CFA Institute

Validation of Risk Management Models for Financial Institutions: Theory and Practice. 2023. Edited by David Lynch, Iftekhar Hasan, and Akhtar Siddique. Cambridge University Press. Because of their high leverage, financial institutions need to maintain a strong focus on risk modeling, both for sound firm management and as a regulatory necessity. Modeling of current and potential risks is critical to well-grounded financial decision making. Getting risk measures wrong can have dire financial consequences. Validation of Risk Management Models for Financial Institutions, through a set of thoughtful articles, describes how effective structuring and testing of the modeling techniques used in risk management can support better financial decision making. The book does not address the question of why financial institutions may fail, which matters because financial failures and blowups continue to be accepted as part of doing business in the financial industry. This set of edited papers does, however, provide insights on how risk models are built, tested, validated, and used in a variety of financial activities. Get the models right, and a financial firm has a better chance of survival. David Lynch, Iftekhar Hasan, and Akhtar Siddique, the editors of this book, have collected 17 papers from leading experts on issues of model validation, which they define as “the set of processes and activities intended to verify that models are performing as expected, in line with their design objectives and business uses.” These papers encompass varying levels of complexity and depth concerning the validity of model assumptions and predictions. From methodological issues to cases on specific businesses, the contributors focus on in-sample training and out-of-sample tests as validation exercises. Successful validation requires substantial data and a formal way of concluding whether a model is within an error tolerance. For financial firms, the margin for error is small. Poor testing and validation may mean the difference between financial success and firm failure. In the first few chapters, the book centers on value at risk (VaR) modeling, the workhorse of risk models. Even with its well-known limitations and the dislike it has engendered among many traders, VaR models serve as a good foundation for risk assessments. There is no viable alternative to this backbone approach for financial institutions, but it requires extensive modeling and structural thinking to be effective. These core chapters extend modeling of the problem to the entire distribution of prices and not just a risk threshold, while also discussing the key issues of conditional backtesting and benchmarking for the ongoing monitoring of risks. Of course, one of the existential risks over the last decade has been the COVID-19 pandemic. Research points to the failure of VaR models to react quickly enough in the spring of 2020. There is reason to hope, however, that future outlier events can be addressed more effectively by including past data extremes in the analysis. Unfortunately, as clearly enunciated in this book, the fundamental stress-testing problem in regard to extreme events is that we simply do not have enough stress periods to train risk models properly. Several chapters, representing more than half the book, focus on credit risk modeling by discussing issues of counterparty risk, retail credit models, and wholesale banking of large loans. Here, there is a focus not just on market price dynamics but also on allowance for loss. Proper modeling of the probability of loss and loss given default is critical to measuring risks, especially given the currently high growth in private credit funds. While VaR modeling has dominated trading businesses, credit default modeling may be more critical for firm risk, given the increased difficulty of hedging these events. Again, with a limited number of recessions and unique credit events, the measurement and validation of loss assumptions are not easy issues to address. The goodness of fit for any model must be balanced against the adequacy of the sample data. Contributors to this volume present the problems associated with credit management both analytically and through a case study. Examining trading and lending business risk is critical, but there is also a need to roll risk up to the enterprise level, a key topic when thinking about firm risk. Models must also be balanced against operational risk and the demands of supervisory stress testing by regulators. All these issues are addressed in various chapters, but the common drawback of any edited book of research papers is present: The papers have varying quality and complexity, and the integration of topics does not always flow effectively for the reader who desires a sequentially organized review of the essential topics. Unfortunately, model construction and validation often do no more than fight the last battle on losses or address the desires of regulators. The process does not prepare institutions for black swans, tail events, or the consequences of making the wrong decisions. While not the focus of model validation, dealing with “unknown unknowns,” extreme scenarios, and unique risk events is fundamental to improved risk decision making. In a complex financial world, diversification and leverage are key components of risk management that influence the effectiveness of validation. Validating on the basis of past data is the best this book has to offer for building models, yet addressing uncertainty, ambiguity, and the complexity of markets is necessary for any useful risk discussion. With its focus on model validation, the book deals with a narrowly specialized topic. Nevertheless, any reader involved in investment management or financial institutions will find it useful for generating keener insights into building and interpreting risk models. Losses at money managers and hedge funds, like the faltering of financial institutions, are often associated with risk model failure in the form of giving incorrect or ambiguous answers or focusing on the wrong risks. Reading this book is not going to prevent bad decisions or constrain inappropriate risk taking, but it will improve model building, which is foundational for minimizing losses. Many potential readers of Validation of Risk Management Models for Financial Institutions may not be focused on managing financial risk, but gaining a deeper understanding of model validation

