AI and Financial Data: What Should Never Leave Your Own Systems

Every day, financial professionals are handed AI tools that promise speed, insight, and efficiency. But the same models that can draft a risk memo or summarise a portfolio report can also—if fed the wrong raw data—expose client positions, trading strategies, or personally identifiable information to servers beyond your control. This book is a practitioner’s guide to drawing that hard boundary: knowing exactly which financial datasets, by regulation and by duty, must never touch an external AI. Written for compliance officers, analysts, portfolio managers, and technology leads who already understand their professional obligations, it walks through concrete perimeter controls, safe prompt practices, local versus cloud deployment decisions, vendor vetting, and incident response specific to a regulated environment. No hype, no scare stories—just the durable principles and checklists you need to use AI without leaking the data that keeps your firm licensed. Part of The AI at Work Library.

About the author

Marcus Chen Ferro writes for The AI at Work Library.

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E-bog: 28. september 2026