APAC banks face 'tail risk' as climate data gaps undermine risk modeling

Banks must adopt simulation-based modeling to quantify the full spectrum of potential losses.

Physical and transition risks are no longer abstract concepts for banks in Asia Pacific (APAC), with data and modelling requirements becoming more specific and stringent.

Banks’ risk and lending teams now need to evaluate new factors related to resilience, capital, and regulation. But they often face incomplete data, making it difficult to understand uncertainty.

“Banks simply don’t have the level of detail or consistency in data needed for accurate risk modeling,” Moody’s Ratings wrote in a report published in January 2026.

It’s not just about missing information, but also information that isn’t standardised, comprehensive, or relevant, the ratings agency warned.

“A common example is location data. Many banks still work from non-standardized addresses that require manual clean-up and conversion into coordinates,” it said.

There also remains uncertainty when it comes to forward looking analysis. Many models rely on central estimates, such as average annual loss. These can mask the severity of potential severe outcomes, Moody’s wrote in the report.

“When banks rely too heavily on these averages, they risk overlooking “tail risk” that could materially affect capital and earnings,” it said.

Banks are advised to broaden their analytical toolkit, such as stochastic modeling. Stochastic modeling runs thousands of plausible event simulations, which can reveal the full distribution of potential outcomes and quantify the likelihood of severe impacts, Moody’s said.