I interviewed 50 amazing people — 25 women and 25 men — from different professions and industries for my 14th annual research paper released on International Women’s Day, 8 March 2024. To celebrate the occasion, I wanted to share some examples of how women around the world are investing. Below are 10 responses to the question: What’s in your investment portfolio? While I was conducting my interviews, I realized that a prospective client’s existing investment portfolio is a potential diagnostic tool for investment advisers. We often look at their portfolio as something that needs to be “fixed,” but what’s in it may reveal useful information about what is important to the prospect and how they may have worked with their previous adviser. This strikes me as very similar to how medical clinicians use diagnostic tests to establish whether a patient has a particular condition.  When working on a prospect’s investment policy statement (IPS), we normally think about whether they want to exclude oil or tobacco stocks, but maybe they have other unique preferences that have led them to invest in a certain way. Using their existing portfolio to diagnose their investing habits and persona just might lead to a higher conversion rate. Valentina Díaz Estévez, Finance Professional, Dublin “I’ve lived in several different cities: Río Gallegos in the south of Argentina during my childhood, Paraná, Buenos Aires, and now Dublin. I love new experiences: Learning how to start again makes me a stronger person. I try to learn from every step in my life. Currently, I am in Ireland, where I have embarked on a master’s of science program in fintech at the National College of Ireland (NCI) in Dublin. I am honored to have received the Government of Ireland International Education Scholarship (GOI-IES) for the 2023 to 2024 academic year, a prestigious award granted to only 60 recipients out of over 5,000 applicants. “In terms of my investment portfolio, it is diversified with 70% in US dollars and 30% in Argentine pesos when I was living in my country. Half of my dollar holdings are invested in Latin American funds, while the other half is allocated to S&P exchange-traded funds (ETFs) and more conservative stocks, such as Proctor & Gamble, McDonald’s, Walmart, and Coca Cola. My pesos are invested in funds that are linked to inflation, and I keep about 10% liquid in money market funds to pay for my day-to-day expenses. Additionally, I always maintain a small allocation to gold as a hedge for quality during periods of volatility.” Umulinga Karangwa, CFA, Founder, Equity Investment Adviser, Africa Nziza Investment, Cape Town “I started my career as a tax advisor, but I found the hours to be grueling so decided to shift to finance. In the last 20 years, I’ve worked and lived in Belgium, the UK, and Africa. I now do business in both Cape Town, South Africa, and Mauritius, and for convenience, I own an apartment in each city. My firm Africa Nziza provides investment advisory services for institutional investors and investment appraisal services for private equity investors, and we conduct independent investment research on investment opportunities in the region. “My personal investment portfolio consists of 30% real estate and 70% equities and ETFs. Living in Africa, you have to buy real estate to hedge against inflation (currently 7%), and this issue is compounded by the depreciation of the currency. Mauritius and South Africa are not very investable stock markets. My pension fund is still housed in Europe, and it is invested mostly in ETFs. Otherwise, I’ve held onto the S&P 500 for 20 years now, and it has appreciated so much more than anything else. I didn’t mean to have so much of my money in the US market; it just happened. Ten years ago, I decided not to rebalance — why argue with success?” Sabrina Amélia de Lima, Portfolio Specialist, Itaú Unibanco, Belo Horizonte, Brazil “My investment portfolio is focused on global diversification. I believe this is the cornerstone of risk management, portfolio construction, and achieving long-term consistent stable returns. Here is the breakdown of my portfolio:  “20% in inflation-linked assets, such as national treasury bonds earning about IPCA [the official Brazilian inflation index] plus 6% in debentures of good companies  “20% in international ETFs, such as IVV, QQQ, and VNQ, and equities, including Coca-Cola, Meta, Alphabet, PayPal, and Ferguson PLC “5% in alternative assets, such as cryptocurrency funds via ETFs “5% in mature companies in the Brazilian stock market, such as Itaú, Vale, and Weg “50% in fixed-income funds and multimarket funds managed by Itaú Asset, Kinea, Kapitalo, Vinland, and others  “My profile is more aggressive in that I accept taking risk in order to seek greater returns. My main concerns are inflation protection and geographical diversification.” Sloane Ortel, Founder and Chief Investment Officer, Invest Vegan, Provo, UT  “I formed a long-term view of how I wanted to shape this industry, and I started Invest Vegan in 2021. “We currently have 19 holdings in the Invest Vegan portfolio including: “Farmer Mac: This mission-driven lender was chartered by Congress to create a secondary market for agricultural credit and reduce the cost of borrowing for American farmers; 99% of its business is recurring fees and net effective spread. “Welltower: a REIT that is one of the largest investors in senior assisted living. Staff turnover is destructive in that business, and I love that they are focused on meaningfully higher staff retention, which also drives meaningfully higher results. “Duolingo: an app that helps anyone learn languages, music, and math for free. These universal skills are among the most meaningful drivers of economic mobility and personal fulfilment for individuals. “To me, veganism is a coherent ethical system that focuses on avoiding harm to living things and seeks a regenerative relationship with the world. It’s not a diet. It’s 1,000 tiny steps that touch on everything from your toothpaste to choosing trains over planes. I named the firm Invest Vegan because, to me, that kind of holistic thinking

In the fast-paced world of investment management, where success is often quantified by returns and rankings, a fundamental shift in mindset can redefine your edge. This is the first in a four-part series on self-improvement that sets the stage for my participation in CFA Institute Live 2025, where I will contribute to a discussion on building trust and managing expectations. Research in sports psychology reveals that athletes who focus on self-improvement perform better than those who focus on outcomes. Ancient Stoic philosophers would agree. You can apply this principle to the practice of leading individuals, teams, and yourself. There are two ways people experience engagement: based on ego factors, such as how one ranks relative to peers, and mastery factors, such as personal improvement. It turns out that athletes perform better if they work toward self-improvement rather than focusing on the score and similar metrics. It’s the difference between a golfer whose goal is to impress others with a low handicap and another who aims to improve their swing — and derives personal satisfaction in doing so.  Both players want to improve.  Both players are highly motivated to win.  