buildingUnder construction, delivery in 4 weeks after kickoff

Financial reconciliation automation

Context

B2B company with a high volume of daily financial transactions. Receives roughly 10 PDF statements per day, each with thousands of transactions. Traditionally, an operator spent about 2 hours daily manually checking which values in the outgoing column had no counterpart in the incoming column, and vice versa.

What we deliver

A Python desktop tool, distributed as a standalone Windows executable. The usage flow is direct:

  1. User drags one or more PDFs into the interface.
  2. Clicks process.
  3. Receives an Excel spreadsheet with two tabs: outgoing without matching incoming, incoming without matching outgoing.

The tool runs 100% offline. No server dependency, no financial data sent anywhere, no Python install or any external dependency required. The client gets a single .exe file that opens with two clicks.

How the algorithm decides what's reconciled

Three criteria across two passes:

  • Same numerical value.
  • Same text name, with tolerance for names truncated by the bank's system.
  • Time proximity: strict filter first; when no match is found, relaxes to any time on the same day or different days.

Criteria are adjustable via a settings screen: time tolerance, minimum name prefix length, second-pass on/off. This lets the client refine behavior as the operation evolves.

Expected outcome

  • ~40 hours per month of operational work recovered.
  • Full traceability: each run generates an auditable spreadsheet with a summary of matched and unmatched pairs.
  • Zero operational risk: offline tool, no third-party dependency.

Stack

PythonpdfplumberopenpyxlCustomTkinterPyInstaller

How we execute this project

Paid 1-week discovery, scope, timeline and price locked, 4 weeks of construction, delivery with a 90-day warranty. No retainer, no hourly billing, no budget surprises.

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