Use Cases

Financial Services (FinServ)

Key Outcomes: Fraud detection, credit risk scoring, customer segmentation

  1. Fraud & Anomaly Detection • Detect complex fraud rings by analyzing transaction networks with GNNs. • Reduce false positives by up to 30%.
  2. Credit Risk & Propensity Modeling • Combine borrower relationships, behavioral data, and external credit signals to enhance risk models. • Achieve 15% improvement in predictive accuracy.
  3. Anti‑Money Laundering (AML) & KYC Enhancement • Map entity relationships across accounts, devices, and geographies for rapid KYC analysis. • Accelerate investigations and reduce compliance costs.