The difference is the why. Lee Crombleholme, a world-renowned pro golf coach, says: “It’s not how much you’re motivated. It’s the underlying reason for your motivation [that matters].” Crombleholme differentiates here between the ego and mastery mindsets. With the mastery mindset, we focus on what we can control, and our self-confidence improves, no matter the final score (the outcomes).  In the same vein, Mt. Everest expert Guy Cotter says climbers should make the journey, not the summit, the goal:  “It is as if people are interested only in the goal of having climbed Everest and not climbing Everest as a major achievement in their climbing career.” I must admit that I’m more in the ego mindset camp. Let’s be transparent: I care about what my colleagues think of me and how much money I make. I think almost everybody does. But I’m trying to redefine my “why” toward the mastery side. So, how can I become better at what I do for the sake of self-improvement? That’s something I can control more easily than the opinion of others. In my day job in money management, I stress about the performance numbers for our portfolios and the growth numbers for our business. There are good reasons why measurable goals are essential in the corporate world. We need to keep score, as far as I’m concerned.  But I also focus on what my team can control: our process. What makes us better investors? Should we change how we run meetings? Can we improve how we interpret financial and economic data? How do we maximize the impact of collaboration to enhance our investment decisions? The business world is obsessed with data and “key performance indicators.” Generally, that’s a good thing, but it ignores the importance of mindset in driving performance.  Traditional goals focus on outcomes, while mastery goals focus on process. Both are effective. It’s important to set goals for process improvements. Shift your focus from what you can’t control—outcomes, opinions, or rankings—to what you can: the process, the effort, and the mastery. Whether you’re leading a team or climbing your own Everest, focusing on the journey will get you further than obsessing over the destination. And your mindset will determine if the climb feels meaningful or empty. Sébastien Page, CFA, is the author of The Psychology of Leadership, forthcoming in April 2025. The book is available for pre-orders here: www.psychologyofleadership.net source

“We all know the importance of fundamentals and fundamental value,” Brian Singer, CFA, said at the Alpha Summit GLOBAL by CFA Institute this past May. “[But] what do we do in an environment where fundamentals begin to take a backseat to public policy? What do we do when the phrase ‘market prices’ becomes an oxymoron?” As moderator of the “Navigating Today’s Investment Conundrums” session, Singer, who is founder and co-CIO of ViviFi Ventures, explored these questions with panelists Jason Hsu, chair and CIO at Rayliant Global Advisors; Albert Trank, CFA, executive managing director and portfolio manager at PGIM Private Capital; and Anne Walsh, CFA, managing partner and CIO for fixed income at Guggenheim Investments. Their consensus: Unconventional monetary policy has exerted an “absolutely crazy” influence on markets, and to avoid being overwhelmed by this new reality or any subsequent structural shifts, investors should keep three key themes in mind. The Structural Shifts: “Absolutely Crazy” and “Unprecedented” Today’s ongoing market turmoil can be understood as a series of aftershocks that followed a major tectonic shift in monetary policy, according to the panelists. The US Federal Reserve’s balance sheet has gone from 5% to 30% of US GDP, Singer noted, while the Bank of Japan’s (BOJ’s) went from 20% to more than 130%. A central bank’s traditional role is to maintain stable currency values by controlling reserves. But the Fed’s reserve holdings as a percentage of its balance sheet went from a few percentage points to 40%. “That’s absolutely crazy to try to understand how that may influence markets,” Singer said. Just how profound have the Fed policy changes been? Walsh provided a chart showing the M2 money supply and M2 velocity from 1960 through early 2022. “Since the global financial crisis, the Fed has been on a mission, it seems, to be very much deeply involved in the markets,” she said. In the post-COVID-19 period alone, the M2 money supply increased 26%. “That is an unprecedented rate of money supply hitting into the system,” Walsh continued. “Now, [the Fed] had to have felt that there was going to be an impact. They had to have seen that. But apparently, it took them by surprise.” “Velocity of money,” or the rate of turnover in the supply, implies that pouring money into the system will create a stimulus effect: The more money in the system, the more it will move around. But since the mid-1990s, this dynamic hasn’t played out. “We are seeing a huge decline in money supply, and this liquidity is being pulled out of the system very rapidly,” Walsh said. “We’ve gone from the Fed buying $120 billion a month of financial instruments, debt instruments, to zero, and now they are going to allow the balance sheet to roll off by approximately $100 billion a month. That’s a $220-billion-a month swing. It will have an effect that combined with rates will definitely have a demand-destruction impact.” And that means that far from being on the sidelines of the financial markets, the Fed has a much more determinative influence. “To the point of manipulation, they are absolutely involved in our markets,” Walsh said. “With a balance sheet of nearly $9 trillion, they pretty much are the market.” So, why has the velocity of money continued to drag? Walsh believes it’s because the liquidity injected into the system has not been put to economically productive use. Instead, it went into investments and inflated asset prices across the board. “While the Fed was trying to have an impact on the economy, what they really did was have an impact on markets,” she said. “So, this demand for money was not driven by traditional or historical business demand but was in fact driven by investor demand.” Of course, just because the Fed has its foot on the accelerator doesn’t mean it’s steering the car. “It’s a huge, huge influence that exists across markets, but policy is not necessarily in control,” Singer said. And that has affected investment behavior. “There’s been a tremendous incentive to take risk and buy assets and invest, and we certainly see that in terms of asset valuations,” Trank said. “The very low interest rate environment has clearly had an impact on institutional investors like insurance companies and pension funds that have many old liabilities at fixed costs.” But the reaction to all this unorthodox monetary policy has not been uniform for all markets. “Japan has printed even more money, but it hasn’t created the same kind of outcome that we’ve seen in the US,” Hsu said. “So, there’s something that’s quite culturally different in the US that if you get the zero rate, you got easy money, people will go and do something with it. . . . In Asia, whenever they print money, all you ever see is bank deposits increase