The course has been designed specifically for financial institutions and is led the CRC’s own Dr Raffaella Calabrese, and Dr Joseph Breeden, CRC External Affiliate, CEO of Deep Future Analytics LLC, and President of the Model Risk Managers’ International Assocation.

About the Course

Participants will gain both the conceptual foundations and practical tools to assess the financial implications of climate change for credit risk. The course covers how to select and apply appropriate climate scenarios, how to integrate climate-related risks into existing credit risk frameworks, and how to evaluate the resilience of loan portfolios under severe stress conditions. It is designed to be tailored to the specific needs of individual organisations, and prospective participants are encouraged to contact the Business School to discuss collaboration opportunities.

The course is particularly well suited to credit risk modellers, senior risk managers, and financial professionals seeking to build or strengthen their organisation's capacity in this rapidly evolving area.

Learn more & register

The research behind the course

Climate Stress Testing and Climate Scenarios draws on a substantial and growing body of research on stress-testing developed by the CRC with Raffaella and Joe making meaningful contributions (please see the details below). State-of-the art stress-testing approaches developed for macroeconomic impacts have found a novel and profound application in addressing climate change issues and their estimations.

The climate applications continue a long-standing legacy of stress‑testing methodologies advanced by CRC founder, Professor Emeritus Jonathan Crook, and other CRC members and External Affiliates:

• Djeundje & Crook (2025), Incorporating behavioural and macroeconomic correlations for the prediction of bank capital for credit risk.
• Wang, Crook, Andreeva (2025), Sensitivity of model parameter estimates in stress testing the probability of default: evidence over the financial crisis.
• Bocchio, Crook &Andreeva (2023), The impact of macroeconomic scenarios on recurrent delinquency: A stress testing framework of multi-state models for mortgages.
• Djeundje & Crook (2022), Sensitivity of stress testing metrics to estimation risk, account behaviour and volatility for credit defaults.
• Wang, Crook & Andreeva (2020), Reducing estimation risk using a Bayesian posterior distribution approach: Application to stress testing mortgage loan default.
• Bellotti & Crook (2014), Reducing estimation risk using a Bayesian posterior distribution approach: Application to stress testing mortgage loan default.
• Bellotti & Crook (2013), Forecasting and stress testing credit card default using dynamic models.

By grounding learning in proven stress‑testing methodologies, the course enables participants to understand not only how climate scenarios are constructed, but also how they can be embedded in empirical models relevant for financial decision‑making through example from Raffaella’s and Joe’s work.

Dr Raffaella Calabrese's research focuses on the quantitative modelling of climate risk in lending and mortgage markets. Two recent studies are of particular relevance to the course. Her work on the impacts of extreme weather events on mortgage risks in Florida — examining how hurricane and flood exposure affects default behaviour and how those relationships evolve under projected climate change scenarios — provides a compelling empirical foundation for understanding physical climate risk at the asset level. A complementary study on climate stress testing for mortgage default probability develops methodological tools for translating macro-level climate scenarios into granular credit risk estimates, offering practitioners a direct pathway from scenario design to portfolio-level impact assessment. Raffaella also designs and delivers executive courses for the European Central Bank on Climate Stress Testing and the EU Supervisory Digital Finance Academy.

Dr Joseph Breeden's contributions bring a complementary focus on the practical dynamics of climate stress in lending. His 2023, Impacts of Drought on Loan Repayment, examines how prolonged drought conditions affect borrower repayment behaviour, drawing on empirical data to quantify a risk that is increasingly material for agricultural and regional lenders, but whose methods and findings carry wider lessons for physical risk modelling.

A second paper, co-authored with Y. Leonova and A. Bellotti, examines instabilities in the use of Cox Proportional Hazards models for loan portfolio forecasting and stress testing — a technically important contribution that speaks directly to the reliability of the modelling approaches practitioners use when assessing portfolio resilience under adverse scenarios.

A collaboration rooted in complementary expertise

The partnership between the CRC and B-CCaS represents a natural alignment of strengths. The CRC brings deep expertise in credit risk analytics, scorecard development, and financial modelling, while B-CCaS contributes specialist knowledge in climate science, sustainability strategy, and the policy dimensions of climate-related financial risk. The joint development of this course reflects the University of Edinburgh Business School's ambition to translate interdisciplinary research into professional practice.

The CRC looks forward to supporting financial institutions in building the analytical capabilities they need to navigate the risks and responsibilities that climate change presents to the credit sector.

