National Insurance Crime Bureau ISO ClaimSearch
Description
The purpose of the AI use case in National Insurance Crime Bureau ISO ClaimSearch is to analyze insurance claim data and highlight suspicious patterns or anomalies more efficiently. By applying AI-driven pattern recognition, risk assessment, and anomaly detection, it streamlines what would be a tedious manual review process. This leads to faster fraud identification, more accurate targeting of problematic claims, and better resource utilization, ultimately strengthening investigative outcomes.
Detailed example
The AI features produce lists of flagged claims, show patterns, and suggest where deeper validation might help.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
The expected benefit is more effective resource use, targeting claims that differ from typical patterns rather than all equally.
Audit / financial statement impact
Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
Controls / human review
ATO: No; PIA: Not published
Data needed
The case owner relied on DOJ AI governance practices to select and prepare data, as well as evaluate performance.