For lending fintechs
Bank statement parsing for underwriting
Turn a Nigerian bank statement PDF into clean transactions, balances, and account metadata over one API call. NDPR-aware redaction in the same call.
Built for a lending data pipeline
The ask is to trust an API with underwriting data. Here is why you can.
Open source engine
The parser is MIT-licensed. Read it, run it, audit the exact code that touches your data.
View the engine on GitHubSelf-hostable
Run the whole stack inside your own infrastructure. Nothing has to leave your network.
Self-host guideProcessed in memory
The statement is parsed in memory. It is never written to disk and never logged.
NDPR-aware redaction
Names, account numbers, and BVN masked in the same call. No second pipeline.
Metadata-only audit log
We record that a file parsed. Never what was in it. No transactions, no balances.
How it fits
- 01
Applicant uploads a statement
A PDF from any covered bank. The same file your underwriters read by hand today.
- 02
One API call parses it
Transactions, balances, and account metadata come back structured and typed. Every parse runs a balance check.
- 03
You underwrite on clean data
No fragile in-house parser to maintain. It handles the statements a direct-connect cannot reach, and the ones customers upload by hand.
curl -X POST https://bankstract.logickoder.dev/v1/parse \
-H "Authorization: Bearer bsk_live_..." \
-F "pdf=@statement.pdf"Coverage
Live today: PalmPay, First Bank, Zenith, and Opay. New banks and format drift ship in about 48 hours. If a bank you need is not covered, that is exactly what a design partner sets the priority on.
Start on the free tier: 25 parses a month, no card. Paid tiers from ₦9,500/mo. See pricing.
Parse your first statement
Free demo, no signup. Self-host the whole stack, or use the cloud when paid tiers ship.
Need volume or NDPR audit support? Talk to sales.