Automated Financial Reconciliation in SAP Systems Using Intelligent Data Matching

Abstract

Financial reconciliation ensures consistency between internal accounting records and external financial transactions in enterprise systems. In SAP environments, large volumes of financial data from invoices, payments, and bank transactions make manual reconciliation slow and error-prone. This study proposes an automated reconciliation framework using intelligent data matching techniques. The approach extracts transaction data from SAP modules, preprocesses financial records, generates structured features, and applies a matching algorithm to identify corresponding transactions across datasets. Evaluation using simulated enterprise financial transaction data shows that intelligent matching improves reconciliation accuracy and reduces processing time compared with traditional rule-based methods. The results demonstrate that automated data matching can enhance reconciliation efficiency and support reliable financial operations in SAP enterprise environments.