In Finance, AI Fluency Is Not the Same Thing as Trust
Generative AI entered financial services through the most attractive door possible: productivity. It drafts faster, summarizes faster, searches faster, classifies faster, and removes friction from workflows that once required significant manual effort. That value is real, which is why so many executive conversations still begin with the same question: how much time will this save?
In regulated finance, however, that is no longer the most important question. The better question is whether an institution can trust the output enough to let it influence a real decision and still explain that decision later under review. That is a much higher bar. It requires more than a good answer on a screen. It requires evidence, controls, ownership, and a reconstructable record of what happened at the time the decision was made.
That is why the central problem is not simply that models can be wrong. By now, most teams understand that models...
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