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Payment Infrastructure

Reconciliation & Settlement

Close the books automatically

Presentation

Overview

Reconciliation is where the theoretical correctness of a payments system meets the messy reality of acquirer files, timing differences and fee structures that rarely match your internal expectations exactly. Pay Engineers builds reconciliation and settlement infrastructure that automates the matching work finance teams have traditionally done by hand in spreadsheets, while giving them clear, actionable visibility into anything that does not match automatically.

We start from the acquirer, processor or scheme files you actually receive, however inconsistent their formats, and build parsers and matching logic specifically tuned to those formats and the discrepancy patterns your business experiences. This is not a generic reconciliation tool; it is infrastructure built around your actual settlement partners and transaction patterns.

The goal is not just automation for its own sake, but faster, more confident month-end and day-end closes, with exceptions surfaced early enough to investigate rather than discovered during a stressful close process.

Who This Is For

  • Finance teams currently reconciling settlement files manually in spreadsheets, with significant time spent chasing discrepancies
  • PSPs and merchants processing across multiple acquirers with different file formats and settlement timings
  • Businesses that have experienced settlement discrepancies going unnoticed for too long due to slow manual processes
  • Any payments business preparing for financial audit and needing a defensible, automated reconciliation trail

What You Get

  • File parsers built specifically for the acquirer, scheme or processor file formats you receive
  • Matching rules that reconcile transactions, fees and settlements against your internal records automatically
  • An exception workbench where finance and operations staff can investigate and resolve unmatched or discrepant items efficiently
  • Settlement dashboards giving real-time visibility into cleared, pending and exception-flagged funds

Technical Approach

The platform is built on Laravel, with dedicated ETL pipelines handling the ingestion, normalisation and transformation of acquirer and scheme files, whatever their native format, delivery mechanism or update frequency. SFTP connectors automate file retrieval from partners who deliver settlement data that way, removing a common source of manual, error-prone process in finance operations.

PostgreSQL stores both the normalised settlement data and the matching results, with a clear, queryable trail of how each match was made, which is essential when an auditor or a partner disputes a reconciliation outcome. Matching rules are configured per acquirer or file type, reflecting the reality that fee structures, timing conventions and reference formats differ meaningfully between partners, and a single generic matching algorithm cannot handle all of them equally well.

Delivery Process

  • Discovery and detailed review of the settlement file formats, volumes and current reconciliation pain points across your acquirers
  • Matching rule and exception workflow design, validated against real historical settlement data from your business
  • Sprint-based build of parsers and matching engines, prioritised by acquirer volume or discrepancy history
  • Parallel-run testing against your existing manual process to validate matching accuracy before cutover
  • Rollout with close monitoring during your first live month-end or day-end close on the new system

Outcomes and Benefits

  • Dramatically reduced manual reconciliation effort, freeing finance staff for higher-value analysis work
  • Faster, more confident closes with exceptions surfaced early rather than discovered under deadline pressure
  • A defensible, automated audit trail for reconciliation decisions, valuable for external audit and partner disputes
  • Scalable reconciliation infrastructure that can absorb new acquirers or file formats as your business grows

Technologies

Laravel ETL pipelines PostgreSQL SFTP connectors

FAQ

The engine typically matches your internal transaction ledger against acquirer or processor settlement files, bank statement data, and gateway or payment method provider reports, identifying matches, mismatches and unmatched items across all sources automatically. We configure matching rules specific to the identifiers and formats your particular partners provide, since settlement file formats vary significantly between acquirers and processors. Multi-currency and multi-entity reconciliation is supported where your business operates across several legal entities or currencies, with matching rules scoped per entity as needed. This automation replaces what is very commonly a manual, spreadsheet-based process prone to human error at month-end.
Unmatched or discrepant items are surfaced in a dedicated review queue with the likely reason flagged automatically where the engine can determine one, such as timing differences, fee variances or currency conversion rounding, so your finance team can focus investigation effort on genuine exceptions rather than re-checking items that matched correctly. We build workflows for annotating, resolving and re-running matches on previously unmatched items as more data arrives, since some settlement timing differences resolve themselves within a few days. Aged unmatched items are escalated automatically based on thresholds you configure, ensuring genuine problems do not sit unresolved. This structured exception handling is usually the single biggest efficiency gain from automating reconciliation.
Yes, the engine is designed to reconcile and report across multiple acquirers, currencies and legal entities within a single system, rather than requiring separate reconciliation processes per relationship that finance then has to manually consolidate. Currency conversion timing and rate differences between your ledger and settlement reports are handled explicitly as a matching factor rather than treated as unexplained variance. Entity-level segregation is maintained throughout so consolidated group reporting and entity-level statutory reporting can both be produced from the same underlying reconciled data. This scales with your business as you add acquirers or expand into new currencies and entities.
By automating the matching process and surfacing only genuine exceptions, the engine typically reduces the manual effort required for month-end close from days to hours for businesses with meaningful transaction volume. We build standard close reports, such as settlement summary by acquirer, outstanding unmatched items, and fee reconciliation, directly aligned to what your finance team needs to sign off the close. Historical reconciliation data remains queryable for audit purposes long after the close period ends, supporting both internal and external audit requests. This is usually one of the fastest-payback engagements we deliver, since the operational time savings are immediately measurable.
A first release covering reconciliation against your primary acquirer or processor and basic exception workflows typically takes 8 to 12 weeks, with additional acquirers, currencies or entities added in subsequent phases as configuration rather than a full rebuild. Timeline depends on how many distinct settlement file formats need to be parsed and how clean your existing internal transaction data is, since data quality issues are usually the biggest source of delay. We run the new engine in parallel with your existing manual process for at least one close cycle before fully cutting over, so discrepancies in the new system are caught before it becomes the sole source of truth. This parallel-run approach is standard practice for financial systems of this kind.

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