Eyes on the Prize: How Far Will US Politics Move the Needle on Climate Risk
Transition to Transition: Guest Editor Robin Castelli on why we should stop talking ESG 1.0 and start talking Transition Finance
Stepping up: Michael Sheldrick makes the argument for three ways banks need to step up to meet the challenges of climate risk in the future
The Science of Emotion: Professor David Tuckett on a groundbreaking study into emotional response to risk management
Governance Risk & Reward: Sean Titley asks whether our Governance Frameworks are fit for purpose in a fast-moving risk environment
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The views and opinions expressed in this publication are those of the thought leader as an individual, and are not attributed to CeFPro or any particular organization.
05
FOREWORD
Is It the End of the World for ESG?
I Don’t Think So …
A month on from the new US administration coming to power, Robin Castelli asks what Republican agnosticism on climate issues means for the ESG risk community
06
THE SCIENCE OF CONVICTION: HOW EMOTION SHAPES FINANCIAL DECISION-MAKING
Professor David Tuckett explains how his Conviction Narrative Theory impacts on risk management, and how it’s being used to explore new AI frontiers
David Tuckett is a Professor and Director of the Centre on Decision-Making Uncertainty at University College London
10
PARIS CALLING – WHAT DOES THE EU SUMMIT TELL US ABOUT THE FUTURE OF AI?
Andreas Simou asks how the recent Paris Summit on AI and CeFPro’s Fintech Leaders report might shape the future strategy and implementation of AI in financial services
Andreas Simou is the Managing Director and CEO of CeFPro
16
RISK, REWARD AND THE FUTUTRE OF GOVERNANCE
Sean Titley looks at how balancing the opportunities and threats of emerging technology will be key to robust governance frameworks that can act as early warning systems in risk management
Sean Titley is a member of the International Risk Management Advisory Committee and a former Director of Enterprise, Operational and Model risk at Metro Bank
20
WHY I’M SPENDING AN INCREASING AMOUNT OF TIME AS A CRO ON NON-FINANCIAL RISK
Didier Magloire on why his focus is increasingly about managing non-financial rather than financial risk
Didier Magloire, Chief Risk Officer at ANZ China & ANZ Asia
24
THREE PRACTICAL WAYS FINANCIAL INSTITUTIONS CAN ADDRESS CLIMATE RISK
14
THE MODERN PROFESSIONAL’S DILEMMA: OVERCOMING THE GALILEAN HURDLES OF LEARNING IN THE AGE OF INFORMATION
Chandrakant Maheshwari looks at how the explosion of new technology in recent years is changing the game for learning and development in risk management careers
Chandrakant Maheshwari is FVP, Lead Model Validator at Flagstar Bank, NY
Michael Sheldrick looks at how financial institutions must adapt to escalating climate risks by integrating resilience incentives, advocating for climate levies and innovating financial incentives to mitigate economic shocks
Michael Sheldrick is the Co-Founder and Chief Policy, Impact and Government Affairs Officer at Global Citizen
28
SHIFTING GEARS FROM ESG 1.0 TO TRANSITION FINANCE
Guest editor C. Robin Castelli looks at why it’s time for a change in thinking around ESG, and makes the case for a Transition Finance mindset
C. Robin Castelli, Head of Transition Finance Investing, Orange Ridge Capital
32
AND
EVENT RISK Reena Mithal makes the case for the need for standardized risk-adjusted return metrics like Carbon Yield amid falling climate tech investment Reena V. Mithal Managing Partner, Sankhya Capital LLC
Connecting You to the Future of Risk & Finance
Connect Magazine delivers the insights, trends, and expert analysis you need to stay ahead in risk and finance. Stay informed. Stay competitive.
Magazine team
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Andreas Simou
Managing Director CeFPro andreas.simou@cefpro.com
Marketing
Ellie Dowsett
Editor
Mark Norman Head of Content CeFPro mark.norman@cefpro.com
Content and Media Marketing Manager CeFPro ellie.dowsett@cefpro.com
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Chris Simou Head of Sales CeFPro chris.simou@cefpro.com
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Is It the End of the World for ESG? I Don’t Think So
Robin Castelli, Managing Director - Partner, Head of Transition Finance Investments, Orange Ridge Capital Guest Editor
Welcome to the February edition of Connect Magazine from CeFPro – your monthly dose of insight and opinion on the key issues, themes and topics that are front of mind for those working within the financial services non-financial risk environment.
As guest editor of the magazine for this issue, and given the noise that has been coming out of the Oval Office since the newly-inaugurated US President began signing off on an unprecedented raft of executive orders, I’ve welcomed the opportunity to bring the issue of climate risk and ESG into the spotlight.
Recently, we have witnessed developments that have moved the dial away from the historical and familiar focus on reporting and disclosure, and further towards practical, and profitable, business opportunities that change always brings.
What this means, in short is more adaptation, and less mitigation – but there are still a lot of deals to be made. Whilst the climate-skeptical narrative emanating from 1600 Pennsylvania Avenue before and since January 20 continues to build to a crescendo, and mires ESG practitioners in a quagmire of policy, legal, and regulatory considerations, it’s worth keeping in mind that climate change is still a real phenomenon.
The world will have to adapt to it, and that adaptation will bring with it massive opportunities for those who have the vision to identify and intercept them.
In short: there is still much work to be done, and much to be gained. The route we take in dealing with climate risk may always be the subject of debate and differing opinion, but science has already shown us that there is little doubt about where the destination lies.
With a small focus on climate risk in this edition of the magazine, you can enjoy exclusive insights from some of the most highly respected figures working in this field. My thanks go out to Reena Mithal, and Michael Sheldrick for sharing their expertise in these pages.
Thanks also to Professor David Tuckett, who unveils a fascinating academic project to explore how media text can influence our emotional responses to risk scenarios, and also to all our other contributors this month whose wisdom underline Connect Magazine’s role in sharing knowledge and insight within the risk community.
If you would like to be the guest editor of a future edition of the magazine, would like to be interviewed for a thought leadership article, or think your organization would benefit from advertising and promotional opportunities within Connect, please get in touch. Contact details for our magazine staff can be found on page 4.
hope you enjoy this edition of the magazine. The next issue will be out on March 25.
Robin
The Science of Conviction: How Emotion Shapes Decision-Making in Risk Management
David Tuckett is the Director of the Centre on Decision-Making Uncertainty at University College London
The Power of Conviction in Uncertainty
What drives a financial professional to make a risky trade or hold back in times of risk?
We often assume that risk management decisions are based purely on logic and data, yet research suggests that emotion plays a much larger role than we might expect.
Back in the October edition of Connect, we spoke to Brandon Davis, from the University of Buckingham, about a groundbreaking study to uncover how emotions influence financial choices—and how understanding this dynamic could reshape risk management.
In this edition of the magazine another member of that academic team, Professor David Tuckett, Director of the UCL Centre on Decision-Making Uncertainty, explains the extent to which emotion informs the way humans interpret external data in order to reach good decisions around risk appetite.
The study, being run in partnership with CeFPro, also includes experts from Princeton University.
Tuckett’s Conviction Narrative Theory suggests that financial professionals rely on conviction narratives –stories they tell themselves to make sense of complex, uncertain information – when making high-stakes decisions.
