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INSIGHT · GLOBAL

LLM performance degradation over time: a production risk for BFSI

Research from frontier labs shows that deployed LLMs gradually degrade in accuracy over months (model drift) due to distribution shifts, obsolete training data, and user input contamination. Economist reports on this emerging operational challenge.

WHY IT MATTERS

BFSI deployments require continuous monitoring and retraining. Static models become liabilities in compliance, underwriting, and fraud contexts. Budget for governance infrastructure as large as model training.

Source: The Economist · 2026-07-17

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LLM performance degradation over time: a production risk for BFSI — ath — AITechHive