and you see real estate prices increase.” So, what happens when a decade and a half of monetary stimulus finally starts to wind down? Walsh expects complications. Historically, the Fed begins its tightening cycle when the economic outlook is more bullish than it is today. “That the Fed is moving so rapidly to pull liquidity out, however, is likely to portend a policy mistake,” she said. “As long as the economy continues to slow or they see headline inflation drop, they’re going to continue on this trajectory of quantitative tightening, but they are going to be informed by market behavior.” And despite sharply declining asset prices, the markets have held up pretty well. The retreat has been an orderly one so far, so the Fed hasn’t had to adjust its tightening policy. But that could change. “Eventually, there is likely to be a market event which the Fed will perceive to be systemic in its risk,” Walsh said. “They may be forced to pivot sooner rather than later because they are moving so rapidly in this tightening direction.” And that makes a focus on fundamental value, among other insights, all the more important for investors today. 1. A

In today’s investment environment, access isn’t the differentiator — clarity is. From AI-generated research to nonstop market commentary, information overload has become a feature, not a bug. The real competitive edge for investment professionals lies not in absorbing more but in filtering better. Geopolitical instability, AI disruption, and climate uncertainty are amplifying risk and eroding trust. But the most resilient firms aren’t chasing every data point — they’re building clarity into their decision-making. That means treating clarity not as an accidental outcome, but as a structured discipline: one built on judgment, signal triage, and cognitive risk management. This post calls on investment professionals to operationalize clarity — to make it a cultural norm, a leadership priority, and a daily practice. In the noise-heavy markets of 2025, clarity isn’t just a mindset. It’s infrastructure. The Global Risk Backdrop The World Economic Forum’s 2024 Global Risks Report identifies misinformation and disinformation as the top global risks through 2027, fueled by AI-generated content from both state and non-state actors. Meanwhile, geopolitical tensions remain high: Russia’s war in Ukraine, conflicts in the Middle East, potential confrontations over Taiwan, and rising polarization across regions are contributing to a fractured global order. Technological acceleration adds new layers of volatility. AI and biotech, while powerful, introduce risks such as bias from skewed training data and opaque algorithmic decisions. These factors don’t just create risk; they undermine institutional trust and damage global cooperation. Decision Fatigue: The Quiet Risk Today’s investment professionals face more than just information overload; they face strategic disorientation. AI adoption, shifting rate regimes, political fragmentation, and demographic divergence create scenario complexity that blurs outcomes and stresses decision frameworks. Decision fatigue is not just mental strain; it’s an operational liability. When complexity overwhelms capacity, professionals revert to heuristics and mental shortcuts. Sometimes these restore clarity; often they introduce bias. Common Cognitive Traps: Anchoring: Relying too heavily on the first piece of information received. Status quo bias: Preferring current conditions and resisting change. Sunk-cost fallacy: Continuing an endeavor because of previously invested resources. Confirmation bias: Seeking information that confirms preexisting beliefs. Framing effects: Reacting differently depending on how information is presented. Faulty forecasting: Overestimating one’s ability to predict future events. Overconfidence: Placing too much faith in one’s judgment or models. Undue prudence: Avoiding risk to the point of missing opportunity. Recallability: Overweighing recent or emotionally charged events. For example, a portfolio manager might be overconfident in their model while subconsciously avoiding bold decisions (prudence trap), or they might misinterpret recent volatility as indicative of future risk (recallability trap). These cognitive distortions often compound in high-noise environments. Clarity as Infrastructure Clarity must become part of the investment infrastructure. The best-performing firms in 2024 and 2025 aren’t chasing every signal. They’re filtering decisively, asking sharper questions, and building workflows that embed judgment and structure. According to McKinsey, the biggest EBIT gains from GenAI don’t come from speed or volume, but from redesigned workflows, CEO-level governance, and embedded human judgment. Clarity is a system, not a sprint. A Practical Clarity Toolkit for Investment Firms Codify Your Investment Philosophy: Write it down. Revisit quarterly. Bridgewater Associates’ commitment to radical transparency ensures decisions are rooted in a clear and shared framework. Install a Signal-Gatekeeping Layer: Assign a triage team to filter incoming research, AI outputs, and news. Only 27% of firms vet AI-generated material before it reaches decision-makers — a missed opportunity to reduce noise. Upgrade Communication Protocols: Replace raw dashboards with contextual briefings that explain why information matters now. Prioritize comprehension over data dumps. Train for Cognitive Risk: Teach teams to spot and neutralize mental traps. Frame this not as psychology but as risk management: biases are measurable and recurring threats to clarity. Elevate Human Judgment: Make leadership judgment a designed input, not an emergency override. Firms that integrate CEO-led oversight and AI governance outperform their peers. Clarity Is a Choice Investment professionals can’t opt out of complexity, but they can opt into clarity. Clarity is built through habits, frameworks, and firm-wide commitment. It doesn’t come from faster feeds or better dashboards. It comes from the strength to ignore the irrelevant, question the conventional, and act with conviction. In an age of information abundance, clarity is the rarest asset. Choose it deliberately. source

