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Article
Solving a Decade-Old Blind Spot in Bank Capital Models
A new dual backtesting framework developed by Krishan Kumar Sharma aims to solve a longstanding weakness in bank capital modeling by isolating scenario-driven forecasting errors from downstream model inaccuracies. The methodology could improve capital efficiency, strengthen validation practices, and reduce excessive conservatism in reserves and capital allocation across the U.S. banking sector.
May 27, 2026
Krishan Sharma, SVP, Model Risk - Regulatory Stress Testing and Capital Forecasting, Citi
Tags:
Model risk
The views and opinions expressed in this content are those of the thought leader as an individual and are not attributed to CeFPro or any other organization
- New dual backtesting
framework separates scenario-driven forecasting errors from downstream
model errors in bank capital models
- Developed by
Citigroup executive Krishan Kumar Sharma and published in the Journal of
Risk Model Validation
- Framework applies to
CCAR, CECL, IFRS 9, and ICAAP capital regimes
- Methodology may
reduce excessive reserves and capital buffers created by uncertainty
- Reported
implementation outcomes include reserve reductions of 10 – 15 percent and
capital reductions of 8 – 10 percent
- Framework aligns with
Federal Reserve SR 26-2 guidance on model validation and governance
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