systematic study has documented how often this occurs.

Objective: The aim of this cross-sectional study was to provide systematic evidence that patient photographs from case reports published in medical journals appear in Google Images search results. Research questions included the following: (1) what percentage of patient medical photographs published in case reports were found in Google Images search results? (2) what was the relationship between open access publication status and image availability? and (3) did the odds of finding patient photographs on third-party websites differ between searches conducted in 2020 and 2022?

Methods: The main outcome measure assessed whether at least 1 photograph from each case report was found on Google Images when using a structured search. Secondary outcome variables included the image source and the availability of images on third-party websites over time. The characteristics of medical images were described using summary statistics. The association between the source of full-text availability and image availability on Google Images was tested using logistic regressions. Finally, we examined the trend of finding patient photographs using generalized estimating equations.

Results: From a random sample of 585 case reports indexed in PubMed, 186 contained patient photographs, for a total of 598 distinct images. For 142 (76.3%) out of 186 case reports, at least 1 photograph was found in Google Images search results. A total of 18.3% (110/598) of photographs included eye, face, or full body, including 10.9% (65/598) that could potentially identify the patient. The odds of finding an image from the case report online were higher if the full-text paper was available on ResearchGate (odds ratio [OR] 9.16, 95% CI 2.71-31.02), PubMed Central (OR 7.90, 95% CI 2.33-26.77), or Google Scholar (OR 6.07, 95% CI 2.77-13.29) than if the full-text was available solely through an open access journal (OR 5.33, 95% CI 2.31-12.28). However, all factors contributed to an increased risk of locating patient images online. Compared with the search in 2020, patient photographs were less likely to be found on third-party websites based on the 2022 search results (OR 0.61, 95% Cl 0.43-0.87).

Conclusions: A high proportion of medical photographs from case reports was found on Google Images, raising ethical concerns with policy and practice implications. Journal publishers and corporations such as Google are best positioned to develop an effective remedy. Until then, it is crucial that patients are adequately informed about the potential risks and benefits of providing consent for clinicians to publish their images in medical journals.

Introduction

Case reports are an important tool for medical, scientific, and educational purposes [ 1 ]. Written by practicing clinicians, peer-reviewed case reports provide relevant and timely medical information that contributes to evidence-based practice [ 1 , 2 ]. A large number of case reports are published each year; for example, 74,270 case reports were published in 2022 and indexed in PubMed.

Case reports often include images, including patient photographs [ 3 , 4 ]. Guidelines related to the publication of medical photographs in case reports often refer to overarching statements such as the Declaration of Helsinki, or slightly more specific policies such as the guidelines outlined by the Committee on Publication Ethics (COPE), or the Case Report (CARE) guidelines for case reports [ 5 - 7 ]. The Declaration of Helsinki states that research participants must be fully informed of any potential risks and benefits associated with the relevant study [ 8 ]. COPE guidelines provide clear recommendations for publishers, editors, and various research institutes on the topic of publication ethics [ 9 ]. Meanwhile, CARE guidelines are specific to case reports and seek to promote and improve their transparency, accuracy, and usefulness [ 10 ]. The CARE guidelines include a checklist with items such as deidentified patient information, informed consent, and patient perspective on the treatment they received [ 10 ]. While multiple guidelines exist, adherence is not mandatory; 1 study found that out of 50 journals, 76% did not adhere to any guidelines for publication of personal information [ 11 ]. Another study investigating CARE guideline adherence in 36 Indian medical journals found that only a third exhibited average adherence and that overall there was poor reporting of subject-informed consent [ 7 ].

With the growth of online publishing and advancements in technology, case reports from academic journals are widely available as web-based publications, and their reach has expanded to a larger audience [ 4 ]. While increased access to medical case reports may be beneficial, photographs from case reports published in academic journals are now also available in online image search results such as Google Images [ 3 , 4 ]. In such cases, patient photographs circulate beyond the original journal website and can be accessed by anyone using the internet. This raises ethical and legal concerns regarding patients’ informed consent and privacy of health information.