Decoding Conviction Narrative Theory
Conviction Narrative Theory (CNT) challenges the traditional notion that rationality alone drives financial decision-making. Instead, Tuckett explains that “under radical uncertainty – that is, contexts in which at the time you make the decision you can’t know the outcome – people draw on conviction narratives to support their actions.”
These narratives act as mental shortcuts, helping us to navigate an overwhelming amount of data, filtering information, highlighting perceived risks and opportunities, and creating an emotional response that guides action.
As Tuckett puts it, “the brain is a constant interaction between thinking and feeling.”
Put another way, a CRO reading a data report isn’t just processing statistics; they’re also experiencing gut reactions that influence the way they interpret that data.
To test this theory, Tuckett and his team are conducting an online experiment – open to Connect readers –in which participants read different financial texts and then indicate whether they would buy or sell a particular asset, or accept or decline a particular risk.
By analyzing how specific words and emotional cues influence decisions, the study aims to determine whether financial professionals are subconsciously guided by emotion-laden narratives.
How Words Shape Financial Risk Perception
The research builds on previous studies showing that language can signal shifts in market sentiment. By applying CNT to large text databases – such as Reuters News or the Bank of England reports – the team has already demonstrated that emotional language in financial texts can anticipate market trends.
One striking example, Tuckett says, comes from their analysis of news coverage in the years leading up to the 2008 financial crisis.
“One result we found was that if you plot a graph showing the relative amount of excitement minus doubt or anxiety in articles about Fanny Mae, you could see an upward trend right up until the crash happened,” he says.
“But very interestingly, if you plot that graph against the Case-Shiller housing price index, you see that in 2006, it began to turn down. Yet it had no impact on sentiment or the share price.”
This suggests that financial markets may be slow to react to fundamental changes because prevailing and exciting “phantastic object” narratives override emerging warning signs.
If traders and analysts remain emotionally invested in such exciting stories, they may ignore factual data that contradicts it.
Testing the Theory: An AI-Driven Future
Tuckett’s project is not just about understanding how narratives influence decisions – it’s also about applying this knowledge to improve financial forecasting.
By identifying which words and phrases trigger approach (confidence) or avoidance (fear), the team hopes to build AI models capable of detecting hidden market risks.
“Supposing you ran these AI models over analyst reports of different investment opportunities,” Tuckett explains, “they would probably pick up things that could not be detected just by reading and making sense of the words.”
This could be an invaluable tool for financial institutions, allowing those organizations of scale to analyze internal reports for unseen risks or even predict shifts in market sentiment before they happen.
The experiment will culminate in AI models designed to analyze financial texts more accurately, providing traders and analysts with an early warning system for emerging risks.
“The survey results should be completed by March, and the AI models we’re building based on them should be available in May,” says Tuckett.
Emotion: The Hidden Driver of Financial Decisions
The implications of CNT extend beyond financial markets. If professionals in high-stakes fields unconsciously rely on conviction narratives, it raises questions about the role of emotion in all forms of decision-making.
Interestingly, many financial professionals pride themselves on their ability to suppress emotion when assessing risk.
But Tuckett argues that emotion isn’t just unavoidable—it’s essential.
“There are financial professionals who say that the way to assess risk well is to keep your emotions out of it,” he says. “But I would say the opposite. I mean, clearly you don’t want uncontrolled emotions, but basically emotion stimulated in our brains is a very, very important part of information. Human beings have evolved to use their emotions to pick up stuff.”
If the team’s research proves successful, it may force a re-evaluation of conventional wisdom in risk management. Rather than viewing emotion as a weakness, firms may begin to recognize it as a powerful tool – one that can be harnessed to improve risk assessment and decision-making.
How to Participate and What’s Next
For those in the financial sector curious about how conviction narratives shape their own decision-making, there’s an opportunity to participate in the study.
The online experiment is open to finance professionals who want to test their own risk perceptions and contribute to the development of AI-driven market analysis.
The only way to see the full results of the study is to take part. Participants will gain insights into how emotional cues influence their own financial choices, offering a rare opportunity for self-reflection in a field that often prioritizes hard data over intuition.
As financial markets grow increasingly complex and volatile, the ability to understand and measure sentiment could become a game-changer.
Tuckett’s work suggests that the next frontier of financial analysis may not lie in crunching numbers – but in decoding the narratives that drive them.
If you would like to take part in the study and have access to the results once they are released, please email mark.norman@cefpro.com putting UoB Study in the subject field and we will pass your details to the research team
Can AI Learn to Think Like You?
AI is only as powerful as the humans who shape it. Join a groundbreaking research study with CeFPro, UCL, The University of Buckingham, and Princeton University to train an AI model designed for real-world financial decision-making.
Our objective?
Integrate human judgment into a large language model that aids financial institutions in making precise risk responses.
By observing how risk perceptions evolve when reading news text, we can train the model to see overreactions or underreactions to risk, in real time.
Paris Calling – What Does the EU Summit Tell Us About the Future of AI?
Andreas is the Managing Director and CEO at the Centre for Finance Professionals
Artificial Intelligence (AI) has rapidly become one of the most talked-about technologies across various industries, and in recent years has garnered significant attention in the media and among businesses worldwide.
Yet compared to other sectors, financial institutions have been slower to embrace this technological revolution.
Unusual, some might argue, particularly given the apparent resources of financial institutions and the cost benefits they could offer. Others, though, will argue that prudence is required before we relinquish too much control to the machines.
While many agree on the potential benefits of innovation and collaboration, the recent AI Summit in Paris revealed stark differences in how nations and regions are approaching AI, with a particularly noticeable divide between the United States, the United Kingdom, China and the European Union.
Global Divergence in AI Regulation and Strategy
At the Paris summit, U.S. Vice President J. D. Vance sparked controversy when he argued that excessive regulation could stifle innovation and essentially ‘kill’ AI before its full potential is met, warning delegates against undertaking deals with ‘authoritarian’ partners.
The first was a direct jibe at the European Union’s newly implemented EU AI Act, while the latter was viewed as the growing threat that the United States sees from China.
The U.S. stance is rooted in a broader political context, reflecting Trumpian ‘America First’ policy, and contrasts with the previous U.S. administration that promoted international cooperation and compromise.
But the geopolitical landscape surrounding AI development is increasingly influenced by economic and strategic considerations. The United States currently leads in AI research, chip manufacturing, and chatbot technology.
However, China’s rapid advancements, such as the recently highly publicized DeepSeek AI, pose a significant challenge to the U.S.
The Chinese firm recently announced the capability to produce high-performance AI systems at a fraction of the cost of Western industries, threatening U.S. dominance in the sector.
In response, the U.S. administration is investing heavily – starting with $500 billion – to regain its competitive edge.
By contrast, the EU’s announcement at the Paris AI Summit of an investment of around €200 billion illustrates where the capital and determination is set to flow from.
AI Adoption in Financial Services: Opportunities and Challenges
What, though, does this mean for financial institutions and the future of AI?
Recent surveys conducted by industry experts shed light on the opportunities and challenges that financial institutions face in implementing AI technologies.