What’s the smartest thing you ever did, and how did it impact your financial future? For International Women’s Day 2025, I interviewed 27 women and 27 men from diverse backgrounds to uncover the pivotal choices that shaped their careers, finances, and personal growth. Whether it was leaving a corporate job, making a bold investment, or moving to a new country, one theme emerged: big changes often lead to big rewards. This post highlights inspiring stories from women who took calculated risks, reshaped their lives, and redefined success on their own terms. Olga Blasco, M&A Principal Partner, Growth and Exit Strategy Solutions, Lion People Global, Dublin: Blasco spent 20 years working in the corporate world and toward the end, she didn’t like the way things were going. “I was an SVP for a large American organization, and I had no time to do the other things that I loved to do. The smartest thing I ever did is leave the big corporate world and take time to think about how I could transform my life and find my ikigai. The word Ikigai means using my skills to support things that I’m passionate about, that the world needs, and that can sustain my livelihood.” Ten years ago, Blasco started a consultancy business and moved to Turkey to dedicate part of her life to non-profit work. Today, she pivots between Dublin, Istanbul, and Barcelona. She balances her role as M&A principal partner at Lion People Global (Dublin) with personal pursuits such as supporting women entrepreneurship as co-founder of JANA (Istanbul). She is a Board member of Clear Tech (Ireland), and Women in Localization (United States), as well as author of the book, The Journey of EKİP: a recipe for long-lasting impact. Jette Bilberg Lauritsen, Executive Secretary, Bygningsstyrelsen, Copenhagen: “I had an older cousin I thought was super exciting. She was into astrology, reflexology, and Buddhist teachings. In 1988, I went with her to a Buddhist lecture. This was a huge experience and turning point for me. I thought, ‘I don’t know what I’m going to do with the rest of my life, but this is definitely going to be a part of it.’” Bilberg says the smartest thing she’s ever done was to start working with her mind using the tools of ancient Buddhist methods. “This led me to doing volunteer work in the Buddhist Community in Copenhagen, which gave me deep satisfaction. I then decided I wanted to work full-time at my volunteer work for a while. To live this dream, I had to fix my financial situation and I needed to be debt free.” No more taxis for Bilberg. “I always rode my bicycle. I ordered far less take away food, cooked for myself, and I didn’t buy clothes for a long time. I paid off my mortgage for my apartment and started to save so that I would have funds to live on while pursuing my dream and working full-time as a volunteer. I am so happy that I eventually made that dream happen.” Barbara Ortiz, Electronics Engineer, MSA Safety Incorporated, Galway: In 2018, Ortiz left South America for the first time alone to work as the head of a multidisciplinary research lab in the United States. “For about 12 months, I lived in an extreme and isolated environment where less than 10% of the staff were women.” She worked on a wide variety of scientific projects related to the study of the ozone layer, solar panels, UV radiation, geodesy, glaciology, seismology, and cosmic rays. There were no negative financial implications associated with another smart move Ortiz made to Antarctica. “Besides paying me, they covered the cost of my clothes, food, and accommodation. That experience was so great that I now want to funnel my financial resources in the direction of seeing all the continents. I have lived and worked in Ireland and the French Alps. The next thing I would do is work as engineer in the Arctic.” Katia Moskvitch, Head of Communications, IBM Research Europe, and author of Neutron Stars: The Quest to Understand the Zombies of the Cosmos, Zürich: “The smartest thing I ever did was to write my book in the way I wanted to write it. This was very smart from both a career development perspective as well as in terms of personal satisfaction,” Moskvitch says. After earning her master’s degree in Journalism (University of Western Ontario), and MPhil in Theoretical Physics (King’s College London), she worked as a journalist in physics and astronomy. She was contacted by an editor at Harvard University Press on LinkedIn suggesting that she write a book. “I wanted to fully live the experience. I spent a year travelling the world and I frequently had the opportunity to have my travel and accommodation covered since I was also working at WIRED UK, a science, tech, and business magazine published by Condé Nast. I always tried to combine opportunities to visit places where I could interview scientists. Some people plan their work and travel destinations to align with beaches or Michelin-starred restaurants. I must be one of the few to make it all about radio observatories.” Sarah Hempel, Head of Sustainability, Axcel, Copenhagen: “When I was in high school my Danish cousin came to stay with us, and I thought she was quite cool. I wanted to be like her,” Hempel says. Her father’s side of the family is Danish, and she had a Danish passport. “The smartest thing I ever did was decide to move to Denmark on my own at age 19 for my bachelor’s degree. Students from the EU/EEA and permanent residents can study at a university in Denmark tuition-free: I was able to complete my entire university degree without any debt.” Hempel has no regrets. “High income earners pay about 56% in tax plus there are capital gains taxes. However, look at what you get. We have free education, free healthcare, low crime rates, and a great public transportation system. For 20 years I just rode my bike everywhere. I

“A forecast is a prediction; we’re saying what we think will happen. A scenario is different . . . it generally looks much further out and is trying to build a picture of the future in extreme uncertainty.” — Seb Henbest It is impossible to predict the future without some level of uncertainty. When we make investment decisions about assets with multi-decade horizons, our forecasts will ultimately break down. But while we do not know what the 2050s will bring, we can envision pathways that provide reasonable variations of what that future may look like. For investment managers, prioritizing one scenario over all others can have far-reaching consequences. This is especially true when it comes to the net-zero energy transition. There are multiple, equally valid pathways through the transition, all with different technology mixes and varied time horizons. Hence, a simple discounting of cash flows in a somewhat predictable “economic” scenario — with rational actors reacting to techno-economic considerations and the policies that are likely to be enacted — is not necessarily viable. Energy investors must consider various outcomes since the outcomes are, well, so various. Research providers, think tanks, sell-side analysts, and industry groups all compete for investors’ attention. Their goal is to either win our business or influence our decision making. Their base case often depends on their background. Those with histories in oil price assessment or renewable energy modeling could be prone to availability or anchoring bias. Many big energy players with high exposure to an abrupt net-zero transition construct their own scenarios, often guided by their own agendas. Gas transmission system operators (TSOs) and their industry groups envision a bright future for their stakeholders, whether through extended use of natural gas or rapid shifts to hydrogen. For example, Shell’s “Energy Transformation Scenarios” — Sky 1.5, Waves and Islands — attracted a lot of