Seeing the Unseen: Why Good AI Begins With Connected Data
Regulators are moving from box-checking to effectiveness, and banks are pointing AI agents at customer data that was never built to connect. Kimberly Lacey, a former Chief AML Officer at KeyBank and SunTrust, explains what breaks first — and what to build instead.
Inside the paper
- The $20,000 bribe you would have missed: the bribery network that was already sitting in the bank's own data — unconnected, and invisible to an AI agent working from fragmented sources.
- Why an AI agent on fragmented data just misses risk faster: the wrong Mary Smith, the missing prior name, the commercial account nobody linked.
- The five questions every financial crime executive should be able to answer before scaling AI — and be comfortable answering in hindsight.
“Without the right data foundation, AI will just have an institution make wrong decisions faster.”
— Kimberly Lacey, Former Chief AML Officer
20+ years fighting financial crime.
Read Kimberly Lacey's Paper
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Introduction
Financial institutions have an opportunity today that may not come again soon. They can build the data infrastructure required to deploy AI responsibly while simultaneously strengthening the effectiveness of their financial crime compliance programs.
The opportunity, therefore, is not simply to automate existing processes. It is to build the underlying data foundation that enables AI to operate at scale while improving the institution's ability to identify increasingly sophisticated financial crime. The challenge is no longer collecting more data. It is providing the context needed to turn that data into reliable intelligence.…
