Avoiding AI Mistakes In The Banking World

InnovationAIAvoiding AI Mistakes In The Banking WorldByJohn Werner,Contributor.Forbes contributors publish independent expert analyses and insights. I am an MIT Senior Fellow & Lecturer, 5x-founder & VC investing in AIFollow AuthorJun 14, 2026, 10:41am EDTsmartphones with digital technology for online banking, mobile banking, shopping, payments, bank accounts, transfers, credit cards, financial management, and global online business.gettyAs businesses of all kinds are integrating automation tools into coding, into writing, and yes, into transactions, there’s some amount of concern about accuracy and oversight. I say “some amount of concern,” but I think it’s safe to say it’s a rather large amount.In finance and elsewhere, LLMs, chatbots and various kinds of neural nets do make mistakes. But why? Aren’t they computers? How can they make mistakes? And what happens when they make mistakes in the real world?Answering the second question first, I found this article by Asha Kiran Kumar at Analytics Insight, where the writer supplies these basic points on AI mistakes and the consequences. I’m including these verbatim because they are so good:When machine-driven decisions cause harm, blame moves through the chain of developers, companies, managers, and leaders who shaped and released the system.Governments are building strict rules for high-risk uses, demanding transparency, oversight, and clear documentation to prove systems were deployed responsibly.From insurers to executives, everyone involved in building or using these systems will carry a piece of the accountability as autonomy grows and risks rise. To recap:Any process is like an organism, with its own touch points. Regulators are trying to stay ahead of AI problems. And those who use AI must wrestle with the liabilities.Thoughts from a Financial AI Panel in BostonIn the Imagination in Action conference in Boston this past April, I heard Nina Gregory, formerly of NPR, interview a panel on financial AI, and wh...