AI/ML and sensitive production data in fintech and healthcare? Where is the data going? Can it be made sense of? [D]

A software engineer at a large fintech company raises concerns about integrating AI/ML systems with sensitive production data in highly regulated industries like fintech and healthcare. The engineer questions how to design architectures to prevent sensitive financial data from leaving the environment unnecessarily and how companies handle Personally Identifiable Information (PII) if data must be externalized. The core worry is the potential for historical PII to be mined or analyzed in the event of a data leak from an AI provider, especially after long-term integration.

Unlike typical discussions on AI in finance, this post directly addresses the architectural challenges of preventing sensitive production data and PII from leaving regulated environments.