Interactive Case Study
AI Agent: Automating Enterprise Loan Underwriting
An autonomous multi-agent underwriting pipeline that parses commercial loan PDFs, calculates debt service ratios, checks credit bureaus, and drafts full credit memos in 15 minutes.
Client
FinTech Capital
Industry
FinTech & Commercial Lending
Timeline
10 Weeks
Role
Agentic AI Architecture & Financial Document Intelligence
Discovery & User Insights
Quantitative Research & Observations
Real user research data and market friction points evaluated before writing the first line of code.
15min
Loan underwriting turnaround (down from 4 days)
99.4%
Extraction accuracy across complex financial PDFs
12k+
Commercial loans audited with zero compliance breaches
70%
Reduction in loan origination operational cost
Target Audience
User Persona Profile
Understanding the primary user archetype ensures the user experience solves real, everyday friction without cognitive overload.
Jennifer Brooks
Senior Commercial Credit Underwriter • New York, USA
Core User Goals
Evaluate debt-service coverage ratios (DSCR) rapidly
Identify hidden balance sheet liabilities across multi-year tax returns
Focus on high-value client relationships instead of spreadsheet data entry
Existing Pain Points
Spending 80% of time re-typing numbers from scanned PDFs into underwriting models
Backlogs causing borrowers to seek competitor lenders
The Problem
What Needed Solving
FinTech Capital needed to speed up their commercial loan underwriting process. Manual financial statement audits, risk calculation, and credit bureau lookups took their team an average of 4 days per loan application.
Our Engineering & UX Approach
What We Architected
We developed an autonomous AI underwriting agent using LangGraph and Python. The agent automatically extracts financial metrics from uploaded PDFs, queries credit bureau APIs, runs credit risk calculations, and writes a comprehensive draft credit memo for underwriters.
System Flow
Step-by-Step Experience Architecture
How user intent transitions through the interface into automated real-time execution.
Document Parsing
AWS Textract & vision models extract income statements, balance sheets, and tax filings.
LangGraph Risk Engine
Multi-agent graph executes risk formulas, cross-references bureau APIs, and flags anomalies.
Credit Memo Generation
Agent compiles a comprehensive 6-page credit memo for final human underwriter sign-off.
Capabilities
Features & Deliverables Shipped
Autonomous document intelligence parsing for multi-page financial statements
LangGraph state flow decision paths with deterministic audit logging
Direct integration with credit bureau APIs
Automated comprehensive credit memo drafts with human-in-the-loop sign-off
Measurable Impact
By The Numbers
15m
Underwriting Time
99.4%
Extraction Accuracy
12k+
Loans Audited
70%
Process Cost Cut
Technologies
Tools & Stack
Portfolio
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