Automated reconciliation enhances bank statements accuracy, indicating improved financial data integrity in audits.
Title: Automated Financial Data Integrity and Bank Reconciliation Using Deterministic Ledger Reconstruction Description: This work presents a deterministic, audit-grade framework for reconstructing true daily financial ledger balances from misordered ERP exports and bank statements. Conventional reconciliation tools fail when source files contain scrambled transactions, missing timestamps, or unreliable running balances. The proposed method uses credit–debit invariants to rebuild the ledger chronologically, independent of how the data is exported. It includes: Algorithmic reconstruction of daily closing balances Automatic detection of bank vs. Tally divergence dates Robust handling of descending-order bank statements Resilience against intra-day disorder and human posting errors Validated results using real financial data (Tally + Bank statements) Detailed architectural diagrams, flowcharts, and mathematical derivations LNNS-formatted manuscript ready for peer-review or conference submission This upload serves as a timestamped authorship record and open scientific contribution. It precedes formal publication and is made available for reproducibility, transparency, and citation via DOI. Keywords: Financial data integrity; deterministic reconstruction; reconciliation; accounting automation; ledger verification; bank statements; LNNS; algorithmic auditing; ERP exports Version: 1.0 (Pre-submission) Author: Abhishek Rai Georgia Institute of Technology, Modinagar Institute of Technology, Subharti University Emails: abraigr@gmail.com | arai@mit.in.net License: All rights reserved. This work is protected by copyright; redistribution only with permission.
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Rai Abhishek (2025) studied this question.
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