AI-Driven Multi-Document Correlation for Financial Compliance - Varsha Shah, Independent

Varsha Shah's research introduces an AI-driven framework for enterprise financial compliance and fraud detection, overcoming the limitations of traditional systems that analyze documents in isolation. The framework combines graph-based entity correlation, adaptive probabilistic risk modeling, and cross-jurisdictional normalization to uncover hidden fraud patterns across payroll, tax, procurement, and financial records. Evaluated on 3 million anonymized records across four jurisdictions, it demonstrates significant improvements in detection accuracy (91% precision, 87% recall), reduces false positives by 76%, and lowers manual audit effort by 40%, ultimately transforming compliance from a reactive process into a proactive, intelligence-driven capability through continuous learning.