CeFPro’s Fintech Leaders 2025 report which gathered insights from hundreds of financial and risk professionals, highlights several key issues, including governance, bias, misinformation, and regulatory uncertainty as obstacles to AI development.
Within the U.S., the unrestrained approach to AI will allow for rapid development and advancement, which was a significant obstacle to the adoption of AI. After all, why invest time, resources and capital when this could be stifled by regulations?
However, providing an environment for growth is just one obstacle, and there are many more within financial institutions that need to be overcome.
One of the most significant challenges is the ambiguity surrounding accountability within organizations.
Financial institutions are still determining who should take primary responsibility for AI as a whole – whether it’s the technology, data, or risk management teams. This uncertainty extends to strategic priorities and practical applications, which vary significantly across different regions.
AI Applications, Opportunities and Investment in FS
Despite these challenges, AI presents significant opportunities, with anti-fraud being a clear example of measurable increased efficiency and effectiveness; this is also an area where some of the greatest investment will occur, according to the respondents of CeFPro’s Fintech Leaders survey.
Up to 76% of respondents identified data-centric AI (traditional AI) as the most significant opportunity in financial services for 2025. This version of AI focuses on data analysis, pattern recognition, and decision-
making support, making it highly applicable for risk assessment and fraud detection.
But when we look at a longer horizon, Generative AI (GenAI) emerges as the frontrunner.
By 2030, 66% of respondents expect GenAI to offer the greatest opportunities in financial services. Unlike traditional AI, GenAI can create new content, including text, images, and even code, enabling more dynamic and personalized customer experiences.
Nonetheless, risk managers express reservations about GenAI, citing concerns over regulatory uncertainties and potential backlash from consumers or policymakers.
This cautious stance has led to a ‘wait and see’ approach, where firms are hesitant to be first movers in adopting GenAI, which in itself is a risk in that the industry moves so fast that if you wait too long you could be left behind, and the investment will be significantly greater when there is a sudden demand for the services.
In terms of investment priorities, AI ranks high but is still overshadowed by cybersecurity.
CeFPro’s Fintech Leaders survey identified cybersecurity as the top investment priority for financial institutions, a position it has maintained for several years. This focus on security is crucial, since financial institutions face increasing threats from cyberattacks, data breaches, and regulatory scrutiny.
Nevertheless, AI continues to gain traction, with traditional AI and GenAI ranking as the second and third most important investment areas, respectively.
Financial institutions are particularly interested in leveraging AI for process optimization, risk management, and customer engagement. Yet, significant challenges remain, especially in aligning AI initiatives with strategic goals and regulatory requirements.
A Case for AI Adoption: Third-Party Risk Management
One promising application of AI within financial services is in third-party risk management.
A separate white paper conducted by CeFPro, surveying nearly 200 industry professionals, highlighted the potential of GenAI to enhance productivity, streamline workflows, and automate labor-intensive processes.
GenAI can significantly improve third-party document management and compliance monitoring, reducing operational costs and increasing efficiency.
However, the survey results also revealed significant concerns about data security, high implementation costs, and the need for skilled personnel to manage GenAI effectively.
Despite these challenges, 62% of respondents indicated plans to increase AI adoption in third-party risk management within the next two years, recognizing its strategic potential for improved efficiency and flexibility.
The Future of AI in Financial Services: Uncertainty and Opportunity
The strategic direction of AI in financial services could be heavily influenced by geopolitical dynamics, regulatory frameworks, and technological advancements.
The U.S. appears poised to maintain its leadership by fostering an innovation-friendly environment, while China continues to challenge this dominance with aggressive investments in AI research and development.
Meanwhile, Europe is taking a more cautious approach, emphasizing ethical considerations and robust regulatory safeguards.
This divergence raises critical questions about the future of AI: Will global collaboration be possible amid differing regulatory landscapes? Can financial institutions navigate these complexities to fully leverage AI’s potential? And, most importantly, how will consumers and businesses adopt and be impacted by these advancements?
The future of AI in financial services is both promising and uncertain. While the technology offers transformative potential, its adoption is hindered by regulatory complexities, geopolitical tensions, and internal organizational challenges.
Financial institutions must strategically navigate this landscape by balancing innovation with compliance, investing in cybersecurity, and fostering cross-functional and cross-border collaboration.
To view a copy of CeFPro’s reports referenced above, please download at our members hub, CeFPro Connect, connect.cefpro.com/report
The Modern Professional’s Dilemma:
Overcoming the Galilean Hurdles of Learning in the Age of Information
Chandrakant is First Vice President, Lead Model Validator at Flagstar Bank, New York. He has more than 15 years’ experience in Financial Risk Management (Market and Credit Risk) and has previously worked with business consulting firm Genpact. He is this month’s guest editor of Connect Magazine
In a world saturated with advanced learning technologies and vast reservoirs of knowledge accessible with a mere click, one might assume that the path to professional development has never been smoother. Yet, the modern risk professional faces a paradox similar to the astronomers of Galileo’s era.
Just as some scholars refused to peer through Galileo’s telescope, thus denying themselves a broader understanding of the universe, today’s professionals often wrestle with cognitive and behavioral barriers that impede their learning and adaptation in a rapidly evolving workplace.
The Telescope of Today: YouTube, GenAI, and Beyond
Today’s learning tools are powerful and pervasive. Platforms like YouTube offer endless tutorials and insights on virtually any subject, while Generative AI (GenAI) technologies present tailored learning experiences and instant informational retrieval capabilities.
These tools promise a democratization of knowledge and a revolution in personal and professional growth. However, their mere presence is not a panacea for the inherent challenges that come with learning and adaptation.
Galilean Hurdles in Modern Learning
1. Procrastination: Procrastination remains a formidable foe. With an overwhelming array of choices and resources, the decision to start learning something new or to update one’s skills can be continually postponed. Like the clerics who refused to look through Galileo’s telescope, professionals today may put off engaging with new technologies or methodologies that could challenge or change their current understanding or workflows.
2. Cognitive Rigidity: Professionals often display cognitive rigidity, clinging to familiar knowledge and tools that have served them well in the past. This rigidity can make them resistant to adopting new technologies or methodologies that conflict with their established views, akin to the Aristotelian scholars who rejected Galileo’s heliocentric proofs.
3. Confirmation Bias: These bias leads professionals to favor information that confirms their pre-existing beliefs or hypotheses. In an age where information is abundant, the tendency to filter out information that contradicts one’s established perspectives can severely limit one’s professional growth.
4. Over-Reliance on Past Successes: Success can breed complacency. Professionals may rely too heavily on strategies and skills that have yielded results in the past, failing to recognize when market dynamics or technological advancements have rendered their tried-and-tested methods obsolete.
5. Fear of Failure: The rapid pace of change in professional environments can engender a fear of failure. Many might avoid utilizing new tools or gaining new competencies due to fear of making mistakes in front of peers or superiors.
6. Information Overload: The sheer volume of available information can lead to paralysis by analysis, where making any decision becomes daunting. This overload can deter professionals from taking the initial steps necessary to integrate new knowledge or tools into their practices.