attention: Its Sky 1.5 pathway assumes a larger role for oil and gas than forecasts issued by the Intergovernmental Panel on Climate Change (IPCC) and other such bodies. How hydrogen will fit into the energy mix of a climate-neutral Germany is also much discussed, but there is no consensus on how large a role it will play or from where it will be sourced. Given the abundance of organizations promoting their own scenarios, investors need to approach them cautiously. We recommend a three-step assessment process: Apply some filters and screen out obviously conflicted forecasters. Review the target forecasters’ scenarios and decide which are most applicable to your investment philosophies. Consider the investment target’s performance and how plausible pathways could diverge from their presumed base case, which is often the “economic” scenario. This is where careful evaluation of environmental, social, and governance (ESG) factors and the resulting risks can help assess how the future may stray from the anticipated path. There are other things to keep in mind. Social factors may drive higher emissions scenarios. Rising energy costs could impact spending on heating, transport, and food. By increasing the cost burden on the low- to middle-income population, such “greenflation” could lead to widespread political and social unrest. Policymakers might be pressured to subsidize fossil fuel consumption. This has already occurred in Latin America, Africa, and Southeast Asia and constitutes a potential headwind that could delay our eventual exit from fossil fuels. Of course, the tailwinds driving us away from traditional fuel sources may be even more powerful. Shock events have strained supply chains, and volatile fuel prices encourage calls for a renewable path to energy independence. Climate change–related risks are top of mind for much of the population, and as climate-related crises grow ever more severe, popular support for sustainability should translate into public policies that help propel the world towards a 2050 net-zero scenario. In addition to policy developments, transformative technological innovations are also possible. Indeed, small modular nuclear reactors may deploy faster than expected or the costs of hydrogen from electrolysis could fall below $2 per kilogram earlier than anticipated. Choosing Our Path Some investors might be tempted to allocate based on their economic case and assume no significant technological or policy shifts. But they have to consider the possibility that these investments could become stranded and prepare accordingly — to either take the hit or extract sufficient value beforehand. Alternatively, some investments may transition themselves. Carbon assets have transition potential, provided they have a future in a hydrogen-based fuel scenario or can be retrofitted for carbon capture and storage (CCS). Both paths could contribute to achieving net-zero by 2050. But will they? We don’t know. There is too much uncertainty around the ultimate cost and effectiveness of transitioning such assets, especially when they could be displaced by lower-cost technology. The most prudent approach, then, may be to focus on no-regret assets. These will likely perform across all the most viable pathways of the energy transition: More renewables, more short-term and long-term storage, a stronger grid, heat pumps, and district heating should all be central to a carbon-free future. When faced with such critical decisions, we need to explore scenarios beyond our economic base case. We cannot assume rationality among all actors: The transition to net-zero won’t be smooth. There will be periods of slow progress, potentially followed by abrupt changes in the face of extreme weather events, technological advancements, political upheaval, pandemics, or other developments. It is important to plan for the future, so we need to be smart, careful, and deliberate about which future we choose. If you liked this post, don’t forget to subscribe to the Enterprising Investor. All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer. Image credit: ©Getty Images / precinbe Professional Learning for CFA Institute Members CFA Institute members are empowered to self-determine and self-report professional learning (PL) credits earned, including content on Enterprising Investor. Members can record credits easily using their online PL tracker. source

The investment management industry stands at a pivotal juncture, where artificial intelligence (AI) is reshaping many traditional processes and decision-making frameworks. From portfolio management to company analysis, AI’s capabilities offer unprecedented opportunities to enhance efficiency, scale expertise, and uncover novel insights. It also introduces risks, including overreliance, regulatory challenges, and ethical considerations. This post summarizes lessons learned from the front lines, incorporating insights from a team of investment specialists, academics, and regulators who are collaborating on a bi-monthly newsletter for finance professionals, “Augmented Intelligence in Investment Management.” Here, we explore AI’s transformative impact on the investment industry, focusing on its applications, limitations, and implications for professional investors. By examining recent research and industry trends, we aim to equip you with practical applications for navigating this evolving landscape. Lesson #1: Augmentation, Not Automation AI’s primary value in investment management lies in augmenting human capabilities rather than replacing them. According to a 2025 ESMA report, only 0.01% of 44 000 UCITS funds in the European Union explicitly incorporate AI or machine learning (ML) in their formal investment strategies [^1]. Despite this marginal adoption, AI tools, particularly large language models (LLMs), are increasingly used behind the scenes to support research, productivity, and decision-making. For instance, generative AI assists in synthesizing vast datasets, enabling faster analysis of market trends, regulatory documents, or ESG metrics. A 2025 study by Brynjolfsson, Li, and Raymond demonstrates AI’s ability to scale human expertise, particularly for less-experienced professionals. In a field experiment with customer-service agents, AI assistance reduced average handle times and improved customer satisfaction, with the most significant gains observed among novice workers [^2]. This suggests that AI can democratize expertise in investment settings, enabling less experienced investment professionals to perform complex tasks like financial modeling with greater accuracy. Practical Insight: For less-experienced investment professionals, investment firms may deploy AI tools to enhance their productivity, such as automating data collection or generating initial research drafts. More experienced professionals, however, could focus more on leveraging AI for hypothesis testing and scenario analysis. Lesson #2: Enhancing Strategic Decision-Making The impact of AI