Climate risk modelling in the financial sector: Understanding, assessing, and integrating risks

Climate risk modelling: What it is and why it matters

The global financial sector is increasingly tasked with understanding and addressing climate risks. These risks fall into two interrelated categories:

• Physical risks reflect the direct impacts of climate change, such as extreme weather events, rising sea levels, and prolonged droughts. These events can devastate infrastructure, disrupt supply chains, and weaken economic stability. For instance, floods in key agricultural regions may lead to defaults on farm-related loans, undermining credit quality;
• Transition risks arise from the economic and regulatory shifts required to transition to a low-carbon economy. New regulations, like carbon taxes or stricter emission standards, can devalue high-emission assets, creating ripple effects in portfolios and markets. For example, banks heavily exposed to coal mining projects may face declining loan performance due to policy-driven closures.

While distinct, these risks often converge, demanding a nuanced understanding of their systemic and localised effects.

The drivers of climate risk modelling

The urgent focus on climate risk modelling stems from several factors. We see the most important among them being regulatory and compliance push, investors' expectations, and long-term strategic planning.

Global and regional regulatory bodies are increasingly prescriptive about the need for climate risk integration. In Europe, the Capital Requirements Regulation (CRR) and Capital Requirements Directive (CRD) mandate that banks include climate scenarios in stress testing and incorporate climate-adjusted capital adequacy measures. Insurers face similar scrutiny under EIOPA’s Own Risk and Solvency Assessment (ORSA) framework, which calls for multi-horizon risk assessments reflecting both physical and transition risks. Meanwhile, the Corporate Sustainability Reporting Directive (CSRD) enforces transparency in how institutions measure and disclose climate impacts, complemented by the European Sustainability Reporting Standards (ESRS).

Investors are increasingly aligning their expectations with sustainability benchmarks, such as Green Asset Ratios (GAR) and decarbonisation goals. This trend is driving institutions to quantify their climate risks rigorously, ensuring alignment with both regulatory demands and market pressures.
Beyond compliance, climate risk modelling provides a competitive edge. Institutions that effectively incorporate climate resilience into their operations can identify new opportunities, such as financing renewable energy or climate-resilient infrastructure, while mitigating long-term financial vulnerabilities.

The framework for climate risk modelling

Modelling climate risk requires a structured approach that integrates robust methodologies with practical applications. The cornerstone of effective climate risk modelling lies in climate scenario analysis. This involves simulating financial outcomes under various climate pathways, ranging from optimistic (limiting warming to 1.5°C) to pessimistic (business-as-usual emissions leading to >3°C warming). Physical risks are modelled using tools like catastrophe models, which estimate damages based on the intensity and likelihood of extreme weather events. Transition risks are assessed by examining regulatory changes, carbon pricing, and shifts in market demand for high-emission industries.

Majority of experts agree on the following important steps to conduct the quantitative climate risk assessment.

1. Set objectives: Institutions must define clear goals, whether it’s to enhance resilience, comply with regulations, preparing stress tests or align with sustainability strategies;
2. Data collection and scenario analysis: Reliable climate and financial data underpin all modelling efforts. This includes emissions data, geographic exposure, sector-specific vulnerabilities and selection of relevant climate scenarios and tools. Many players of the financial market seeing the process of setting up the tailored climate scenarios as one of the biggest challenges.
3. Integration into financial models: Incorporate climate variables into credit, market, and operational risk models. For example, adjusting Probability of Default (PD) calculations to account for carbon pricing impacts on borrowers’ cash flows.
4. Validation and review: Continually refine assumptions and update models to reflect evolving data and insights.

Sector-specific applications

• Banks: Banks are leveraging climate-adjusted credit scoring to account for borrower vulnerability to climate shocks. For example, drought impacts on agricultural loans or the increased risk of default for industries heavily reliant on fossil fuels are integrated into their credit assessment models. Additionally, banks are conducting scenario analyses to evaluate the resilience of their portfolios under various climate pathways. Stress testing, mandated by regulations such as the CRR, includes modelling the financial impacts of regulatory shifts like carbon pricing or abrupt policy changes that could devalue high-emission assets;
• Insurance companies: For insurers, climate risk modelling goes beyond natural catastrophe (NatCat) modelling to include detailed scenario analyses for the ORSA. Insurers use these analyses to evaluate the long-term viability of their business models under various climate scenarios. For example, they assess solvency implications under extreme weather events or transition risks from regulatory changes. Furthermore, feasibility studies for developing new insurance products—such as parametric insurance for climate-sensitive regions or policies incentivising sustainable practices—are increasingly being informed by advanced climate risk models;
• Asset Managers: Asset managers apply portfolio-level analyses to evaluate exposure to high-carbon sectors. They also use climate risk models to identify stranded asset risks, such as investments in coal or oil-dependent industries that may lose value due to the energy transition. Additionally, scenario analyses help forecast long-term portfolio performance under different climate pathways. Tools like transition risk heatmaps or sectoral exposure dashboards enable asset managers to make informed decisions on divestment strategies, green investment opportunities, and overall portfolio decarbonisation plans.

Integrating climate risks into broader frameworks

Climate risk integration is not a siloed activity. It should permeate an institution’s overarching risk management and governance systems. The current guidelines on how to integrate climate risk in the overall risk management and assessment process are very much aligned across the financial sector. For example, CRR requires banks to embed climate risks into their capital frameworks, ensuring adequate buffers against climate-related losses. This involves simulating the financial impacts of climate shocks on credit risk metrics, such as Loss Given Default (LGD) and Exposure At Default (EAD), and adjusting capital ratios accordingly. EIOPA emphasises a tailored approach, urging insurers to adapt global scenarios to their specific portfolios and geographic exposures for the ORSA reporting. Insurers are expected to document the selection of scenarios comprehensively, providing transparency in how climate risks influence solvency. All the regulatory bodies enforce the importance of the cross-functional governance framework where climate risk management should be overseen by dedicated committees, ensuring alignment between sustainability, risk, and strategy teams. Advanced tools, such as AI-driven models and geospatial climate data, enable precise scenario analysis and real-time monitoring.