Temporal Layering and Rule-Based Matching in Distributed Settlement Ledgers: A Multi-Horizon Reconciliation Architecture for Financial Break Detection (International Journal of Intelligent Systems and Data Science)

Summary

• The paper introduces a multi-horizon reconciliation architecture that coordinates daily batch, hourly incremental partitioning, and real-time listener interception over a single transaction stream.p.1
• The empirical study evaluated one month of production data totaling 210 million transactions from a distributed loan origination system processing approximately 7 million transactions daily.p.9
• The evaluation identified 1,200 classification anomaly exception records, representing $5,000 in misapplied fees.p.12
• Operational testing detected 210 compatibility processing error exception records, representing $30,000 in exposure recorded at detection.p.12
• The platform recorded 85 calculation discrepancy exception records, resulting in $12,000 of realized loss.p.12

Key insights

1. A shared rule repository and unified exception store prevent duplicate alerting and maintain semantic consistency across distinct temporal tiers.p.1
2. Deterministic rule-based SQL logic provides the auditability and interpretability essential for regulated financial reconciliation compared to machine-learning models.p.2
3. The real-time listener tier evaluates approximately 1% of transaction volume filtered by risk criteria within a 15-minute latency target.p.8
4. Transaction suspension events generated 45 exception records with $0 realized loss because settlement was blocked prior to execution.p.12