Vendor Collusion Graph Detector
Description
Detect suspicious vendor/employee/payment relationships and unusual clusters in vendor master, contract, invoice and payment data.
AI / analytics pattern
graph analytics + anomaly detection
Automation level / stage
human-in-the-loop analytics
Expected benefit
High-value DoD FM productivity, auditability, data-quality and control improvement.
Audit / financial statement impact
Expenses, accounts payable, accounts receivable, compliance reporting
Controls / human review
Human approval required before posting, payment, denial, personnel action, or official audit response; model validation; drift monitoring; exception sampling; full prompt/data/output logging.
Data needed
ERP transactions, vendor master, travel, payroll, contract pay, public/exclusion lists, investigative data; transaction history; audit evidence; reference data; control requirements.
Possible metrics
dollars impacted; exceptions resolved; aged balance reduction; cycle time; NFR closure; audit sample pass rate
MVP scope
Build as a controlled pilot using one Component/process, read-only dashboards, and documented human signoff.
Related material weakness / control objective
Improper payment prevention; fraud risk management