In the original study on this topic, drawing on a sample of case reports with patients who are transgender published between 2008 and 2015, at least 1 patient photograph was available on Google Images for 37% of the medical case reports in the sample [ 3 ]. Curious about whether the results would be the same for a random sample of medical case reports published more recently, the aim of this cross-sectional study was to provide systematic evidence that patient photographs from case reports published in medical journals appear in Google Images search results. Research questions for this study were (1) what percentage of patient medical photographs published in case reports are found in Google Images search results? (2) what is the relationship between open access publication status and image availability? and (3) do the odds of finding patient photographs on third-party websites differ between searches conducted in 2020 and 2022?

Study Design

The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) cross-sectional checklist was used when writing up results [ 12 ] (see Multimedia Appendix 1 ).

Ethical Considerations

Research ethics approval was not required because the data were collected from case reports published in medical journals.

Data Source and Study Population

PubMed includes a diverse range of medical journals and is “the most widely used database with biomedicine-related article abstracts” with over 36 million entries [ 13 ]. The efficient identification of a random sample was facilitated by the ways medical case reports are identified within PubMed. A structured search of PubMed was conducted to identify all indexed medical case reports published within a 1-year period between July 1, 2017, and June 30, 2018 (Search: “2017/07/01” [Date—Publication]: “2018/06/30” (Date—Publication) Filters: Case Reports). The search produced 23,589 results (the search was conducted on August 15, 2018).

Sample Size

To determine sample size, a pilot study was conducted to inform an estimate of effect size and power. All medical case reports indexed in PubMed for the month of February 2018 were identified. This search produced 955 references. Full-text PDFs were retrieved for each reference and the documents were visually checked to see whether each case study included photographic images of patients. Of the 955 case reports published in English in February 2018 and indexed in PubMed, 370 (38.7%) included patient photographs. Based on the original study, it was anticipated that approximately 37% of the case reports with photographs would include at least 1 image found online. Using a 95% Cl and a 4% margin of error, a sample size of 585 was required.

Data Collection and Measures

To identify the random sample for this study, the list of 23,589 case report references was exported from PubMed to Microsoft Excel (Microsoft Corp). A random number generator was used to assign a number to each of the references, and then the list of references was rank-ordered from the smallest to the largest random number. The first 585 references were selected in order, imported into EPPI-Reviewer (EPPI Centre) [ 14 ], and then full-text papers were uploaded for each reference ( Figure 1 ).

For the 585 references, the full text of each case report was examined to determine whether the publication included clinical photographs of patients or not. The photographs from each publication were consecutively numbered on a hard copy, and then the information was entered into a Microsoft Excel spreadsheet, with a unique number for each case report and photograph. A total of 186 case reports included patient photographs, with a total of 598 patient photographs in the sample.

Two categories of data were collected—data at the case report level and data at the image level. At the image level, details were documented related to the specific part of the patient’s body that was photographed (eg, eye, face, or torso); the timing of the photograph (eg, pre- or posttreatment or during surgery); the gender and age of the patient as described in the body of the case report; whether the photograph was in color or not; and whether the authors had attempted to anonymize the photograph using image blurring or bars covering parts of the image. For each case report, 1 member of the team entered data about the images into the Excel spreadsheet. All data were then independently verified by a second team member.

At the case report level, data collection included author information, year of publication, open access status, and availability on Google Scholar, ResearchGate, and PubMed Central. To document the open access format for each of the case reports, 1 member of the team searched for each paper in the open database Unpaywall. The open access status of case reports is classified using colors [ 15 ]. The color classifications are (1) gold—published in an open access journal that is indexed by the Directory of Open Access Journals; (2) green—toll-access on the publisher page, but there is a free copy in an open access repository; (3) hybrid—free under an open license in a toll-access journal; (4) bronze—free to read on the publisher page, but without a clearly identifiable license; and (5) closed—all other papers, including those shared only on academic social networks or Sci-Hub. For the purposes of this analysis, open access included papers categorized as gold, green, hybrid, and bronze.

Google Images Search

To determine whether it was possible to find photographs from the case reports on Google Images, searches were carried out for each of the 186 case reports that included patient photographs. Searches were conducted on a yearly basis from 2019 to 2022, using an approach referred to as algorithmic probing [ 16 ]. This analysis focuses on the results of the most recent searches conducted in 2022.

