Most organizations are being pushed to adopt AI-powered workflows before their data is anywhere close to ready. In this episode of What Counts, Maura and Lee pick up where they left off — diving deep into the concept of data reconciliation and why it must happen before AI ever touches your records. Using a real-world example built across multiple systems — a customer database, a work order system, and a contract management platform — they break down what it means to have duplicate, overlapping, and contradictory counterparty data, and why humans, not algorithms, are the ones who can resolve it. Maura introduces the concept of the golden record, explains the role of metadata mapping and fuzzy matching, and walks through the governance framework — policy, process, and system-of-record designation — that prevents the mess from coming back. If your organization is facing an AI initiative, a system migration, or growing pressure around data privacy and right-to-be-forgotten compliance, this episode gives you the foundational framework you need to start doing it right.
Continued in Episode 133: Counterparty Data Reconciliation at Scale.
Episode length: 00:26:36
What Counts is produced by TrailBlazer Consulting, LLC and hosted by Lee Karas and Maura Dunn. Learn more at trailblazer.us.com or email us at info@trailblazer.us.com. Explore compliance-ready training at the TrailBlazer Learning Academy. Read more from Maura at mauradunn.substack.com. Music by Jason Blake. Full disclaimer.