Course presenters

Raffaella Calabrese, Professor at the University of Edinburgh Business School

Dr Calabrese works closely with financial institutions and regulators to propose analytical solutions to better measure the effects of climate change on credit risk and how to perform climate stress testing exercises. Raffaella collaborates with financial institutions, government bodies and regulators in the UK, USA, China and multiple EU countries. She provides training on Climate Stress Testing at the European Central Bank and on digital finance at the European Commission.

Joe Breeden, Chief Executive Officer at Deep Future Analytics LLC

Dr Breeden has been designing and developing risk management systems for loan portfolios since 1996. He founded Deep Future Analytics in 2011, which focuses on portfolio and loan-level forecasting solutions for pricing, account management, stress testing, CECL/IFRS9, and AI monitoring; serving banks, credit unions, and finance companies. He also serves as President of Model Risk Managers’ International Association and on the board of Upgrade. Dr Breeden earned a PhD in Physics and published over 90 academic articles, 8 patents, and 6 books.

On the 19 February 2026, CRC partnered with the Model Risk Managers International Association (MRMIA) to host a comprehensive in-person session titled Fundamentals of Model Risk, bringing together regulators, industry experts, and scholars for a full-day exploration of one of the most pressing analytical challenges facing the financial sector today.

Why Model Risk matters

Models are central to decision-making across finance, analytics, and research, yet they are not infallible. Beyond routine testing and validation, models can embody incorrect assumptions, unstable specifications, shifting data environments, or improper application. Collectively, such vulnerabilities contribute to Model Risk, defined as the potential for loss resulting from the use of an unsound or misused model. As predictive analytics and machine learning expand in complexity and influence, a clear understanding of Model Risk is essential for robust decision-making, effective governance, and responsible innovation.

Building a strong foundation: Expert insight and practical guidance

CRC’s collaborative session engaged leading figures in model governance and quantitative risk, including:

• Dr Diederick Potgieter, Senior Technical Specialist in Capital Management at the Prudential Regulation Authority (PRA), Bank of England
• Christian Duesterberg, Risk Management Consultant with over 26 years’ experience in financial services
• Dr Alan Forrest, CRC Business Associate, MRMIA Board Member, and former senior model development and validation lead at Virgin Money UK, Royal Bank of Scotland, and Halifax Bank of Scotland
• Additional international experts in model risk and quantitative risk management

Through structured beginner sessions and an in-depth panel discussion, participants gained insight into how Model Risk manifests across modelling approaches, from classical statistical frameworks to advanced machine learning and generative AI. Indeed, the session included examples from law and engineering as well as financial services. Presentations examined how Model Risk is understood and regulated in the UK financial services sector, how seasoned practitioners identify and assess risk within model lifecycles, and how a Model Risk mindset enhances transparency, trust, and operational resilience.

Lukasz Szpruch, Professor at the School of Mathematics, the University of Edinburgh, and the Programme Director for Finance and Economics at The Alan Turing Institute, the National Institute for Data Science and AI, and Dr Maria Kalantzaki, Senior Validation Manager in Novel Financial & Non-Financial Risk at Virgin Money joined the evening session as panellists.

The featured discussion, moderated by Dr Alan Forrest, brought together regulators, academics, and industry leaders to reflect on both conceptual and practical dimensions of Model Risk. The panel session encouraged open dialogue under Chatham House rules, emphasising real-world implications and cross-sector learning.

Thought leadership that makes an impact

Events such as Introduction to Model Risk are not simply educational forums; they play a structural role in shaping how risk is understood and managed across the financial sector. By bringing regulators, industry leaders, and academics into the same room, CRC helped strengthen a shared language around Model Risk — one that moves beyond compliance toward deeper analytical accountability.

The discussion reinforced that Model Risk is not a niche technical concern, but a foundational element of modern decision-making. As modelling becomes more complex, particularly with the rise of AI and machine learning, a disciplined approach to identifying assumptions, understanding limitations, and communicating uncertainty becomes central to institutional resilience. By foregrounding these principles, the event contributed to embedding Model Risk thinking more firmly within professional practice.

Importantly, the collaboration between CRC and MRMIA demonstrated how academic insight and regulatory experience can jointly influence industry standards. Financial institutions increasingly operate in environments where model governance is both a regulatory requirement and a strategic necessity. Events like this support the cross-fertilisation of ideas and diffusion of best practice across organisations, helping practitioners adopt more structured, transparent, and defensible approaches to model development and deployment.

In doing so, CRC’s work extends beyond convening discussion - it contributes to shaping expectations, strengthening governance cultures, and supporting more robust, trustworthy analytical systems across the market.

