Bank Reconciliation Automation: MT940, BAI2, & ISO 20022 CAMT Architecture
Engineered parsing, intraday matching, and automated balance verification across global corporate banking formats.
Parsing Mechanics: BAI2 vs MT940 vs CAMT.053
BAI2 uses comma-delimited records with continuation lines (Record 88) that often split reference codes across line boundaries. MT940 uses colon-delimited SWIFT tags where Field :86: contains free-text transaction narration. Modern banking uses ISO 20022 CAMT.053 XML files. A reliable data layer must parse all three formats deterministically without dropping metadata.
Handling Intraday (BAI2 Record 02 / CAMT.052) vs End-of-Day Statements
Real-time treasury operations require ingesting intraday provisional reports while maintaining clean separation from final end-of-day cleared statements. Reconciliation engines must handle transaction state transitions gracefully, ensuring provisional transactions are replaced by finalized clearing entries without creating duplicate ledger records.
Continuous Cash Invariant Verification with the NAYA Proof Engine
The NAYA Proof Engine matches statement line items against internal payment intent records, verifying that Opening Balance + Total Credits - Total Debits = Closing Balance for every bank account. It highlights unallocated items immediately and generates automated bank reconciliation proof packs.
Frequently Asked Questions
Common questions about this topic
QWhat is the difference between MT940 and MT942?
MT940 is the End-of-Day (EOD) statement, considered the legal final record. MT942 is an Intraday Interim statement, providing a snapshot of transactions during the day. Automated systems use MT942 for speed and MT940 for final verification.
QWhy can't we just use Plaid/Yodlee/Teller?
Aggregators are great for consumer apps but often lack the data fidelity required for complex B2B reconciliation. They may scrub description fields or lack the specific "Bank Reference ID" needed for 100% accurate matching. Direct host-to-host (SFTP) connections are preferred for enterprise scale.
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