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Article
Stress Testing Breaks When Models Pretend to Know
Tanveer Bhatti argues that modern stress testing must be designed to fail safely, not flawlessly. As systemic risks grow more nonlinear and AI accelerates model complexity, institutions must combine advanced analytics with governance discipline, uncertainty bounds, and decision integrity to remain credible under extreme pressure.
Mar 02, 2026
Tanveer Bhatti, Early Stage Fintech Investor, Former Group Head of Model Risk, Revolut
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
- Models often fail at
the moment they are most needed
- Stress frameworks
must be designed to fail safely
- Cascading effects
require network and action based modeling
- Plausible scenarios
depend on coherent causal mechanics
- AI accelerates scale
but amplifies spurious correlations
- Model risk management
shifting toward decision integrity engineering
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