Atlas Commerce (fictional) · Process Optimization
Multi-Bank Reconciliation
A unified reconciliation layer across multiple banks, currencies and statement formats, collapsing a multi-day manual routine into a guided, exception-based workflow.
The Problem
Atlas Commerce held accounts across several banks, currencies and statement formats. Every month-end, analysts reconciled them by hand against the ledger — a slow, error-prone routine under a hard deadline.
Why It Matters
An unreconciled account is not a technical detail — it is a number leadership cannot yet trust, on the eve of a decision.
How I Approached It
I designed a normalization layer that ingests every statement format and currency into one model, then auto-matches transactions to the ledger by amount, date and counterparty. Anything it cannot match with confidence becomes an exception card with suggested candidates, so analysts spend their time only on what truly needs judgment.
- Any format — OFX, CSV, API, PDF — into one model
- Auto-matched by amount, date and counterparty
- Only unmatched items reach a person, with candidates
Interactive Demonstration
The preview is the reconciliation workspace: match rate by account and exception cards. Fictional and illustrative only.
Match rate
1284/1310 matched
Exceptions · Northwind Bank
Card settlement batch
Suggested match: Merchant payout · Jul 03
Unidentified credit
Suggested match: Refund · Halcyon Retail
Enabling Technology
Ingestion
- Multi-format parsers
- Currency normalization
- Unified model
Matching
- Rules + tolerances
- Candidate suggestions
- Exception queue
Close
- Status by account
- Sign-off control
- Audit log
Business Value & Takeaway
Month-end reconciliation moves from days to hours, with one view across every bank and currency, and breaks found early instead of against the deadline.
Speed came from normalizing the data first. The technology only made it repeatable.