Three members of the research team (AC, HJ, and ZM) conducted manual searches on Google Images for each paper in the study sample using the same strategy first developed by Marshall et al [ 3 ]. For each reference, the researcher used the title of the case report in quotation marks as the text key. These searches were conducted using a Tor browser, “a proxy that masks the location information and browsing history of the user, allowing for anonymous use of the Internet” [ 17 ]. This browser was used to minimize the influence of Google’s personalization strategies to help prevent results from being skewed by historical searches conducted by team members [ 18 ]. Images of the search result pages were saved in PDF by date. One member of the research team then manually compared the search results in the PDF to the photographs in the published medical case report, circling the matching image using PDF editing software. Google Images search results also include a link directly under the image to the original source of the photograph. In Figure 2 , for example, the first 3 images are from a case report [ 19 ] and include links to BMJ Case Reports, and Europe PMC. The link was extracted for each image and then each source was coded as a journal website, publisher website, research database (eg, Semantic Scholar), research repository (eg, ResearchGate), social media, professional association, or other. A second member of the team verified the results.

Data Management

Data were entered into Microsoft Excel and screened for misentries (eg, spelling errors, empty cells, or shifted cells). The primary outcome variable was the availability of medical photographs on Google Images and was coded as “0” not found and “1” found. Secondary outcome variables included the image source and the availability of images on third-party websites over time. Missing data analyses were performed to screen the data for entry errors.

Statistical Analysis

Sample characteristics were described using means, SDs, quantiles, and frequency distributions. The level of analysis is individual case reports rather than individual photographs. This is necessary for 2 reasons. First, some published figures contain more than 1 patient photograph. For example, a figure may include 4 images of a patient taken from different perspectives. Second, case reports included a range of 1 to 33 patient photographs. The relationship between multiple images found in 1 case report is different from multiple images found in separate case reports, and as a result, each photograph cannot be treated independently.

To better understand whether the characteristics of case reports (such as full-text availability on ResearchGate, PubMed Central, or Google Scholar, and open access status) were related to the availability of medical images on Google Images, chi-square tests and simple logistic regressions were conducted. To test if there is any trend for finding images on third-party websites over different searches over time, generalized estimating equations with a logit link and robust sandwich estimators were used. Odds ratios (OR) with 95% Cl were reported. P ≤.05 was considered significant. Analyses were conducted using SAS (version 9.4; SAS Institute).

Sample Demographics

From the sample of 585 case reports, 186 (31.7%) case reports had at least 1 patient clinical photograph. A total of 598 images were identified in these 186 medical case reports. Individual photographs were coded into five broad categories (1) the specific body part that was photographed; (2) patient sex as identified in the case report; (3) patient age (adult vs child); (4) the timing of the photograph (pretreatment, during surgery, autopsy, etc); and (5) whether the photograph was anonymized or not.

From the 186 case reports with 598 photographs, 309 (51.7%) were photographs of women, 278 (46.2%) were photographs of men, and 3 (0.5%) were photographs of trans women. Information about patient sex or gender was not provided for 8 (1.3%) of the photographs. Patients who were photographed ranged in age from 2 days to 93 years. A total of 412 (68.9%) photographs were taken of adult patients (older than 18 years), and 176 (29.4%) were photographs of infants, children, or teenagers younger than 18 years of age. Information about age was not provided for patients in 10 (1.7%) photographs.

Patient photographs most often included internal organs (eg, endoscopy, laparoscopy, or bronchoscopy; n=151 images, 25.3%). Other common types of photographs included limbs such as legs, arms, hands, or feet (n=109 images, 18.3%), or images of the abdomen or torso (n=53 images, 8.9%). A total of 110 (18.3%) out of 598 photographs included eye, face, and full-body photographs, including 65 (10.9%) that could potentially identify the patient. In terms of the context of when the photograph was taken, 403 (67.4%) were photographs of the patient’s condition pre- or posttreatment whereas 144 (24%) were photographs taken during surgery ( Table 1 ).

