SQL-Based Data Reconciliation in Banking Systems

Abstract

SQL-based data reconciliation is important in banking systems because financial records must remain accurate, consistent, and traceable across core banking platforms, payment gateways, ledgers, customer accounts, and reporting databases. Reconciliation using SQL helps compare transactions, identify mismatches, detect missing entries, validate balances, and generate exception reports through structured queries and database rules. Existing literature highlights record matching, balance verification, duplicate detection, variance analysis, audit trails, transaction status checking, and source-to-target comparison as major methods for banking data reconciliation. However, many banks still face challenges such as delayed settlement updates, duplicate transactions, inconsistent account mapping, missing reference numbers, timing differences, and weak exception tracking across multiple systems. This research is important because unreconciled banking data can affect financial reporting, regulatory compliance, fraud detection, customer trust, and operational accuracy. This article discusses SQL-based data reconciliation in banking systems, focusing on transaction matching, ledger comparison, checksum validation, exception reporting, duplicate identification, reconciliation logs, and automated query-based controls. The study concludes that effective SQL-based reconciliation improves financial data accuracy, reduces operational risk, strengthens audit readiness, and supports reliable banking information management.