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CRISK: A Market‑Based Framework for Quantifying Climate Risk in Banking

著者 Ciara McGahey,

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Effective risk management increasingly requires understanding how climate‑related factors can influence market valuations and balance‑sheet resilience. CRISK provides a transparent, market‑based framework for estimating the expected capital shortfall a bank might face under a climate stress scenario.

At the MathWorks Finance Conference, Michael Robbins (Columbia University) and Arpit Narain (MathWorks) discussed the CRISK framework, a practical, data‑driven approach to incorporate climate factors into systemic risk analysis.

What Is CRISK?

Diagram of a climate stress‑test framework showing how climate science models feed into climate economics models, which inform a disorderly transition model, and ultimately flow into financial valuation network and valuation models.
Climate stress‑test framework linking climate science, economic outputs, transition‑risk modelling, and financial valuation to assess the impact of climate scenarios.

CRISK measures the expected capital shortfall a financial institution would face if a climate‑related systemic stress event were to occur.

The framework builds on research from the Federal Reserve Bank of New York and the academic work of Hyeyoon Jung, Robert Engle, and Richard Berner, whose contributions to volatility modelling and systemic risk underpin the methodology.

CRISK introduces two key components:

  • Climate risk factors capturing transition or physical climate shocks
  • Climate beta, quantifying a bank’s sensitivity to those factors

By linking climate betas to expected capital shortfall, CRISK provides a forward‑looking perspective on potential vulnerabilities in the banking system using only publicly available data.

Why CRISK Matters for Financial Institutions

Banks and supervisors increasingly need to quantify how climate scenarios affect capital adequacy. CRISK’s appeal lies in its:

  • Transparency — relies on publicly available equity, debt, and climate factor data
  • Scalability — supports comparisons across firms and geographies
  • Interpretability — produces a single, intuitive metric: expected capital shortfall
  • Regulatory relevance — the method has already been replicated by a major Asian central bank
Diagram comparing limitations of classic risk‑assessment frameworks with CRISK solutions, showing how climate beta, dynamic measurement, and market data address historical, perceptual, and data‑reliability challenges.
Classic risk‑assessment challenges and the corresponding CRISK solutions, highlighting how climate beta, dynamic measurement, and market‑data‑based approaches overcome common limitations.
Diagram illustrating the CRISK methodology, showing how a climate‑factor shock feeds into return equations and ultimately into the CRISK capital shortfall formula
CRISK methodology: climate‑factor shocks and return equations feeding into the capital shortfall calculation.

Implementing CRISK in MATLAB

Two line charts showing CRISK values over time for major U.S. banks. The first plot compares CRISK for Citi, Wells Fargo, and Bank of America from 2000 to 2020; the second shows CRISK time series for a wider set of banks on the same date axis.
CRISK time‑series results for major U.S. banks, comparing individual institutions and a broader peer set across two decades.

The presentation highlighted how MATLAB supports a full‑stack implementation of CRISK, including estimation, scenario integration, and deployment.

Using MATLAB, institutions can:

  • Build CRISK models tailored to local regulatory requirements
  • Integrate climate factors from NGFS, national centres, or custom scenario sets
  • Run large‑scale computations efficiently across portfolios
  • Deploy models seamlessly to enterprise environments for reporting and auditability

This combination of transparency, rigor, and deployment readiness makes MATLAB a strong environment for central banks, supervisors, and large financial institutions implementing climate risk analytics.

Advancing Climate Risk Assessment

As climate‑related risks increasingly influence creditworthiness, asset valuations, and systemic resilience, CRISK enables institutions to:

  • Quantify vulnerabilities to transition and physical risks
  • Benchmark exposures across entities or jurisdictions
  • Support supervisory dialogue and stress‑testing exercises
  • Embed climate considerations directly into capital planning

CRISK represents a meaningful step toward a more data‑driven climate risk management ecosystem.

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カテゴリ: 
Climate Finance,
Econometrics,
Risk Management,
Time Series
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