Open Access Status of Case Reports With Medical Images

Of the 186 case reports, 102 (54.8%) were closed access; among the closed-access reports, 66 (65%) case reports had at least 1 image found on Google Images. Of the 83 case reports that were open access, 76 (92%) had at least 1 image found on Google Images. From crude comparisons ( P <.001), it appears that case reports with open access were more likely to have medical images visible as Google Images.

Image Availability

For 76.3% (142/186) of the case reports, at least 1 image was found on Google Images. The odds were higher of finding an image from the case report online if the full-text paper was available on ResearchGate (OR 9.16, 95% Cl 2.71-31.02), PubMed Central (OR 7.90, 95% Cl 2.33-26.77), or Google Scholar (OR 6.07, 95% Cl 2.77-13.29) than if full-text was available solely through an open access journal (OR 5.33, 95% Cl 2.31-12.28), but all factors contribute to increased odds of locating patient images online ( Figure 3 ).

Image Source

To better understand where Google Images is obtaining patient photographs, information about data sources was extracted from the hyperlink under each of the images that were found online. Raw image sources included the journal website, publisher website, research database (eg, Semantic Scholar), research repository (eg, ResearchGate), social media, and professional associations. These were grouped into 2 main categories—journal websites or other websites (any third-party sources). A total of 51.0% of photographs came from the journal website, and 49.0% were from a third-party site. In 2021, 51.1% were from journal websites, and 48.9% from third-party sites. In 2022, the number of images from journal websites increased to 63.4%, while the number from third-party sites was 36.6%.

Trend Over Time

Based on generalized estimating equations, after adjusting for individual study differences, compared with the search in 2020, patient photographs were less likely to be found on third-party websites based on the 2022 search results. Specifically, the odds of finding a patient photograph on a third-party site in 2022 were about 40% less likely, compared with the search done in 2020. This finding was statistically significant with OR 0.61, 95% Cl 0.43-0.87. The likelihood of finding a patient photograph on a third-party website was not significantly different between the search in 2021 and the search in 2020 ( Table 2 ).

Principal Results

The aims of this study were to identify what percentage of patient photographs published in medical case reports were found in Google Images search results, to better understand the relationship between open access publication status and image availability, and to verify whether there is a trend over time for finding patient photographs on third-party websites. Out of the 186 case reports that included clinical photographs, at least 1 photograph from the case report was available on Google Images for 142 (76.3%) references. The odds of finding an image from the case report online were higher if the full-text paper was available on ResearchGate (OR 9.16, 95% CI 2.71-31.02), PubMed Central (OR 7.90, 95% CI 2.33-26.77), or Google Scholar (OR 6.07, 95% CI 2.77-13.29) than if full-text was available solely through an open access journal (OR 5.33, 95% CI 2.31-12.28), but all factors contributed to an increased risk of locating patient images online. This study is the first of its kind to search Google Images for medical photographs from a random sample of case reports; as such there are no studies with which to compare results.

Findings from this study are notably higher than the results from earlier research, where 34 (37%) out of 94 case reports had at least 1 photograph accessible on Google Images [ 3 ]. While the difference in sample population may partially account for the disparity in outcomes, this study identified several additional variables that influenced the availability or unavailability of patient photographs on Google Images. For instance, finding images from the case reports online was more likely if the full-text paper was also available on ResearchGate, PubMed Central, or Google Scholar, compared to case reports solely accessible through open access publications.

To better understand how Google retrieves the images, the image source was recorded for all photographs found on Google Images and these results were compared over a 3-year time period. From 2020 to 2022, there was a notable change in where images were sourced, with a significant decrease in photographs housed on third-party websites such as ResearchGate and Semantic Scholar. This change may be linked to a recent legal judgment where Google was held liable for copyright infringement for displaying content with links to a third-party infringer’s website which was not the original publisher and owner of the copyrighted content [ 20 ].

Limitations

The systematic, documented approach to searching for patient medical photographs on Google Images is a strength of this study. The primary challenge is that Google Images search results are not stable. Although the team attempted to manage as many factors as possible, including using the Tor browser to control for the influence of team member search histories, search results changed. Investigating the same data set yearly for over 3 years, sometimes the photographs were never found, while others were consistently located. The primary findings in this paper are based on the most recent searches in 2022, as the purpose of this study was not to demonstrate the ways search results change over time, but whether the images were found or not. Search results from 2020, 2021, and 2022 are available on request.

