fintech-fraud-sim: Bridging Realistic Fraud Testing and Production Safety

Testing fraud detection systems requires realistic patterns that reflect how actual fraud manifests across user behavior and transactions—not random fields or production customer data. fintech-fraud-sim solves this by generating synthetic fraud scenarios with configurable patterns and deterministic output, enabling teams to build better fraud models, dashboards, and monitoring systems without regulatory or privacy risks. For fintech engineers, this means faster development cycles and higher-confidence testing across QA, rules engines, and analytics pipelines.