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Article
The Failure Syndrome – How Models Fail When Data Fails
Financial institutions must rethink how they build and govern valuation models as data becomes scarcer, markets more volatile, and AI more capable. A senior treasury executive argued that artificial intelligence should strengthen human judgment rather than replace it, while robust governance remains essential to maintaining confidence in model outputs.
Jul 08, 2026
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
- Poor quality and
limited market data remain the greatest challenge for valuation models
- AI can improve model
performance through better data analysis and synthetic data generation
- Greater predictive
accuracy must be balanced against explainability and governance
- Human judgment should
remain central to valuation decisions and model overrides
- Strong documentation
and evidence are essential when challenging model outputs
- Continuous governance
helps maintain confidence in valuation frameworks as markets evolve
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