AI underwriting engine for a lending platform
An LLM-assisted underwriting engine that lifted application throughput sixfold while lowering default rates.
Business impact
6x application throughput
31% lower default rate
4-week payback
- Industry
- FinTech
- Timeline
- 14 weeks
- Team
- 6 engineers, 1 designer, 1 architect
Business challenge
Manual credit review capped approvals at 300 applications a day and risk decisions were inconsistent across analysts.
Solution
An LLM-assisted underwriting engine with document extraction, a feature store, and human-in-the-loop review dashboards.
Workshops, working software, measured results
How the work unfolded
Scroll to follow the programme from first workshop to measured result.
- 01
Discovery
Shadowed analysts for two weeks to map decision criteria and identify the documents driving most of the review time.
- 02
Data foundation
Built a feature store consolidating bureau data, bank statements and application history with lineage and access controls.
- 03
AI extraction & scoring
Deployed document extraction and an explainable scoring model, with LLM-generated summaries for analyst review.
- 04
Human-in-the-loop rollout
Launched to one analyst pod first, measured agreement rates, then expanded once accuracy thresholds were met.
Technology stack
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