extends beyond operational efficiency. It also influences strategic decision-making. A 2024 article by Csaszar, Katkar, and Kim highlights AI’s potential to conduct a Porter’s Five Forces analysis [^3]. AI can also serve as a “devil’s advocate,” identifying risks and counterarguments to mitigate groupthink — a critical advantage for investment teams. In addition, AI-driven sentiment analysis tools, powered by natural language processing (NLP), can parse earnings calls, social media, or news to gauge market sentiment, offering investors a potential edge. However, AI’s “black-box” nature poses challenges. A 2024 study in Frontiers in Artificial Intelligence notes that AI’s opacity raises regulatory and trust concerns [^4]. Explainable AI (XAI) frameworks, which provide transparency into model outputs, are emerging as a potential solution to align with existing regulations. Practical Insight: For professional investors, the question is no longer whether to adopt AI, but how to integrate it into the investment decision design in a practical, transparent, risk-aware, and performance-enhancing manner. The second lesson highlights the limitations of the current generation of GPTs. With their pretended explainability, they all cannot explain how results were achieved. As a result, in high-stakes fiels like finance — where full transparency and control are essential — AI should be used to support decision design, not to make the final decision. Its role is best suited to generating ideas or automating components of the process, rather than serving as the final arbiter. Lesson #3: Preserving Human Judgment While AI can increase productivity, an overreliance may create tangible risks. One area that may have been overlooked is the risk that AI may erode critical thinking skills. A 2024 Wharton study on generative AI’s impact on learning found that students using AI tutors performed better initially but struggled when AI support was removed, indicating a potential loss of analytical skills [^6]. For investors, this suggests that excessive dependence on AI for tasks like valuation or due diligence could undermine the contrarian thinking and probabilistic reasoning essential for the generation of excess returns. Anthropic’s 2025 analysis further illustrates these cognitive outsourcing trends, where professionals delegate high-order thinking to AI. To counter this, investors must embed AI within structured workflows that encourage independent analysis. For instance, AI can generate initial investment theses, but in the end, investment professionals have the responsibility. They must deeply understand the thesis and firmly believe in it. Practical Insight: Create deliberate workflows where AI outputs are stress-tested through human-led discussions. Encourage analysts to perform periodic “AI-free” exercises, such as manual valuation or market forecasting, to maintain cognitive sharpness. Lesson #4: Ethical and Regulatory Challenges AI’s integration into investment processes may raise ethical and regulatory challenges. A 2024 Yale School of Management article highlights liability concerns when AI-driven decisions lead to unintended outcomes, such as discriminatory algorithms in recruiting or housing [^8]. In investment management, similar risks arise if biased models misprice assets or violate fiduciary duties. Moreover, a 2024 Stanford study reveals that LLMs exhibit social desirability biases, with more recent models showing a greater extent of biases. Practical Insight: With AI having a role in decision making, human guidance and oversight has become even more important. The assumption that machines can make better investment decisions by being more rational is unfounded. Current AI models still exhibit biases. Lesson #5: Investor Skill Sets Must Evolve As AI reshapes the investment industry, investor skill sets must evolve. A 2024 article in Development and Learning in Organizations argues that investors should prioritize critical thinking, creativity, and AI literacy over rote learning [^14]. Practical Insight: The shift from technical to non-technical skills—accompanied by a rising need for meta-skills like learning how to learn—is not a new phenomenon. It reflects a longer trajectory of technological advancement that began accelerating in the latter half of the 20th century and has steepened further with the emergence of AI-augmented human intelligence. The challenge now lies in targeting more precisely how these competencies are developed in a personalized manner, including support from machines through

Global mergers and acquisitions plunged to a decade low last year, with $2.9 trillion in deal value announced, down 17% from 2022. Dealmakers mostly stayed on the sidelines as they grappled with higher inflation, rising interest rates, increased regulatory scrutiny, and market uncertainty, while potential sellers remained anchored to previous, richer valuations. Activity among private equity (PE) buyers declined last year after accounting for nearly 25% of all buyouts in the previous two years as tighter financing conditions and higher interest rates made completing leveraged buyouts more difficult. In Canada, of the 441 completed transactions last year, most were bolt-ons to an existing company within a PE portfolio. PE firms found ways to keep doing deals in a higher rate environment by purchasing minority interests in companies. They preserved capital by writing smaller checks but allowed the target company shareholders to maintain interest in the company should the valuation recover. There were some bright spots. Activity picked up among commodity and industrial sector firms as inflation benefited many of them and companies looked to scale their operations to drive improved efficiencies. The energy sector led M&A activity with several mega merger deals announced in the back half of the year with deal activity in the US Permian shale region surpassing $100 billion. While technology sector M&A fell overall, two big deals — Activision Blizzard’s $69 billion acquisition by Microsoft and VMware’s $61 billion acquisition by Broadcom Inc — closed successfully. In the health care sector, activity increased as well with dozens of biotech and pharmaceutical merger announcements, while many large drugmakers face steep patent cliffs over the next decade and are seeking to refresh and extend their patent drug portfolios. Despite the challenges of 2023, the pick-up in the last quarter gave investors a glimpse of better days ahead. In 2024, dealmakers are battle-hardened and have adapted to the new regime by employing more structured deals to balance risk. These include the use of earn-outs, contingent value rights, carve-outs, and spin-offs. Dealmakers are also structuring transactions with all or part stock consideration as opposed to all cash. Acquirers often structure deals with all cash consideration when they have ample cash or access to financing and are confident enough to assume all the risk. With