A process that took 2–3 weeks and produced a 40-page document is the kind of thing everyone wants to "AI-ify."
Here's what most people get wrong about it: they reach for the LLM first.
In regulated lending, the LLM is the last and smallest part of the pipeline. The hard parts are: ingesting messy documents reliably, extracting data into a canonical model, validating and cross-reconciling it, and doing the actual financial calculations - and those calculations must be done in deterministic code, never by a language model that might quietly round a number wrong.
The LLM drafts prose. Code does the math. A human owns the risk decision. That ordering isn't a limitation - under OSFI E-21 it's the only design that's allowed to exist.
The teams that win with AI in banking aren't the ones using the biggest model. They're the ones who know which 10% of the problem the model should touch.
Where have you seen an LLM used for something that should have been deterministic code?
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