Settlement Report and Bank Statement Reconciliation

• Head of Reconciliation
• Settlement Operations Manager
• Financial Controller
• Treasury Manager

A payment aggregator reconciles at least three views of the same money: its own transaction log, settlement reports from acquiring and UPI partner banks, and credits in the escrow account statement. Fees, GST on fees, refunds, chargebacks and net settlement mean the numbers rarely match line for line, and every source uses its own formats and references.

We build a reconciliation engine that ingests your transaction log, settlement files and bank statements in whatever format they arrive, normalises them and matches them at the right level: one-to-one, one-to-many and net batch. Deterministic rules handle known patterns such as MDR, GST on fees, refunds, chargeback debits and reserves. Where rules run out, a language model reads the remaining context, such as statement narrations, file headers and emailed advices from the bank, and proposes an explanation with the supporting lines. Your reconciliation analyst accepts or rejects each proposal. Every break has an age, an owner and an audit trail, and approved matches feed your merchant payout and GL posting.

• Parses CSV, Excel, fixed-width and PDF settlement reports and bank statements, and detects layout changes
• Matches one-to-one, one-to-many and net batches using UTR, RRN, ARN and amount-date windows
• Applies rules for MDR, GST on fees, refunds, chargeback debits, reserves and holds
• Proposes explanations for unmatched items from narrations and bank emails, with evidence
• Tracks break ageing, ownership and resolution notes
• Produces payout-ready and GL-ready files from approved matches

1. 01Ingest the sourcesTransaction logs, acquirer and UPI settlement files and escrow statements are pulled daily by SFTP, API or mailbox.
2. 02NormaliseEach file is mapped to a common schema, and layout changes are held for confirmation rather than silently misread.
3. 03Match with rulesDeterministic rules match transactions to settlements and settlements to bank credits, including net batches.
4. 04Explain the remainderFor unmatched items, the model proposes a likely explanation with the supporting lines and documents.
5. 05Analyst reviewReconciliation analysts accept, correct or reject each proposal and assign open breaks to an owner.
6. 06Post and reportApproved matches feed merchant payouts and GL entries, and open breaks appear in an ageing report.

1. Ingestion
   • SFTP and bank API pulls
   • Mailbox parser for emailed MIS
   • File layout change detector
2. Normalisation
   • Schema mapper per source
   • Reference cleaner for UTR, RRN and ARN
3. Matching
   • Rule engine for one-to-one and one-to-many
   • Net batch solver
   • LLM break explainer
4. Review
   • Break workbench with ageing and owners
   • Maker-checker approval for adjustments
5. Output and audit
   • Payout file generator
   • GL posting export
   • Audit trail

Analysts approve every model-proposed explanation and every manual match, with maker-checker on write-offs and adjustments. Rule-based matches are sampled daily, and payouts are released by your treasury team, not by the engine.

• Payment gateway or switch database
• Acquiring and partner bank SFTP or API
• Core ledger or ERP such as SAP, Oracle or Tally
• Merchant payout system
• BI tool such as Power BI or Metabase

• Model explanations are proposals only and never close a break without analyst approval
• Maker-checker on any adjustment or write-off
• Layout changes stop the affected file from auto-processing until a person confirms the mapping
• Every match records the rule or reviewer that made it
• Bank and merchant account numbers masked in logs

• Supports the escrow reconciliation and audit trail that payment aggregators are expected to maintain under RBI directions.
• Payment data processed and stored in India, consistent with RBI's direction on storage of payment system data.

• Fintech & Payments

  Chargeback and Dispute Evidence Pack Assembly

  Gather order, delivery, authentication and refund records for each chargeback, check them against the reason code and draft a representment pack for your disputes analyst.

• Fintech & Payments

  Invoice and GST Data Extraction for B2B Payments

  Extract GSTINs, HSN lines, tax splits and IRN data from supplier invoices before a B2B payment or invoice financing is released, with tax-logic and duplicate checks.

• Accounting, Audit & Consulting

  Bank and Ledger Reconciliation

  Match bank statements in any format against the cash book or ledger, explain unmatched items and produce a BRS the reviewer can tick through, with ambiguous matches held for a person.

• Retail, D2C & Quick Commerce

  Vendor Invoice and Credit Note Reconciliation

  Match vendor invoices, GRNs, RTVs and credit notes, recalculate what each vendor owes you from the agreements, and chase missing or short credit notes with evidence.