Anomaly Detection for Financial Transactions Related to DOI Programs
Description
Use traditional machine analytics with difficult-to-manually-analyze financial data for DOI programs to create analytical methods that are scalable and repeatable. Additionally, the analytics must be aligned with quality standards required for OIG audits and investigations.
Detailed example
Outputs will identify anomalous transactions and will be provided to auditors or law enforcement analysts and agents to further review and/or action.
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
b) Pilot – The use case has been deployed in a limited test or pilot capacity.
Expected benefit
It allows OIG to identify anomalies or trends that would be undetectable via manual analysis or would require endless IT and staff resources to manually process and analyze information.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Financial Transaction Data related to DOI Programs