tighter financing conditions in general and especially for deals in capital-intensive industries, sharing the risk and reward with shareholders is becoming more common. Last year’s headwinds may become this year’s tailwinds, and we are optimistic about the outlook for M&A and merger arbitrage in 2024. As inflation cools, interest rate expectations trend lower, and companies adapt to the post pandemic environment, investor confidence is returning. Despite the geopolitical and economic backdrop of uncertainty, savvy companies are seeking opportunities to drive future growth and acquire the technologies and capabilities needed to compete and otherwise avoid being disrupted. On the deal side, indications from investment banks, advisors, and company insiders all suggest that the M&A pipeline is robust. Rising equity markets have given management and boards confidence to make deals with a growing number of companies in active dialogue. Shareholder activism is also rising as frustrated investors seek to unlock value in stocks trading at what they perceive as deep discounts to intrinsic value. Heading into proxy season, ineffective boards may become targets, and increased shareholder dissent could bring opportunistic acquirers to the table. Merger arbitrage may also offer an attractive investment opportunity, with merger arbitrage yields exceeding 10% for the average North American merger deal. This is a material premium relative to historical levels and a significant spread over high-yield bonds. Amid a more hostile regulatory environment, arbitrage investors now understand what sorts of deals may come under greater regulatory scrutiny. After a string of losses, regulators are stretched thin. With wide spreads, an improved playbook for assessing deal risk, and the potential for more M&A activity to materialize, 2024 could be a strong year for merger arbitrage performance.  If you liked this post, don’t forget to subscribe to Enterprising Investor and the CFA Institute Research and Policy Center. All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer. Image credit: ©Getty Images / noomcpk2528 Professional Learning for CFA Institute Members CFA Institute members are empowered to self-determine and self-report professional learning (PL) credits earned, including content on Enterprising Investor. Members can record credits easily using their online PL tracker. source

In an era characterized by significant disruptions, the future has become increasingly uncertain. Scenario planning is a crucial methodology tailored for such times. Unlike traditional forecasting, which relies on historical data to predict probable futures, scenario planning uses imagination to identify plausible futures. As the world grows more complex, strategic foresight methodologies encompass a broader range of futures. Scenario planning helps us to envision multiple outcomes and foster resilience against uncertainties. Systemic disruptions compel us to confront the inherent unpredictability of the future, highlighting the significance of scenario planning and foresight, both of which prioritize imagination. But most of us are not naturally inclined to confront change. As John Maynard Keynes put it in 1937, “The idea of the future being different from the present is so repugnant to our conventional modes of thought and behaviour that we, most of us, offer a great resistance to acting on it in practice.” The concept of “metaruptions,” coined by the Disruptive Futures Institute, describes multidimensional systemic disruptions that extend beyond initial impacts. Understanding these disruptions requires a creative approach, because conventional data analysis falls short. Scenario planning, originally developed in the 1950s and refined in the 1970s, provides a framework for exploring different futures and their implications. In 1982, John Naisbitt defined “megatrends” as large, transformative processes with global reach and significant impact. However, trends are reflections of the past, and extrapolating them can be perilous. Disruption marks the end of trends, compelling us to confront unpredictability. Here, imagination is a superior tool. Scenario Planning: A Safe Space Scenario planning is vital in investment management. By creating plausible narratives about future developments, it helps investors explore options and inform decision-making. This methodology encourages practitioners to challenge assumptions, adapt strategies based on emerging information, and avoid tunnel vision. The TUNA framework (Turbulence, Uncertainty, Novelty, Ambiguity) from the University of Oxford further aids investors in managing challenges by promoting imaginative thinking and questioning established assumptions. Navigating a TUNA world involves rethinking assumptions. Scenario planning provides a safe space to acknowledge uncertainty and encourages imagining previously inconceivable developments. Scenario planning and strategic foresight in general are essential tools for navigating future uncertainties in investment management. They provide structured approaches to anticipate and prepare for disruptive changes, enabling investors to make informed decisions and develop strategies that are robust across a range of futures. Scenario Planning vs. Forecasting Scenario planning is a critical discipline that explores plausible futures to identify emerging challenges and opportunities, setting it apart from forecasting, which relies on past data to predict risks and returns. Foresight manages complexity by framing problems, considering multiple pathways, surfacing current assumptions, scanning for weak signals, mapping the system, selecting change drivers, developing scenarios, and testing assumptions to identify potential challenges and opportunities. It is important that practitioners understand that foresight includes both scenario planning and forecasting. This approach allows investors, policymakers, and strategists to anticipate future developments and ensure proposed actions are resilient across various plausible futures. Sharing mental models and developing robust policy assumptions helps decision-makers rehearse for future challenges. Practical Implementation In most organizations, the responsibility for scenario planning typically resides within the Strategy division. It is not common to see roles such as Chief of Foresight or Scenario Officer within the investment industry. Rather, scenario planning is generally a collaborative effort among various strategists, leveraging the collective imagination and expertise of diverse team members to explore multiple plausible futures. By fostering resilience through the consideration of various outcomes, strategists can better anticipate and manage the complexities and disruptions that characterize today’s dynamic environment. A collaborative effort is essential in developing robust strategies that are resilient across a range of plausible futures, enhancing decision-making in an unpredictable world. source