AI in Finance: From Decision Support to Decision Infrastructure
Inside the largest banks and asset managers, AI is migrating out of analyst toolkits and into the underlying systems on which credit, trading and risk decisions are made.
The headline AI deployments inside large financial institutions — research summarisation, document processing, customer interaction — are the visible surface. The more consequential work is happening underneath, in the systems on which credit decisions, trading risk and portfolio construction are actually made.
What changes when AI moves from decision support to decision infrastructure is the locus of accountability. A model that informs a human analyst is governed by that analyst's judgement. A model that participates in the underwriting workflow is governed by model risk management, validation, and the institution's regulatory posture. The bar is higher, the deployment timeline is longer, and the operating leverage when it works is correspondingly larger.
The institutions that move fastest at this layer are not the ones with the most public AI narratives. They are the ones whose model risk frameworks were already mature before the current cycle began.
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