Navigating
the Stars: Strategies for
Overcoming Learning Barriers
To overcome these modern Galilean hurdles, professionals can adopt several strategies:
• Structured Learning Pathways: Creating clear, manageable learning objectives and timelines can help mitigate the feeling of being overwhelmed and reduce procrastination.
• Embracing a Growth Mindset: Adopting a mindset that views challenges as opportunities for growth rather than threats can alleviate fears of failure and reduce cognitive rigidity.
• Diverse Information Sources: Actively seeking out diverse sources of information can help counter confirmation bias and encourage more holistic understanding of new developments.
• Regular Skills Audits: Periodically assessing one’s skill set and comparing it against industry benchmarks can help identify areas for improvement and reduce over-reliance on outdated methods.
• Mindful Consumption: Setting specific goals for information consumption and using tools that curate content can help manage information overload effectively.
In conclusion, the modern professional must navigate a landscape filled with both unprecedented opportunities and significant psychological and behavioral hurdles.
By recognizing and addressing these modern Galilean hurdles, professionals can fully leverage today’s telescopes of technology and knowledge to enhance their competencies and remain competitive in their fields.
Risk, Reward, and the Future of Governance
Sean Titley is an experienced senior risk manager with an extensive background in operational and credit risk. He is a member of the International Risk Management Advisory Committee, and was previously Director of Enterprise, Operational and Model Risk at Metro Bank
Head into any discussion or event concerning the subject of risk management and what’s keeping CROs and other senior risk leaders awake at night, and the chances are you’ll find yourself in a conversation about technology.
The financial services sector is becoming increasingly digitally volatile. That, in and of itself, isn’t necessarily a bad thing: in our burgeoning tech-focused world, AI, blockchain, and cyber offer opportunities as much as they do threats.
The challenge for risk management teams isn’t about how to suppress those tools. Rather, it is about how to give them room to breathe without losing control and having them become the runaway train that outpaces an organization’s existing governance frameworks.
Emerging technologies like AI and blockchain are reshaping our lives on personal, industrial, organizational and financial levels. The endgame lies not in keeping up with them so much as getting ahead of them.
That means looking at emerging trends around tech usage and regulatory and compliance expectations – and then applying and adapting fit-for-purpose frameworks – proactively – to identify and intercept risk at the earliest possible moment.
Sean Titley, a seasoned expert in risk management, has seen this transformation firsthand. With decades of experience across credit risk, non-financial risk, and operational risk, he has worked with institutions ranging from retail banks to asset finance firms.
In April, he will share his insight on this subject at CeFPro’s upcoming Risk Evolve conference. When Connect caught up with him earlier this month, he reflected on the importance of robust governance frameworks and the strategies organizations need to implement in an era of rapid technological advancement.
Keeping Up with Emerging Risks
The conversation around risk frameworks and emerging technologies is not new, he observes, but it remains an ongoing challenge.
“There’s been a tendency to layer new frameworks on top of old ones,” he said. “But rather than creating more committees and complexity, we should look at AI and other emerging risks as cross-cutting themes that impact multiple areas – data security, technology disruption, and more.”
To keep pace, organizations need to ensure they have the right expertise in place. “It’s about training, awareness, and making sure you’ve got the right reporting all the way up to the board level,” he explains.
“Keeping on top of fast-moving developments is crucial, and that means having the right people in place to interpret and act on the risks as they emerge.”
The Role of Technology in Risk Management
We all know that the digital landscape is evolving at an unprecedented rate, and non-financial risks— such as cybersecurity, ESG concerns, and regulatory compliance—are at the forefront of industry thinking.
To be effective, organizations must adopt data-driven approaches to risk management – and that requires the right tools.
“There’s only so much you can do with Excel,” Titley points out. “For small organizations, you work with what you have. But for medium and larger firms, investing in the right risk management systems is essential. You need real-time insights to make informed decisions.”
AI, in particular, is transforming how organizations monitor and manage risks. “Many firms are already using AI to track trends across risk events, system issues, and key indicators,” he says.
“Even tools like ChatGPT can be useful for benchmarking and developing risk frameworks –though, of course, you have to be careful. Feeding sensitive company data into an open-source AI tool can land you in a whole heap of trouble.”
The challenge, he explains, is striking a balance between innovation and control. “AI is both a risk and an opportunity. It’s a powerful tool, but it needs human oversight.
“The concept of ‘prompt engineering’ – asking the right questions and interpreting responses correctly – is becoming an essential skill in risk management.”
Navigating the Compliance Challenge
In highly regulated industries, risk managers are required to work within strict compliance frameworks while also staying ahead of bad actors who exploit gaps in the system.
The problem for the risk management function is that cybercriminals don’t need permission to use AI. They move fast, and they’re always ahead of the game, and that, Titley warns, means the ‘good guys’ need to leverage AI just as aggressively to stay competitive.
But he also acknowledges the pitfalls of relying too heavily on technology. “There’s always a temptation to think AI can solve everything—just implement it and be done with it. But in reality, AI can sometimes undermine or outpace the very governance structures we’re trying to build. The trick is to stay agile.”
From ‘No’ to ‘How’: Changing the Culture of Risk Management
Once viewed as the “no” team – the department that blocked ideas rather than enabling them – risk management is undergoing a cultural shift.
Titley believes that today’s risk professionals need to fulfil the role of trusted advisors, helping businesses find solutions rather than shutting down innovation.
“It’s all about people,” he emphasizes. “Risk teams need to understand the business and be seen as enablers, not blockers. Yes, sometimes you have to say no, but more often, it’s about re-engineering a proposal to ensure the right guardrails are in place.”
This shift requires embedding risk management into the business at the right level. “You don’t want to bog yourself down in endless meetings,” he says. “Instead, you need to be strategically involved at the right points in the decision-making process.”
Real-Time Risk Monitoring: The New Standard
The days of annual risk assessments are over. “Doing a risk and control self-assessment once a year, dusting it off, and calling it done just doesn’t cut it anymore,” says Ttiley. “Risk management needs to be a continuous, near real-time process.”
To achieve this, organizations must join the dots between different areas – data issues, system failures, customer concerns – while ensuring their risk indicators are relevant and up to date.
“You need to use the same level of sophisticated tools to assess risk as the business uses to run its operations,” he adds.
What’s the One Key to Stronger Governance?
Asked to name the single most important factor in improving risk governance, Titley doesn’t hesitate: “Be practical and business aware. While every organization needs to follow core risk principles, you have to apply them in a way that makes sense for the business.”
He warns against newcomers to the financial sector who try to bypass essential risk management structures.
“Some new entrants have attempted to ditch key risk principles, thinking they can operate without them. That’s a mistake. At the same time, though, governance frameworks must be proportionate to the size and nature of the business.”
Ultimately, risk management is about striking a balance—between innovation and control, between agility and regulation, and between safeguarding the business and enabling it to thrive.
“It’s an evolving landscape,” Titley concludes, “and the key is to stay ahead of the curve.”
FINTECH LEADERS
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Why I’m Spending an Increasing Amount of Time as a CRO on Non-Financial Risk
In my capacity as a chief risk officer, I oversee a broad spectrum of risks which are largely divided into two pots. We call them financial and non-financial risk, a delineation which is commonly acknowledged in the banking industry.
