Real-time reconciliation shifts financial operations from a reactive, T+1 (next day) batch process to an event-driven model. In high-volume environments (marketplaces, gig economy payouts, high-frequency trading), waiting 24 hours to verify a transaction is unacceptable.
Implementing this requires moving away from parsing End-of-Day (EOD) bank files and towards consuming real-time notification rails (Webhooks, Instant Payment notifications like RTP/SEPA Instant). The goal is to update the user's balance or the merchant's ledger immediately upon settlement confirmation, providing "intraday" visibility into cash positions.
Event-Driven Architecture (EDA) vs. Batch
In a legacy batch model, the system parses a CSV at midnight. In a real-time model, the architecture relies on message queues (e.g., Kafka, RabbitMQ). The Publisher: The Payment Service Provider (PSP) or Bank API pushes a webhook event (payment.succeeded). The Consumer: The Reconciliation Service consumes this event. The Stream: The service queries the internal ledger for the pending transaction. If found, it updates the status to reconciled instantly. This reduces the "Cash Trap"—money that is physically available but operationally inaccessible because the system hasn't recognized it yet.
Handling Race Conditions and Latency
Real-time reconciliation introduces concurrency challenges. A common race condition occurs when a bank webhook arrives before the internal system has finished creating the initial transaction record (e.g., due to database latency). If the reconciliation engine queries the ledger and finds null, it must not fail the match. Instead, it should implement a "retry with backoff" strategy or place the bank event into a "holding pattern" queue. The system periodically re-scans the holding queue against the ledger, allowing the internal record time to propagate.
