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AI Agents & Automation

Bank ReconciliationAutomation

Match thousands of statement lines to ledger entries by rule and by fuzzy logic, leaving your team a short list of genuine differences to investigate.

Bank Reconciliation Automation: what the work involves

Reconciliation sounds simple until the bank statement shows a single deposit that covers eleven invoices, a payment reference reads only TRF 4471, and a branch deposit slip was never posted. Staff scroll between two screens ticking lines off. In Pakistan, with several bank accounts, raast and cheque transfers, and mobile wallet settlements, the monthly job can swallow a week.

DevKey builds a matching engine around your accounts. Statements arrive as CSV, PDF or through bank feeds, and are normalised into one format. Deterministic rules handle exact matches first. A second layer scores likely matches using amount, date proximity, names and reference fragments, including one-to-many and many-to-one groupings. Anything below your confidence threshold goes into a worklist with the candidates shown side by side, and each confirmed match improves future suggestions.

What we build

Core features

01

Statement normalisation

CSV exports, PDF statements and API feeds from different banks are converted into a single structure with consistent dates, signs and reference fields.

02

Layered matching rules

Exact reference and amount matches clear first, followed by tolerance rules, then probabilistic suggestions for the harder cases.

03

Split and batch matching

One bank deposit can be matched to a set of invoices, or a bulk payment to several bills, with the combination tested rather than guessed.

04

Gateway settlement tie-out

Payouts from payment processors and courier cash collections are reconciled against the underlying orders, including fees deducted at source.

05

Reviewer worklist

Open items show the best candidates with reasons for the score, and one click confirms, rejects or posts a missing adjustment entry.

06

Variance and ageing report

Unmatched items are summarised by age and amount so you can see what needs chasing before period close.

Planned for

What we get right before launch

A wrong match hides a real error

Auto-confirming too eagerly can bury a missing payment. We set conservative thresholds, test on past periods where the right answers are known, and allow only exact matches to clear without review.

Bank data access

Some banks offer APIs, others only portals and PDFs. We check what your banks permit, avoid storing login credentials where possible, and keep statement files in encrypted storage with access logs.

Messy references

Payers type names in odd ways and use informal references. We build alias tables for recurring customers and let reviewers teach the system, rather than relying on the model to guess.

Stack

Tools and technology

  • Python
  • pandas
  • FastAPI
  • PostgreSQL
  • OpenAI GPT
  • Xero and QuickBooks APIs
  • Open Banking and Plaid feeds
  • Next.js
  • Docker
Bank Reconciliation Automation FAQ

Common questions, answered

Can it handle Pakistani bank statements?

Yes, in principle. Most banks provide CSV or PDF statements, and we write parsers per bank format. We start with the accounts you use most and test each parser on several months of real data.

Does it post adjustments automatically?

Only when you allow it. Typically bank fees and rounding differences follow explicit rules you approve, while other adjustments are drafted for a person to review before they touch the ledger.

How does it deal with one payment covering many invoices?

It searches combinations of open invoices whose total fits the deposit, within tolerances, and proposes the most plausible set. The reviewer sees the candidates and confirms the grouping.

What if our accounting system has no API?

We can work with exports, import templates or direct database access. Feasibility depends on the software, so we check it before committing to a design.

What drives the cost?

Number of banks and statement formats, transaction volume, complexity of matching rules, and the accounting system integration. A sample month of statements and ledger data lets us scope accurately.

Ready to start your Bank Reconciliation Automation project?

Tell us what you need and we will come back with a clear scope, timeline and the questions worth answering before any build starts.