Climate Stress Tests Are Broken - Banks Must Build Their Own

Financial institutions are learning a hard truth about climate risk – models designed for scientific assessment rarely work as plug-and-play tools for balance-sheet decisions. 

Central banking officials acknowledged that early scenario vintages lacked short-term adversity and sector granularity, prompting a pivot to more finance-ready narratives that include policy shocks, market stress and disruptive physical events with impacts on credit spreads and default probabilities. 

Speaking at a recent CeFPro conference on climate risk, the head of climate economics at a central European bank described the agenda bluntly.

For him, there is a clear need for more granular sector pathways using input-output tables, tougher damage functions to capture nonlinear losses, and dedicated short-term scenarios that look and feel like macro stress tests rather than academic pathways. 

The aim, he said, is consistency of data and methods – and integration of climate alongside other risks in standard supervisory exercises. 

Banks are not waiting. In the same session, a managing director and head of risk analytics outlined a two-track build – an agent-based macro model calibrated to internal assumptions, and a rapid “SSP – RCP” pathway method that derives deflationary effects from temperature and inflationary effects from carbon prices, then propagates them through sectors to credit. 

The driver is ownership and explainability, not black-box dependencies. 

A head of climate risk analytics added that qualitative scenario narratives are also proving decisive: decade-long storylines that translate physical hazards and transition uncertainty into concrete strategic choices for sectors and portfolios. 

Those narratives, he claims, underpin internal macro scenarios, credit discussions and climate scorecards – but still need quantitative bridges to external frameworks to flow into capital and pricing.