Key takeaways
Data governance and human oversight lead to AI success
Glenn notes that although financial services has traditionally been a conservative industry, it’s now eagerly adopting AI in back-office functions to reduce costs and boost efficiency, driven by board-level directives.
He emphasizes that successful AI implementation hinges on robust data governance and high-quality data. Despite the compliance challenges posed by AI’s “black box” nature, he suggests firms accept some risk but enforce stringent validation processes. Crucially, he advocates keeping humans in the loop to oversee AI outputs, ensuring accuracy and compliance.
Community banks use AI to level the playing field against big banks
Ravi points out that giants like Chase employ over 900 data scientists, a luxury smaller banks can’t afford.
Abrigo’s AI-driven software helps these institutions offer services like automated loan origination for commercial, agricultural, and construction loans, as well as SMB lending. On the back end, Abrigo provides tools for compliance in areas like anti-money laundering, asset liability …