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Article
Why Reading AI Training Papers Matters (And When It Doesn’t)
As generative AI models become embedded in financial services, risk professionals are inundated with technical training papers and model documentation. This article explores when reading AI research genuinely strengthens model validation - and when behavioural testing, governance controls and outcome analysis matter more than architectural detail.
Feb 25, 2026
Chandrakant Maheshwari, First Vice President - Model Validation Lead, Flagstar Bank
Tags:
Model risk
Operational and Non Financial Risk
AI and Technology (including Fintech)
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
• AI research papers are increasingly complex and
technical.
• Not all validation teams need deep architectural detail.
• Behavioural testing often reveals more than theory.
• Governance and reproducibility are critical controls.
• Marketing claims must be separated from measurable performance.
• Model risk frameworks must adapt to GenAI.
• Accountability remains with the institution, not the model.
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