Financial risks are the ones that first come to mind when I talk about finance and risk management in a social setting, like at a cocktail party where I might casually chat with another guest.
The guests understand credit risk and, with a little bit of explaining, market risk. But at this gathering, I rarely have the opportunity to delve deeper and explain how, as a CRO, spend an increasingly large amount of my time on something incredibly interesting and intellectually challenging, which is non-financial risk (NFR).
If it does come up, I keep the explanation high level (and hopefully intriguing), saying a large part of my role is focused on people and corporate culture. Let me explain.
In banking, institutions are spending more money and time on managing compliance with regulations, reducing operational errors, fighting fraud and
cyber threats. Add to that geopolitical uncertainties, climate risk and other external events, and the list of nonfinancial risks starts to become quite long. Managing these risks is increasingly important because of the ever-changing external environment, the complexity of large banks, and regulators’ increasingly high expectations.
My argument is that despite its moniker, the impact of NFR on financial institutions is in many ways more threatening than that of financial risks.
NFR poses distinctive challenges, necessitating a departure from conventional financial risk management approaches that have been in place for decades. The problems NFR poses for CROs is that some NFR events are more difficult to predict.
Take climate risk as an example. The long term trend of more volatile weather events is very clear, yet the location and severity of the next big storm or drought can be hard to predict. Reputation takes years to build, so protecting it is essential. The goal is to avoid the occurrence of any material events that might affect organizational reputation negatively. But the potential impact on the firm of any event is hard to quantify.
A bank’s reputation in the market or its relationship with regulators and media is precious, and damage to it can be immeasurable.
Consequently, it is difficult to apply the traditional financial risk management approach when addressing these risks.
Risk Appetite’s Battle with NFR
Typically, the risk management process starts with defining a risk appetite, and assessing the threshold within which a financial institution is willing to assume certain risks.
Financial risk is commonly expressed in monetary terms – typically representing the amount a bank is prepared to put at risk and potentially lose.
However, setting risk appetite for NFR is a much more elusive and theoretical concept. How do you set a risk appetite for an event when your stated tolerance should be zero occurrences?
Or how do you quantify damage to the firm’s reputation, for example being mentioned in a less-than flattering story on the front page of The Financial Times?
A little bit is nice if the coverage is fair-minded, but not a lot if your institution or name is mentioned negatively.
That, however, does not sound very scientific. To mitigate this dilemma, we set key performance indicators, measuring the events that by themselves are manageable and measurable, but that may lead to bigger problems in the long run.
Key performance indicators may seem subjective or misguided. Keeping up with required training is an example. Does the training really help avoid major issues? In my view, it does – and if not enough people sign up to training by a certain time, I get an alert.
Therefore, it is crucial to regularly discuss these indicators, contextualise the concepts through reallife examples, such audit or self-assessment findings, study close calls or other bank mishaps, and so on. These discussions represent the opportunity to emphasize the importance of individuals within the firm acting judiciously.
The importance of NFR culture
While some events leading to NFR are beyond our control, many can be effectively managed through policies, procedures, systems and training.
An in-depth analysis often reveals that the root cause of risk involves people: their business priorities, institutional beliefs and behaviour.
To consistently reduce NFR, we emphasise the development, embedding and sustaining of a robust risk culture, one that fosters the desired behaviours.
Key elements of a sound risk culture include open communication, dialogue on risks and concerns, identification of opportunities for continuous improvement, risk awareness, ownership and accountability, and defining risk appetite and tolerance.
Measuring this is tough, but you do get a strong indication of your direction of travel through risk culture surveys over time.
Then you look at the long-term trend of those key performance indicators. As we said earlier, tolerance levels are appropriately low for certain risk classes, such as reputational or compliance risk.
For this reason, a preferred risk mitigation strategy is avoiding the event altogether, relying on low tolerance levels for the events themselves, supported by KPIs.
An illustrative instance is the significant fines incurred over the prolonged use of WhatsApp for business purposes across the banking industry at large.
This behaviour persisted for years without adequate intervention, indicating potential failures in risk awareness, communication channels (speaking up) and accountability – all integral components of a robust risk culture.
A good CRO is therefore a people person. More than a culture carrier, he or she works with the CEO and the leadership team to promote and embed the right risk culture, to change day-today behaviours in a way that can materially reduce risks at the firm.
This article originally appeared in a publication by FT
Didier Magloire, Chief Risk Officer
ANZ China & ANZ Asia
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Three Practical Ways Financial Institutions
Can Address Climate Risk
Michael Sheldrick is the co-founder and Chief Policy, Impact and Government Affairs Officer at the Global Citizen platform, which exists to mobilize millions of people and convenes across sectors to drive tangible policy change and financial investments to defeat poverty, demand equity and defend the planet. He is also a highly respected author and an Associate Professor at Columbia University.
As climate disasters like wildfires, floods, and hurricanes become more frequent and severe, financial institutions such as banks, insurers, and other investors have two choices:
Adapt — by pricing climate risk correctly, helping people prepare, and creating financial safeguards for disasters.
Ignore reality — afraid to be a “first-mover” and continue business as usual, leaving homeowners, businesses, entire economies, and ultimately themselves dangerously exposed to financial losses.
So far, most financial institutions have been too slow to act, and the consequences are already playing out.
California’s Wildfire Crisis: A Case Study in Mispriced Risk
Regular readers will have doubtless read with interest Craig Spielmann’s article in last month’s edition of Connect which looked at the social and economic impact of the Los Angeles wildfires in January, which highlighted the increasingly arbitrary, and ultimately unsustainable, nature of the insurance industry.
Most insurers currently take an all-or-nothing approach—either fully covering an area or withdrawing entirely—without properly recognizing or incentivizing efforts to make homes and communities more resilient to climate disasters. Even California’s FAIR Plan, the state’s last-resort insurance, fails to account for risk reduction measures in its premium calculations.
In the lead-up to the fires, insurers withdrew en masse from high-risk areas or sharply increased premiums, leaving homeowners with few or unaffordable options. At the same time, banks continued issuing mortgages for fire-prone homes without factoring in the growing
likelihood that insurance would be unavailable or unaffordable.
The result? Many households were left uninsured, and there was little incentive to invest in fire resilience, despite the availability of risk-reduction measures. The financial toll of this failure is staggering—California’s January wildfires alone are estimated to have caused over $100 billion in damages, with 60% of losses uninsured.
But California is just one example. Global losses from natural disasters in 2024 reached approximately $320 billion, according to reinsurance firm Munich Re—well above the inflation-adjusted average for the past decade. Likewise, a 2023 study of 12,000 companies by Morningstar Sustainalytics found that corporate assets in the United States are among the most vulnerable to climate disasters.
Looking ahead, a timely new report from First Street warns that climate-driven floods, wildfires, and extreme weather could wipe out $1.5 trillion in U.S. home values over the next three decades.
In response, insurers are pulling out of high-risk states beyond California, including Florida and Louisiana, as extreme weather makes coverage unsustainable. But retreating from one area is not a long-term solution.
