Climate-related physical and transition risks are becoming increasingly tangible for banks in Asia Pacific (APAC), as expectations around data and modelling grow more detailed and demanding.
Risk and lending teams are now required to assess additional factors tied to resilience, capital adequacy, and regulatory requirements. However, these efforts are often hindered by incomplete and inconsistent data, making it harder to gauge uncertainty.
Moody’s Ratings noted in a January 2026 report that banks lack the level of detail and consistency needed for reliable risk modelling. The challenge is not only missing data, but also information that is not standardised, comprehensive, or sufficiently relevant.
For instance, many banks still rely on non-standardised address data, which requires manual processing before it can be converted into usable geographic coordinates.
Uncertainty also persists in forward-looking analysis. Many models depend on central estimates, such as average annual losses, which can obscure the potential impact of more extreme scenarios. Overreliance on these averages may cause banks to underestimate “tail risks” that could significantly affect capital and earnings.
To address these gaps, Moody’s recommends expanding analytical approaches, including the use of stochastic modelling. This method simulates thousands of possible scenarios, helping banks better understand the range of potential outcomes and assess the probability of severe events.
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