Real-Time Reconciliation Systems: Transforming Transaction Verification in Global Payment Networks
DOI:
https://doi.org/10.22399/ijcesen.3890Keywords:
Real-time reconciliation, payment systems, event streaming, data lineage, settlement verificationAbstract
Traditional reconciliation processes in global payment systems rely on end-of-day batch processing, creating significant delays between transaction execution and verification. Real-time reconciliation represents a paradigm shift that enables instantaneous verification of payment events as they occur, dramatically reducing the time gap between transaction processing and error detection. Event streaming platforms serve as the technological foundation for these systems, capturing and processing payment data including transaction identifiers, amounts, timestamps, and counterparty information in real-time. Reconciliation engines continuously compare incoming payment events against settlement files, authorization logs, and clearing records, enabling immediate identification of discrepancies such as missing payments, duplicate transactions, or settlement failures. Data lineage tracking provides comprehensive visibility into the complete lifecycle of each payment event, facilitating rapid troubleshooting and enhancing financial reporting accuracy. Global remittance companies and cross-border payment providers have successfully implemented these systems to verify fund delivery instantly, with automated alerts flagging discrepancies for immediate investigation. The implementation of real-time reconciliation eliminates traditional delays inherent in batch processing, reduces operational risk, and significantly improves the accuracy and reliability of financial transactions in modern payment ecosystems.
References
[1] Santosh Nikhil Kumar Adireddy, (2024). Idempotency and Reconciliation in Payment Software, International Journal for Research in Applied Science and Engineering Technology (IJRASET), https://www.ijraset.com/research-paper/idempotency-and-reconciliation-in-payment-software
[2] Krishna Mula, (2025). Real-Time Revolution: The Evolution of Financial Transaction Processing Systems, European Journal of Computer Science and Information Technology. https://eajournals.org/wp-content/uploads/sites/21/2025/04/Real-Time-Revolution.pdf
[3] Pradeep Kumar M. Kanaujia, et al., (2017). Real-Time Financial Analysis Using Big Data Technologies, 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), IEEE Conference Proceedings. https://ieeexplore.ieee.org/document/8058323
[4] Sivanagaraju Gadiparthi & Jagjot Bhardwaj, (2024). Comparative Analysis of Real-Time and Batch Data Processing: Technologies, Performance, and Use Cases, International Journal of Data Analytics Research and Development (IJDARD), Vol. 2, Issue 1(50–58), https://www.academia.edu/120709291/COMPARATIVE_ANALYSIS_OF_REAL_TIME_AND_BATCH_DATA_PROCESSING_TECHNOLOGIES_PERFORMANCE_AND_USE_CASES
[5] Yufei Wang, (2024). Optimizing Payment Systems with Microservices and Event-Driven Architecture: The Case of Mollie Platform, Vrije Universiteit Amsterdam & Universiteit van Amsterdam – Joint MSc Thesis, https://staff.fnwi.uva.nl/a.s.z.belloum/MSctheses/MScthesis_Yufei-Wang.pdf
[6] Xiaoxue Zhang & Chen Qian, (2022). Towards Aggregated Payment Channel Networks, 2022 IEEE 30th International Conference on Network Protocols (ICNP), IEEE Conference Proceedings, https://ieeexplore.ieee.org/abstract/document/9940365
[7] P. Helman & G. Liepins, (1993). Statistical Foundations of Audit Trail Analysis for the Detection of Computer Misuse, IEEE Transactions on Software Engineering, Volume 19(9), https://ieeexplore.ieee.org/document/241771
[8] Sayan Chakraborty, et al., (2021). Building an Automated and Self-Aware Anomaly Detection System, 2020 IEEE International Conference on Big Data (Big Data), IEEE Conference Proceedings, https://ieeexplore.ieee.org/document/9378177
[9] Parveen Mor, et al., (2021). A Systematic Review and Analysis of Blockchain Technology for Corporate Remittance and Settlement Process, 2021 Fourth International Conference on Computational Intelligence and Communication Technologies (CCICT), IEEE Conference Proceedings, https://ieeexplore.ieee.org/document/9514930
[10] Yuup Van Engelshoven & Stefanie Roos, (2021). The Merchant: Avoiding Payment Channel Depletion through Incentives, 2021 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS), IEEE Conference Proceedings, https://ieeexplore.ieee.org/document/9566168
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