Ultimately, insurers depend on broad economic stability to remain profitable. When climate disasters trigger large-scale market collapses, they don’t just face rising claims—they also see their investments (e.g., real estate, bonds, etc.) erode. Pulling out of high-risk areas doesn’t eliminate exposure; it simply concentrates risk elsewhere. After all, a shrinking customer base makes it harder to spread risk, driving up costs across the entire system and making coverage unsustainable for everyone.
With climate impacts expected to be widespread, leaving few communities immune, insurers—and financial institutions more broadly—cannot simply retreat. Without greater climate resilience, new schemes to offset losses and raise additional capital, and stronger measures to protect the fiscal stability of climate-vulnerable economies, this is a crisis they can’t outrun.
1) Reward Resilience
Insurers and lenders can integrate climate vulnerability into pricing models to incentivize greater investment in resilience efforts. For example:
Homeowners who clear brush, install fire-resistant materials, or maintain firebreaks should receive lower wildfire insurance premiums. California’s “Safer from Wildfires” initiative already mandates that insurers provide discounts for such mitigation efforts. However, implementation has faced challenges, with some discounts being too minimal to drive meaningful behavior change. For instance, starting September 1, 2024, State Farm offered only a 0.1% premium reduction for installing fire-resistant windows—just $14 off a $13,800 premium.
Businesses that elevate buildings or enhance flood defenses should receive lower flood insurance rates. In *Switzerland, insurers—driven by both regulations and market forces—now offer lower premiums to properties built with flood-resistant construction, actively incentivizing risk reduction.
2) Advocate for Climate Accountability
Even with better risk assessment that provides stronger incentives for disaster prevention, some disasters will be too costly or too frequent for insurers to cover alone. That’s where governments need to step in—but not just through a last-minute scramble for emergency funds, which is neither sustainable nor responsible.
California’s $10 billion ‘rainy day fund’ was designed for economic downturns—not to cover $60 billion in uninsured wildfire losses. As of this writing, FAIR has already requested an additional $1 billion from private insurers to cover claims from the recent wildfires, and taxpayers will likely bear part of the cost as well.
A solution lies in policies that require those driving climate risk (i.e., high-emission industries) to contribute their fair share toward future losses and damages. New York’s Climate Superfund Act is a prime example, mandating that major polluters pay into a $75 billion fund for disaster recovery.
Momentum is growing for similar efforts worldwide. At the 2023 UN climate talks (COP28), the Global Solidarity Levies Task Force was launched to develop scalable levies that make polluting industries pay for climate action. Already backed by 17 governments, the task force is working on concrete proposals to be adopted at the next UN climate talks—COP30 in Brazil this November.
Public support is also strong. A Global CitizenGlocalities report found widespread backing across G7 countries—including bipartisan support in the U.S.— for holding high-emission industries financially accountable.
Of course, implementing such levies falls within the purview of policymakers, but financial institutions—banks,
insurers, and other investors—have a direct incentive to advocate for them. After all, it’s about protecting financial markets from long-term instability. As AXA’s CEO, Thomas Buberl, warned, if temperatures rise too much, we may reach a point where the vast majority of the world becomes uninsurable.
Moreover, by supporting the implementation of climate levies, financial institutions won’t feel penalized for taking voluntary action that their competitors may avoid. Instead, they will have a stronger marketdriven incentive to shift their lending, investment, and insurance practices toward cleaner, lower-risk industries—rather than continuing to, in effect, fund the crisis. Specifically:
Insurers will have a stronger business case to stop underwriting projects that worsen climate risk— reducing future liabilities.
Banks will face fewer high-risk borrowers as polluting industries are forced to account for their true costs.
Investors will gain clearer financial signals, ensuring that climate risk is treated not just as an ethical concern but as a material financial threat.
3) Deploy New Financial Tools to Mitigate Economic Shocks
Climate impacts are not just a problem for individual homeowners or businesses in the U.S.—they pose a risk to entire economies. When disasters wipe out a significant portion of a country’s GDP, governments— especially those of smaller, more vulnerable economies—must choose between funding recovery or repaying debt. This leads to higher borrowing costs and rising default risks that directly impact banks, bondholders, and insurers.
Take Malawi, which was hit by Cyclone Freddy in 2023—one of the longest-lasting storms on record. The cyclone displaced 500,000 people and wiped out 10% of the country’s GDP. Already burdened with debt, Malawi had to divert funds from essential services to repay creditors, delaying recovery and increasing the risk of economic collapse—which, in turn, heightened the risk of defaulting on debt repayments.
These risks aren’t confined to developing nations. Wealthier economies are also vulnerable to soaring debt burdens, credit rating downgrades, and economic shocks resulting from climate change, which pose a threat to financial markets.
To prevent climate-driven financial collapse, financial institutions can both adopt and advocate for new mechanisms that protect borrowers and lenders while giving governments the fiscal space to respond to climate-induced crises. One such solution, which I document in my book From Ideas to Impact, is natural disaster clauses.
A natural disaster clause is a debt-relief mechanism that allows governments to temporarily pause or restructure loan repayments after a major climate disaster, freeing up funds for emergency response and recovery without risking default. This reduces the risk of immediate financial collapse and ensures eventual repayment, as affected countries are not forced to choose between default and disaster recovery.
In recent years, natural disaster clauses have become more standardized, thanks in large part to the advocacy of leaders like Prime Minister Mia Mottley of Barbados and the financial expertise of firms such as White Oak Advisory. The World Bank and multiple public bondholders have pledged to include these clauses in loan agreements with dozens of climate-vulnerable countries, and private investors are following suit.
In July 2024, Hurricane Beryl devastated Grenada, making it the first country to trigger a natural disaster clause and defer debt payments for a year.
Building a Climate-Resilient Financial System—Before It’s Too Late
The real risk isn’t just climate disasters—it’s the failure of financial systems to anticipate and adapt to them. If banks, insurers, and investors continue ignoring climate risk, they will fuel instability, drive up costs, and weaken economic security.
But financial institutions, through their power to shape markets, influence policy, and drive systemic change, can lead the transition toward a more stable, climateresilient economy by:
Rewarding resilience efforts—ensuring that riskreduction measures, like wildfire buffers or flood defenses, lead to lower premiums rather than market withdrawals.
Advocating for climate levies—ensuring that banks, insurers, and investors have clear incentives to reduce their dependence on high-emitting industries and, in turn, help address the root causes of climate change.
Deploying innovative financial mechanisms —such as natural disaster clauses, resilience-linked loans, and climate bonds that help nations and businesses withstand economic shocks.
Shifting gears from ESG 1.0 toTransition Finance
C. Robin Castelli is Head of Transition Finance Investing at Orange Ridge Capital. He’s an expert in climate risk, transition finance, and private equity, with a strong background in quantitative modeling, financial analysis, and strategic management. In a long and successful career, he has led defense programs, conducted due diligence, and driven innovation in financial and technological sectors. He is fluent in three languages and is a highly respected author on the subject of transition finance.
The recent developments in global politics and regulatory/banking alignments away from ESG themes are a most visible and obvious trend in a phenomenon that has been years in the making.
Financial institutions, investors, and the general public have been exposed to what can well be called “ESG 1.0”, where narratives that have little in common (Environment, Social Justice and the, seemingly unconnected, Governance) are bundled into a single concept, and measured, often in loosely defined and unvalidated methodologies, with single-point metrics, for the purposes of facilitating trading (often algorithmic trading) and providing scorecard-like grades to corporates and governments.
