AI Loan Processing
Automation

The challenge

A fast-growing digital lender was processing hundreds of loan applications per week, but their review team was buried in manual document checks, data extraction from PDFs, and repetitive credit decisioning tasks. Response times stretched to 3–5 business days, causing applicant drop-off and limiting growth without proportional headcount increases.

What we built

We designed and deployed a full Intelligent Process Automation system handling the entire loan pipeline — from document ingestion to credit decision output:

• AI document ingestion engine extracting structured data from bank statements, payslips, and ID documents with 90%+ accuracy
• Intelligent data validation layer cross-checking extracted data against application inputs and flagging discrepancies
• Agentic credit assessment model applying configurable decisioning rules and generating structured decision reports
• Human-in-the-loop escalation workflow for edge cases and appeals
• Real-time dashboard for the operations team with SLA tracking and exception management
• Full audit trail for regulatory compliance

The results

Within 8 weeks of go-live, the system was processing 100% of incoming applications. Average review time dropped from 3.2 days to under 11 hours. The team tripled application volume without adding headcount, and applicant NPS scores improved significantly due to faster decisions.

Technology used

• Custom LLM pipeline for document understanding (fine-tuned on financial documents)
• Python + FastAPI backend with PostgreSQL data store
• AWS Lambda + S3 for document processing and storage
• React operations dashboard
• Full CI/CD pipeline via GitHub Actions