Looking ahead

CRC remains dedicated to advancing research and practice at the intersection of credit risk, analytics, and financial services. Through events like Fundamentals of Model Risk and our ongoing Village Hall series Let’s Talk About, the CRC is proud to serve as a neutral hub for open and critical discussions.

The Credit Research Centre extends our heartfelt gratitude to MRMIA for sponsoring this event.

• MRMIA

Titled Fundamentals of Model Risk, the event examined how models - from simple regressions to advanced machine learning and generative AI systems - can fail, and how such failures translate into measurable risk. Model Risk, defined as the potential loss caused by incorrect, inappropriate, incomplete or misused models, is increasingly recognised as both a professional discipline and a regulatory priority, particularly within financial services.

Expert perspectives from industry and regulation

The programme featured contributions from leading specialists, including:

• Dr Diederick Potgieter, Senior Technical Specialist in Capital Management at the Prudential Regulation Authority (PRA), Bank of England
• Christian Duesterberg, Risk Management Consultant with over 26 years’ experience in financial services
• Dr Alan Forrest, CRC Business Associate, MRMIA Board Member, and former senior model development and validation lead at Virgin Money UK, Royal Bank of Scotland, and Halifax Bank of Scotland
• Additional international experts in model risk and quantitative risk management

Drawing on deep experience from the banking sector, speakers addressed how Model Risk manifests in practice, how it is regulated in UK financial services, and what benefits a strong Model Risk mindset can bring to modelling and decision-making.

Developing the Model Risk mindset

The workshop sessions introduced participants to the structured thinking behind Model Risk management, and its importance across industries. Discussions covered:

• The Model Risk mindset and the model lifecycle
• Case studies from financial services, engineering & law
• Model Risk as a form of risk management
• Regulatory oversight by the Bank of England
• The costs and benefits of embedding Model Risk discipline

Participants were encouraged to reflect critically on their own modelling practices and consider how systematic identification, assessment, and mitigation of model weaknesses can improve both analytical rigour and business outcomes.

Panel discussion and industry dialogue

The evening panel session brought together regulators, academics, and industry leaders for a candid discussion under Chatham House rules. Panellists included:

• Diederick Potgieter, (Bank of England PRA)
• Christian Duesterberg, (Independent Consultant)
• Lukasz Szpruch, (The Alan Turing Institute)
• Maria Kalantzaki, (Virgin Money UK / Nationwide)

Moderated by Dr Alan Forrest, the panel explored the practical implications of Model Risk governance, the challenges of implementation across institutions, and the future direction of regulation and professional practice.

The day concluded with a drinks reception, providing attendees the opportunity to continue discussions and build connections across academia, industry, and regulatory communities.

Strengthening the model risk community

The event demonstrated CRC’s continued commitment to fostering dialogue between research and professional practice. By uniting academic insight with regulatory and industry experience, CRC and MRMIA highlighted how a mature Model Risk framework not only protects organisations but strengthens trust, transparency, and decision-making quality across sectors.

The Credit Research Centre extends our heartfelt gratitude to MRMIA for sponsoring this event.

• MRMIA

This volume aims to bring together cutting-edge research and practical insights that reflect the evolving challenges and opportunities in credit risk analytics. It will showcase methodological advances, real-world applications, and forward-looking perspectives from both academic researchers and industry practitioners.

CRC strongly encourages contributors to the 19th Credit Scoring and Credit Control Conference, including both academic and practitioner presenters, to submit a chapter based on their conference work. High-quality submissions not presented at the conference will also be considered; submissions falling outside the conference themes may be desk-rejected.

The submission deadline is 31 March 2026.

Full details on the scope of the volume, submission criteria, and the submission process

CRC looks forward to receiving contributions that help advance research, practice, and dialogue in credit risk management and analytics.

The event featured expert contributions from:

• Professor Michael Rovatsos, Dean of Research and Innovation at the College of Science and Engineering and Professor of Artificial Intelligence at the School of Informatics, University of Edinburgh
• Dr Maria Kalantzaki, Senior Validation Manager in Novel Financial & Non-Financial Risk at Virgin Money
• Roberto Wolf, Principal of AI Innovation at Optima Partners
• Professor Alexandra Birch, Chair of Multilingual Natural Language Processing in the Institute for Language, Cognition and Computation (ILCC) at the School of Informatics, University of Edinburgh, and co-founder and Chief Scientist of Aveni.ai
• Soner Candan, Lead Data & AI Scientist at Lloyds Banking Group

The event was moderated by Professor Galina Andreeva, Director of the Credit Research Centre.

We are pleased to share slides from a selection of speakers with our global community:

We look forward to welcoming participants to upcoming CRC events.