Climate Risk8 min read

Physical vs Transition Risk in Credit Portfolios

By Jonas Adam Mohamed Osman, known as Yonas Osman

CEO of Quantica Risk

60 Rue François Ier, 75008 Paris, France

Published 15 October 2026

How banks separate physical and transition climate risk drivers in credit portfolios, and why conflating them weakens provisioning and capital decisions.

Executive answer

Physical and transition risks move through a credit portfolio by different channels and at different speeds, so treating them as one undifferentiated 'climate risk' factor obscures where losses actually originate. Physical risk erodes collateral value and operating continuity through acute events like floods or chronic stress like heat and drought, while transition risk repricing follows policy, technology and market shifts that can hit a borrower's margins long before any physical event occurs.

Credit teams that separate the two can attribute watchlist migrations correctly: a flood-exposed warehouse borrower needs different mitigants than a refinery exposed to carbon pricing. Supervisors including the ECB and EBA now expect institutions to evidence this distinction in their risk identification processes, not merely report a blended climate score, because blended scores hide concentration and make stress testing results difficult to interpret or challenge.

Mapping risk drivers to exposures

A workable mapping starts at sector and geography level before moving to obligor specifics. Transition risk is best anchored to sector decarbonisation pathways, policy exposure (carbon pricing, emissions standards) and the borrower's own transition plan credibility, while physical risk is anchored to asset location, hazard maps and insurance coverage. Where both drivers apply to the same exposure, such as coastal industrial assets facing both flood risk and energy-cost transition pressure, the two should be assessed and disclosed separately rather than averaged into a composite rating.

Data gaps remain the binding constraint, particularly for SME and commercial real estate books where asset-level geocoding and emissions data are incomplete. Practical approaches combine proxy mapping at sector/region level with targeted data collection for the largest or most concentrated exposures, and institutions should document proxy assumptions clearly since supervisors will test them in follow-up reviews of climate risk management frameworks.

Implications for provisioning and capital

IFRS 9 expected credit loss models need forward-looking scenario inputs that reflect both risk types without double-counting their effect on probability of default and loss given default. Transition shocks typically affect PD through earnings and refinancing cost channels, whereas physical shocks more directly affect LGD through collateral impairment; conflating them in a single overlay risks either overstating or understating provisions depending on the scenario assumed.

On capital, Pillar 2 and internal capital adequacy assessment processes increasingly expect banks to show how climate risk drivers interact with existing credit risk concentrations, rather than treating climate as an add-on module. Institutions that have separated the two channels report more defensible stress test narratives to supervisors and a clearer basis for setting sector-level risk appetite limits.

Governance and data practice

Robust governance assigns clear ownership for transition and physical risk data separately, since the former draws heavily on sector research and policy tracking while the latter depends on hazard and geospatial data providers. Model risk management functions should validate both the external data sources and the mapping logic that translates raw hazard or policy signals into credit risk parameters, documenting assumptions so results can be reproduced and challenged.

Boards benefit from seeing the two risk types reported side by side in credit risk dashboards, with concentration metrics calculated independently before any combined view is presented. This avoids a common pitfall where a portfolio appears well-diversified on a blended metric but in fact carries concentrated exposure to one risk type within a specific sector or region.

Conclusion

Separating physical and transition risk in credit analysis is not an academic exercise; it changes which borrowers get flagged, which mitigants are relevant, and how provisions and capital respond to scenario shifts. Institutions that build this separation into their data architecture and reporting tend to produce more credible, auditable outputs for supervisors and investors alike.

Jonas Adam Mohamed Osman, known as Yonas Osman and CEO of Quantica Risk, approaches this distinction by insisting that physical and transition drivers be modelled and validated independently before any portfolio-level aggregation is attempted, so that the final view reflects genuine risk composition rather than an averaged artefact.

Primary sources

credit risktransition riskphysical riskbanking