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Regulators like the ECB and PRA are aggressively cracking down on black-box climate models that hide their methodology. The only path to compliance and sustained profitability is scientifically credible, 90-meter resolution data paired with rigorous, fully transparent Model Risk Management (MRM).
Evolving Regulatory Expectations
The regulatory landscape surrounding climate risk is maturing rapidly. Supervisory bodies, most notably the European Central Bank (ECB) and the UK Prudential Regulation Authority (PRA), have moved beyond requesting general sustainability disclosures. There is now an explicit expectation that banks must integrate severe climate scenarios directly into their internal supervisory and stress-testing frameworks. Specifically, the ECB requires institutions to demonstrate a definitive assessment of the "impact of physical risk on the value of collateral".
This shift requires a fundamentally more rigorous approach to climate data management.
The Limitations of Opaque Modeling
In an effort to meet these accelerating mandates, some institutions have licensed third-party climate models that operate as "black boxes". While these models provide high-level risk scores, the underlying scientific logic, hazard assumptions, and specific evidence sources are often proprietary and opaque.
From a regulatory perspective, this lack of transparency presents a significant challenge. Regulators are increasingly demanding line-of-sight into the methodology behind risk assessments. If a bank's internal validation committee cannot fully interrogate the mathematics and scientific assumptions driving a climate risk score, it becomes difficult to justify that score during an official audit. Utilizing models with hidden methodologies introduces a layer of corporate and regulatory liability that most risk departments are no longer willing to accept.
The Role of Model Risk Management (MRM)
Consequently, Model Risk Management (MRM) has become the critical proving ground for climate data integration. Successful integration requires breaking down internal data silos; physical risk data must serve as a consistent, single source of truth across credit risk assessments, asset valuations, and strategic business planning.
Meeting these MRM standards requires deeply transparent, scientifically credible data that can withstand independent and academic scrutiny. Jupiter addresses this industry need by providing "everything but the IP” to model validation teams evaluating Jupiter models. Through the Jupiter MRM Accelerator, client institutions are provided with comprehensive technical documentation – exceeding 500 pages – and over 60 pre-developed validation tests.
By providing quantitative analysts with direct access to standardized validation procedures, the underlying science and the scientists who produce them both, model validation teams can verify methodologies efficiently, significantly reducing the time required to move from assessment to production. Teams vetting Jupiter models with Jupiter MRM Accelerator saved over 77% in resource costs alone.
The Granularity Mandate and Collateral Value
However, transparency is only one part of the regulatory equation; spatial accuracy is equally critical. When addressing the ECB's requirement to understand the impact of physical risk on the value of collateral, 90m-grid hyper-granularity becomes an operational necessity.
It is exceedingly difficult to determine the precise value-at-risk for a specific collateralized warehouse or a retail branch using a standard 10km grid. A 10km grid averages the hazard exposure across a broad geographic area, blending the risk profiles of assets situated on high ground with those located in adjacent flood plains. Jupiter’s minimum 90m resolution bridges the gap between general hazard intensity and specific financial modeling. We will shortly be implementing a 30m layer for flood in all major markets. It provides the exactitude required to demonstrate to a regulator precisely which assets are exposed, the projected severity of the event, the estimated direct damage costs, and the implications for the asset's residual life. By pairing this 90m-grid granularity with robust, audit-ready transparency, banks can confidently defend their climate-adjusted valuations to both shareholders and regulatory bodies.
Final Thought: A defensible climate strategy requires the ability to explain exactly how risk conclusions are drawn. By prioritizing 90m-grid accuracy and demanding comprehensive MRM transparency, financial institutions can meet current regulatory expectations and build a stronger foundation for long-term risk management.
Rohan Hamden is the Director at Global Banking at Jupiter Intelligence.
Additional information
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