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Lending

Lumen Credit

An SME loan decision in nine minutes

A working capital facility approved in nine minutes, every factor showing what it contributed
Sector
Lending
Location
Dubai, UAE
Year
2025
Kickoff to production
18 weeks
01Overview

Statement-driven underwriting that reads a business the way a good credit officer would, and shows its reasoning.

02The problem

Underwriting a small business took six days of reading PDF bank statements by hand. Two officers could reach different answers on the same file, and nobody could reconstruct why a loan was declined six months later.

The underwriting queue at the start of a day, scored and sorted before anyone opens a file
03What we built
  1. 01

    Statements into cashflow

    Bank statements are parsed into a normalised cashflow view (revenue quality, seasonality, salary runs, bounced payments) regardless of which bank produced them.

  2. 02

    Policy as code

    Credit policy lives in a versioned rules engine, so a change is reviewed, dated and replayable against past decisions before it goes live.

  3. 03

    Every decision defensible

    The reviewer console shows the factors behind each score with the underlying transactions one click away.

A decline held open on its binding constraint, with the two changes that would clear it
A policy change replayed against 1,284 past decisions before the committee lets it live
04The result

Approvals move without loosening risk, and the credit committee finally reviews policy rather than individual files.

What changed

Time to decision
Minutes
Reason on every decision
Written
Risk unchanged
Same policy
The decision pack it prints, every reason traceable to a parsed bank statement line

Stack

  • Python
  • Postgres
  • LangGraph
  • Next.js
  • AWS Textract

Disciplines applied

  • AI solutions
  • Financial technology
  • Data & analytics

Closing

Do you have an idea, or a problem?

Either works. In my experience the second one goes faster.

I usually reply the same day.