A further limitation is that the team did not investigate other image search engines or social media platforms where patient photographs might also appear. While the team was able to provide clear evidence using Google Images it would be an interesting avenue for future research to explore some alternate image search engines and platforms. In addition, the use of the Tor browser to minimize personalization in search results may not completely replicate the typical user experience and may have introduced a form of selection bias.

Conclusions

From a clinical standpoint, the availability of patient photographs on Google Images presents both advantages and risks. Results demonstrated a high proportion of medical photographs from case reports on Google Images. While this concentration allows for wider accessibility and educational benefits, the public availability of these sensitive images online also raises ethical concerns with respect to the privacy of personal health information. Patients should be adequately informed about the possible impacts of providing consent for clinicians to publish their images in medical journals. Even if clinicians seek consent for their publication in case reports, it is not clear whether patients are informed about the possibility of photographs becoming available on Google Images and reaching unintended audiences, including the media and the general public. Similarly, it is not known whether clinicians themselves are aware of these risks. As such, they may not be in a position to ensure informed consent from their patients regarding the potential availability of their clinical images online. A recent content analysis of journal consent forms for the publication of patient photographs found that 55.5% (10/18) of consent forms related to 132 journals mentioned photographs being available to an audience outside of the journal website, but only 16.7% (3/18) addressed the possibility of the patient’s images being linked to journal or publisher social media platforms [ 21 ].

A lack of standardized guidelines poses a challenge to obtaining patient consent for publishing case reports with photographs. In addition to the policy and practice recommendations highlighted in earlier research, current findings underline the need for increased dialogue among academics, patients, governments, and industry. Discussions should focus on improving the consent process and establishing consistent practices and policies for publishing case reports with patient photographs. Study findings indicate that patient photographs are accessible on Google Images, even when published in closed-access case reports. Engagement with Google and other major online image repositories is critical to raise awareness of this issue and to seek input regarding the underlying causes and potential solutions. New policies should be implemented to ensure that patients are protected and that all stakeholders are aware of the risks involved in submitting clinical photographs to online medical journals. Accordingly, the next phase of this study focuses on qualitative interviews with case report authors, journal editors, publishers, and patients. The goal is to identify potential solutions to this complex ethical challenge, including responsive policies that will influence practices across academic publishing to maintain patient privacy.

Acknowledgments

The Natural Sciences and Engineering Research Council of Canada (554764-2021) provided student scholarship funding. The funders had no role in study design, in collection or interpretation of data, in writing the report, or in the decision to submit the paper for publication.

Data Availability

The data sets generated and analyzed during this study are available from the corresponding author on reasonable request.

Authors' Contributions

ZM was responsible for conceptualization (lead), investigation (lead), methodology (equal), supervision (lead), writing—original draft preparation (lead), and writing—review and editing (lead). MB carried out the investigation (equal), project administration (equal), writing—original draft preparation (equal), and writing—review and editing (equal). MW contributed to the formal analysis (lead), methodology (equal), visualization (lead), writing—original draft preparation (equal), and writing—review and editing (supporting). AC did the investigation (equal), writing—original draft preparation (equal), and writing—review and editing (supporting). HJ did the investigation and writing—review and editing (supporting). SA aided in conceptualization (supporting), methodology (equal), writing—original draft preparation (equal), and writing—review and editing (supporting). RP contributed to the investigation (equal), project administration (equal), and writing—review and editing (supporting). VB performed the investigation (equal), project administration (equal), writing—original draft preparation (equal), and writing—review and editing (supporting). VFR did the investigation (equal), project administration (equal), and writing—review and editing (supporting). BC performed the investigation (equal) and writing—review and editing (supporting). LA performed the investigation (equal) and writing—review and editing (supporting). MS contributed to the methodology (equal) and writing—review and editing (supporting). VW aided in conceptualization (supporting), methodology (equal), and writing—review and editing (supporting). FB was involved in conceptualization (supporting) and writing—review and editing (supporting). CK contributed to the conceptualization (supporting) and writing—review and editing (supporting).

