In regulated lending, LLMs handle only a fraction of the AI pipeline

A DEV Community post highlights a common misconception about AI's role in complex, regulated financial workflows. In regulated lending, large language models handle only the final prose-drafting step, while the heavier work — document ingestion, data extraction, validation, and financial calculations — must be performed by deterministic code. Financial calculations in particular cannot be delegated to LLMs, which risk silently producing rounding errors or inaccurate outputs. Canada's OSFI E-21 guideline reinforces this design constraint, requiring human ownership of risk decisions. The author argues that winning AI teams in banking are those who precisely identify the narrow slice of the problem where a language model is actually appropriate.