Event-level transaction records rather than daily summaries, with stable identifiers that remain consistent across the ledger, switch, and acquirer feeds. For fraud detection, six to twelve months of history with confirmed fraud and chargeback labels is a realistic baseline. Beyond transaction data, models use device and session signals, relationships between cards and beneficiaries, and outcome data to close the feedback loop.