Conflicts of Interest

None declared.

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) cross-sectional checklist.

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Abbreviations

Edited by T de Azevedo Cardoso; submitted 13.12.23; peer-reviewed by M Roguljić, D Singh; comments to author 08.03.24; revised version received 08.04.24; accepted 24.04.24; published 24.06.24.

©Zack Marshall, Maushumi Bhattacharjee, Meng Wang, Abdul Cadri, Hannah James, Shabnam Asghari, Rene Peltekian, Veronica Benz, Vanessa Finley-Roy, Brynna Childs, Lauren Asaad, Michelle Swab, Vivian Welch, Fern Brunger, Chris Kaposy. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 24.06.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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Retrospective analysis of glacial lake outburst flood (glof) using ai earth insar and optical images: a case study of south lhonak lake, sikkim.

1. Introduction

2. study setting, 3. data and method, 3.1.1. sar images, 3.1.2. optical images, 3.2. insar calculation in cloud platform, 3.2.1. gpu-assisted insar processing module, 3.2.2. automated full-resolution fast insar time-series analysis method.

• Employ the small baseline principle to select interferometric pairs and generate the optimal interferometry network [ 40 ].
• Calculate burst offsets between each image and the reference image, generating a burst offset file and determining the burst offsets of each slave image based on the AOI of the reference image.
• Automatically download the corresponding orbit auxiliary files and external DEM files. SRTM DEM with a resolution of 30 m was utilized to subsequently mitigate terrain phase effects.
• Utilize GPU to accelerate the generation of differential interferograms; details of GPU-accelerated InSAR processing are available in Section 3.2.1 . Subsequently, all generated differential interferograms are resampled based on the registration parameters to ensure consistency with the SAR coordinate system of the reference image.
• Image cutting. Interferograms are cropped according to the specified range of the AOI.
• SHPS phase filtering and phase unwrapping. Utilize the SHPS algorithm to reduce noise in the interferograms while preserving the spatial resolution of SAR images. Coherent points surrounding each reference pixel are selected, aiming to retain interferogram details while eliminating phase noise from incoherent and low-coherence areas. Then, phase unwrapping of interferograms was achieved using minimum cost flow (MCF) networks [ 41 ].
• Corrections for orbital error and terrain-related atmospheric delay errors.
• Time-series analysis in SAR coordinate system. With high-pass and low-pass filters, the average deformation rate is calculated using the linear least squares (LS) method. Subsequently, a time-series analysis is performed. The InSAR time-series analysis module follows the traditional method, employing the Small Baseline Subset method to derive deformation time series through the singular value decomposition (SVD) algorithm [ 6 ].

4. Results and Analysis

4.1. analysis of insar deformation results, 4.2. optical image analysis, 5. discussion, 5.1. correlation between insar deformation results and multiple factors, 5.1.1. rainfall factor, 5.1.2. lake area factor, 5.1.3. slope factor, 5.2. possible causes of landslide and glof, 5.3. secondary landslide risk, 6. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest.

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Yu, Y.; Li, B.; Li, Y.; Jiang, W. Retrospective Analysis of Glacial Lake Outburst Flood (GLOF) Using AI Earth InSAR and Optical Images: A Case Study of South Lhonak Lake, Sikkim. Remote Sens. 2024 , 16 , 2307. https://doi.org/10.3390/rs16132307

Yu Y, Li B, Li Y, Jiang W. Retrospective Analysis of Glacial Lake Outburst Flood (GLOF) Using AI Earth InSAR and Optical Images: A Case Study of South Lhonak Lake, Sikkim. Remote Sensing . 2024; 16(13):2307. https://doi.org/10.3390/rs16132307

Yu, Yang, Bingquan Li, Yongsheng Li, and Wenliang Jiang. 2024. "Retrospective Analysis of Glacial Lake Outburst Flood (GLOF) Using AI Earth InSAR and Optical Images: A Case Study of South Lhonak Lake, Sikkim" Remote Sensing 16, no. 13: 2307. https://doi.org/10.3390/rs16132307

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