AI That Compounds: Why Financial Institutions Need a Governed Learning Foundation, Not More Point Solutions
Year: 2026
Type: preprint
Abstract: Most AI in financial services arrives as point solutions sold on efficiency. They do not compound, they copy institution data and split governance across vendors, and they leave the institution renting intelligence it does not own. This white paper argues for a single shared, governed learning foundation: mapped data from live core connections, three model layers (a large quantitative model, a banking behaviour model and a language model), one gateway and one write-once audit trail, with a governed loop in which outcomes improve each institution's own models. It describes how SmarterFI, connected to 13 banking cores today, was built on this foundation, how it fits current model-risk and third-party guidance, and offers a five-step roadmap and board questions for institutions getting started.
Author: Donahue, James (Jamie)
Language: English
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7225610971