The ESG investing strategies typically focus on one specific KPI or metric to base assessments, be this ESG ratings (“green vs. brown” portfolio theory), Pure Emissions (Weighted Average Carbon Intensity, WACI), Implied Temperature Rise (ITR), or Science Based Target Initiative alignment (SBTI).
These approaches are used, and have some merit, to build equities and bond portfolios, where the goal is to create algorithmic exclusion/inclusion principles, and trade on relatively short-term returns from the stock markets.
None of these approaches have successfully passed the smell test on actually correlating good grades/ values with positive outcomes for investors, and are now likely on the way of the Dodo, marching towards extinction and irrelevance.
The failure of these overly simplified, naïve metrics and approaches is based on poor understanding of economics, complex non-linear systems, and behavioral-based actions and reactions.
This misalignment with reality is epitomized by the “Just Stop Oil” activist approach, which focused on protesting banks and the financial system in visible and confrontational manners, with the stated goal to stop them from providing financial services to the O&G industry.
This approach failed completely to address the painfully obvious fact that such a strategy, if it were to ever succeed, would have not have resulted in the reduction of a single barrel of oil being produced and used, as the industry would simply have moved to Private Credit or other alternative sources of financing, and passed these costs onto the finished product, and thus the consumer base.
The use of unsound metrics and approaches doesn’t however mean that Climate Change is not a real problem that the world is facing, and that a transition to alternative, zero-emissions, energy sources is not an imperative (after all, oil is a finite resource which needs to be replaced at some point, if we don’t want to be sent back to a pre-industrial society once it runs out).
The warming climate, coupled at times with very bad policy decisions (such as stopping bush clearing and forest thinning in California over the last decades), has been top of the news n recent times, and is increasingly striking at the heart of the Financial Markets, via the Insurance and Reinsurance risk transmission channels.
Figure 1 below gives us as clear a clear-eyed view as possible about the increasing frequency of very severe Climate-Related disasters between 1980 and 2023 [these are CPI adjusted figures, which remove any discussion on inflationary effects as driving the exponential growth in the rolling 10-year window numbers].
Figure 1 – Billion-dollar natural disasters (CPI adjusted) in the USA from 1980-2023 (Source: National Oceanic and Atmospheric Administration/Haver Analytics)
Average # of events per year 1980-2023: 8.5
Average # of events per decade 1980-2023: 77.5
Events in 2023:
Table 1 – Aggregated Billion-Dollar disasters for the USA (1980-2023) and change at the end of the period (Source: National Oceanic and Atmospheric Administration/Haver Analytics)
2 – An aerial
of damage caused by the passage of Hurricane
in
Mexico, on October 28, 2023 - Rodrigo Oropeza / AFP / Getty
In addition to the increased damage from Acute and Chronic Physical Risk, we are also seeing shifts in long-term weather and precipitation patterns, which have impacts on agriculture that go far beyond the commonly discussed topics.
If we look at the average annual minimum temperatures as reported by the Applied Climate Information System, we detect warming for 95% of locations in the 1950-2022 timeframe. As a result of this warming, 50% of all measuring stations experienced an increased hardiness zone shift in the observation period (i.e. this means that it’s as if the and had moved south).
The historical measured data shows how arable land is quickly moving northward, shifting the wheat belt into higher and higher latitudes. Longrunning projections, based on current pace of around 160 miles per decade, predict it could go from about 55 degrees north (the current limit) to around 65 degrees North by 2050 (the latitude of Anchorage, Alaska), showcasing an example of Climate-driven investment opportunity.
These changes in climate are ongoing, unstoppable in the short to medium term, and independent of what administration is in power and what policies are put into place.
The picture, however, is not all doom and gloom, as change is also a major driver of opportunity, and, for the savvy investor, there is no shortage of profitable, climate-driven investment theses.
3 - Of the 10
Enter Transition Finance, exit ESG.
Whereas ESG has a primary focus on achieving specific goals, and a secondary one on turning a profit (and is, therefore, more suitable for philanthropy than it is for investing), Transition Finance is primarily about solid business models, with clear business cases driven by real-world cause and effect relationships.
This reversal of priorities means that profitability, scalability and soundness come first, and the positive effects for climate and the environment come as a result of the response to these fundamental drivers.
Definition of Transition Finance
While ESG pushed investors into piling on into similar investments, often with companies and sectors that had already transitioned to low or net-zero emissions (i.e. wind, solar, EVs, etc…), Transition Finance has a much broader spectrum, and doesn’t apply any of the exclusionary rules which have plagued ESG since it’s inception, and are the root cause of most of the controversy that has characterized this investment methodology over time.
“All the financial activities, including Investment, Financing, Insurance and Financial products and services, that will be required as a result of the global macroeconomic system adapting to a transition from the current carbon-intensive economy to a net-zero, or carbon-negative end state and a warmer world”
Source: “Principles of Transition Finance Investing – Finding Alpha in a World Adapting to Climate Change” –Wiley [publication date Q3-2025]
Transition Finance is a pragmatic, ideologyneutral, approach that is based on understanding the changes that the world and the economy is going through as a result of climate change, using appropriate modeling techniques which address and expand upon the high complexity and interconnectedness of the nexus of the natural and economic worlds, and deliver investment opportunities that are both Adaptation-centered as well as Mitigation-centered, but always rooted in solid business models.
This includes a material focus on “brown-togreen” plays, where investments are made into “dirty” companies or assets which are on a trajectory to transitioning into “clean” ones (for example, an Oil and Gas company that is diversifying into Geothermal energy by leveraging the technology it already uses for fracking drilling).
Additionally, it also includes a large set of other investments that leverage the effects of the change in climate, to identify growth areas (as an
example, HVAC companies and Improved Energy Efficiency in the built environment, which are both going to grow significantly as the temperatures rise).
The world is facing an unprecedented challenge, and a parallel industrial revolution, which can, and will, make many investors and entrepreneurs into billionaires in the coming years and decades, all while moving the needle in the right direction for the planet and the species that inhabit it (which is likely a first in history).
Those who recognize this challenge, approach it with the right models and tools, and step in at the right time, will reap the benefits, while the ones who don’t will be repeating the errors of investors in the early 20th century who stuck to horse-drawn buggies while the world was moving on to cars and trucks.
Figure
view
Otis
Acapulco,
Figure
million square miles (26 million square kilometers) of northern vegetated lands, 34 to 41 percent showed increases in plant growth (green and blue), over 1983-2013. Credit: NASA’s Goddard Space Flight Center Scientific Visualization Studio
Measuring Climate Impact Amid Unproven Technologies and Unpredictable Event Risk
Reena V. Mithal is the founder and Managing Partner at Sankhya Capital LLC, investing in and working closely with small enterprises in skill development, financial inclusion and healthcare in India and the US. Previously, she spent more than two decades working in global financial markets and investment research. She was also part of US-based Emerging Markets research teams at Putnam Investments, Deutsche Bank and Lehman Brothers.
Climate tech investment is having a moment of reckoning.
