Generative AI for Fintech: Customer Service, Compliance, and Developer Experience

A fintech deploys a commercial AI chatbot for customer support. Within a week, the bot quotes a fee schedule that's outdated, suggests a workaround for a frozen account that violates the fintech's compliance policy, and tells a customer their money is 'safe and insured' when the fintech's accounts don't carry FDIC insurance (the sponsor bank's do, with specific conditions). Each response sounds professional and confident. Each is wrong in a way that creates regulatory or legal risk. The chatbot was trained on the internet, not on the fintech's actual product, policies, and regulatory constraints. Generic AI doesn't know the difference.

Generative AI that works at fintechs requires grounded retrieval against the fintech's actual documents — current product terms, current fee schedules, current compliance policies, current regulatory constraints. Explicit refusal patterns for questions about FDIC insurance, account safety, and other topics that require precise legal language. Citation of sources so the support agent or customer can verify. Financial data boundaries that prevent the agent from accessing account balances, transaction history, or PII without proper authorization. And the model risk documentation that satisfies the compliance team and the auditors.