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AI-Driven Multi-Document Correlation for Financial Compliance - Varsha Shah, Independent
Takeaway
Cross-document relationships and jurisdiction-aware normalization provide a stronger basis for financial risk detection than isolated record validation.
Summary
- The proposed compliance framework connects payroll, procurement, tax, and transaction records to reveal risks that isolated document checks miss.
- A graph-based entity engine links employees, vendors, accounts, transactions, and filings into a shared relational view.
- An adaptive probabilistic model combines anomaly strength, source reliability, and historical patterns, using audit outcomes to improve risk prioritization.
- A normalization layer harmonizes currencies, tax rules, reporting periods, and classifications; the evaluation setup includes approximately three million records over five years across four jurisdictions.
document-correlationfinancial-complianceknowledge-graphs
Original description
Traditional compliance and fraud detection systems analyze financial documents in isolation, making it difficult to identify sophisticated fraud patterns that emerge across multiple enterprise systems. This session presents an AI-driven framework that combines graph-based entity correlation, adaptive probabilistic risk modeling, and cross-jurisdictional normalization to detect hidden compliance risks across payroll, tax, procurement, and financial records. Drawing on an evaluation of approximately three million anonymized records across four jurisdictions, the talk demonstrates how cross-document intelligence can improve fraud detection accuracy, reduce false positives, and lower manual audit effort. Attendees will gain practical insights into building scalable AI solutions that transform enterprise compliance from a reactive validation process into a predictive, intelligence-driven capability. Speakers: Varsha Shah (Independent Researcher): Varsha Shah is a Technical Architect, researcher focused on enterprise AI, agentic systems, intelligent document processing, and AI-powered financial governance. LinkedIn: linkedin.com/in/varsha-shah-7b5111247 GitHub: https://github.com/VarshaShahTech