This is like having a very smart auditor that has learned from years of historical tax returns. It scans new returns and flags the suspicious ones that don’t “look right” based on patterns seen in past fraud cases, so human investigators focus only on the riskiest filings.
Governments lose significant revenue to tax fraud and evasion, and manual audits can only cover a tiny share of returns. This system uses machine learning to automatically score income tax filings for fraud risk, helping tax authorities detect more fraudulent returns with fewer human resources.
Access to large volumes of historical, labeled tax return and audit data owned by the tax authority, plus integration into confidential government compliance workflows.
Classical-ML (Scikit/XGBoost)
Feature Store
Medium (Integration logic)
Data privacy and secure access to sensitive taxpayer data; maintaining model performance as fraudster behavior shifts over time.
2 use cases in this application