After a strong run in 2022 and 2023, global climate tech equity investment reported by BloombergNEF (BNEF) fell by 40% in 2024 – from $84 billion to $51 billion.
The decline comes amidst a positive outlook for overall energy transition finance, which increased to more than $2 trillion globally.
With venture funding headed for AI at the expense of companies focusing on decarbonization, and even within the climate tech space, BNEF pointed out that funding for Energy startups surpassed investment in electric vehicles and batteries as demand for AI pushes investors to focus on technologies that can power data centers with lower emissions.
DeepSeek’s recent domination of headlines based on its announcement of lower-energy usage relative to OpenAI – and the resulting flurry of market activity – is a signal of what lies ahead.
And, President Trump’s announcement of an “energy emergency” endorsing more drilling to support new data centers, reinforces the bid for energy demand, albeit from the opposite end of the emissions spectrum. Despite the US administration’s support for fossil fuels, there is still a strong focus on energy transition, underlying the need for frameworks to analyze investment returns on a risk-adjusted basis.
The definition of Climate Tech – renewable energy, nuclear power, green hydrogen, electric vehicles and batteries, industrial decarbonization including green cement and steel, AFOLU (agriculture, forestry and land use), carbon removal and DAC (direct air capture) – will continue to evolve as the sector matures.
However, unproven technologies come with high information asymmetries and little transparency, exacerbated by the reality that there is no standardized methodology to estimate ROI or calibrate risk.
Climate risk metrics are characterized within carbon accounting frameworks measuring an existing company’s Scope 1, 2 and 3 emissions, and Life Cycle Analysis – both of which are inadequate for start-ups operating in nascent markets.
The World Bank’s Climate Impact Measurement Report discusses Global, Regional, Country-level and Projectlevel factors, but while it presents a comprehensive discussion of inputs, it is difficult to use in its current form.
For a tool to be usable by market participants, it needs to answer the following questions:
• What is the project/company’s expected returns over a specific time period?
• Can the returns be adjusted for risk and how?
• How will the investment manager compare expected risk-adjusted returns across projects, portfolios and over time?
This is a tough ask in the Climate Tech space, given the technological uncertainty and diversity of sectors, countries and markets.
Allocation of capital to a green hydrogen project in India vs. a methane reduction enterprise in Kenya and a DAC company in Poland – all of which are pre-revenue – seems impossible, even for funds accustomed to operating globally.
Investing in AI is potentially a lot simpler even as a range of AI models touting faster and cheaper processing ability continue to emerge.
Expected returns for electric vehicles battery makers or solar energy producers can be compared across regions, but while funds may have expertise in one or more sub-sectors, disparate opportunities and nascent technologies cannot be ignored.
TPG Rise Climate, a private equity fund, was set up by TPG in 2021 under its impact investing platform, TPG Rise, which was founded in 2016.
With more than $7 billion under management, TPG Rise Climate declared that it was going to invest globally in Clean Electrons (energy transition and green mobility), Clean Molecules (sustainable fuels and sustainable molecules), and Negative Emissions (carbon solutions).
With a mandate this extensive, a celebrity-infused board including Bono and Richard Branson and a highprofile management team led by Executive Chairman and former Treasury Secretary Hank Paulson, there has been no dearth of pipeline or capital.
Social and environmental impact assessment has historically been evaluated using one-off approaches based on an understanding of the investment opportunity, derived from instinct and/or experience.
TPG Rise had already, in partnership with Bridgespan Social Impact, created the Impact Multiple of Money (IMM), a methodology using a six-stage approach that estimates the financial value of social and environmental good likely to arise from each dollar invested.
The IMM is forward Looking, requires impact projections and is multidimensional: it is not simply about the number of people affected but also the level of change.
It is not a precise measure but enables comparisons across companies and sectors and there is a minimum IMM threshold of $2.5 for every $1 invested, below which an investment will not occur.
TPG Rise Climate, took the IMM a step further. In 2019, TPG set up Y Analytics, a wholly-owned public benefit corporation focused on data-driven decision-making related to the environmental and social impacts of deployed capital.
Guided by an independent advisory board, Y Analytics provides research and investment insights that guides TPG’s capital allocation.
Under the umbrella of climate mitigation strategies (although adaptation and resilience could also be applied in some instances), TPG Rise Climate’s fund managers declared that:
“Evidence-based research and data will drive investment decision making and guide TPG Rise Climate in constructing a portfolio of companies that can enable carbon aversion in a quantifiable way.
“TPG Rise Climate will utilize Y Analytics’ methodologies, including Carbon Yield – a decision tool that leverages scientific, health, economic, and social science research – to estimate the tons of carbon dioxide equivalent emissions avoided per dollar invested.”
Carbon Yield estimates the additional, differentiated, net emissions reduction attributable to a project or venture.
It translates a company’s activities and outcomes into “impact pathways” where each pathway “connects how a business activity materially benefits or harms people and the planet.”
The Carbon Yield = (GHG Reduction Impact x Fund Stake)/Capital Invested
Y Analytics defines the GHG Reduction Impact as follows: “Each pathway is defined by its breadth, depth, and an adjustment factor based on the uncertainty of impact.”
GHG Reduction Impact = Breadth x Depth x Duration x Risk Adjustment
Carbon Yield incorporates the core principle of Additionality and lays out a process to assess it within an industry, target market and geographic framework.
Estimating Additionality is perhaps the most challenging component of estimating impact and returns from a Climate tech investment.
The Integrity Council for the Voluntary Carbon Market has established protocols evaluating additionality for various carbon credits, and while elements of these methodologies are useful, investors’ insights embodied in proprietary metrics from prior experience and publicly available data are crucial.
Y Analytics has used TPG’s extensive investment portfolio to build a database with parameters quantifying additionality.
The Carbon Yield is a starting point. It might end up evolving into a performance indicator that sets the standard for ROI in the Climate Tech space. Or it could remain one of numerous measures – with some transparency that permits calibration within the context of an investor’s database.
As of now, funds continue to use different metrics and very few are publicly available, impeding progress towards standardization.
For Carbon Tech investing to become a mainstream asset class, industry standards for risk and return analysis are essential and the Carbon Yield checks a lot of challenging boxes.
From Y Analytics: GHG Reduction Impact = Breadth x Depth x Duration x Risk Adjustment
Breadth – i.e., how much of the product is produced or how many people the service reaches, e .g. how many MW of power generated by a solar energy project
Depth – i.e., the effect size per unit of output or the net GHG emissions reductions enabled by a company relative to emissions generated by displaced products or the “counterfactual”. To achieve net emissions the company’s own emissions are deducted from the emissions averted
Longevity of impact – based on how asset-heavy a deal is, e.g. a 30-year life for wind turbines
Risk adjustment of returns – by a factor between 0 and 100% calibrated based on the uncertainty of impact. The rubric lays down details for different impact categories and specifies conditions for a 0%, 10% and 20% discount rate.
Post-exit impact adjustments can be made within the discount factor calculation, including assessments of the durability of impact. In instances where there are additional non-climate related impact occurs, the IMM is calculated and combined with the Carbon Yield to achieve an overall metric to assess the potential deal.
source: yanalytics.org
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