coco-financial-fraud

To investigate suspicious financial transactions, you query the CoCo-Financial dataset in Snowflake to identify anomalous patterns, assess risk scores, and review contextual data from customers, accounts, and merchants.

Velocity analysis in financial fraud detection identifies rapid transaction bursts from a single account or customer, flagging suspicious activities where multiple transactions occur in an unusually short timeframe.

Yes, you need Snowflake access to detect financial fraud patterns, specifically requiring read access to the TRANSACTIONS, FRAUD_LABELS, CUSTOMERS, ACCOUNTS, MERCHANTS, and ALERTS tables.

You detect geographic anomalies in transaction data by analyzing customer location patterns to identify impossible travel scenarios, where transactions occur from geographically distant locations within impossible timeframes.

Yes, you can score customer risk based on fraud indicators by analyzing transaction history, velocity attack patterns, and geographic anomalies to assess the overall risk profile of customers and merchants.