Managing false positives systematically

A false positive is a potential match created by name similarity that is assessed as a different person or organization after contextual review.

Improve quality before thresholds

Normalizing input, preserving aliases and collecting strong identifiers improve review quality. Lowering a threshold alone may increase the risk of missed matches.

Use precedent with context

Prior decisions can accelerate research, but a changed customer or list record requires renewed review. Every closure rationale should be explicit and verifiable.

The right objective is not zero alerts; it is a manageable review queue aligned with the organization’s risk approach.