JP Morgan's Contract Intelligence: AI That Reads 360,000 Hours of Documents in Seconds
Richard Casemore - @skarard
The Problem: Drowning in Documents
Every commercial loan agreement at JP Morgan required manual review. Lawyers spent hours extracting key terms, identifying risks, and ensuring compliance. With thousands of agreements processed annually, the bank was spending 360,000 hours—the equivalent of 180 full-time lawyers—just on document review.
The work was tedious, error-prone, and expensive. Something had to change.
Enter COIN: Contract Intelligence
JP Morgan's COIN platform uses natural language processing to analyze legal documents in seconds. What took lawyers hours, AI accomplishes while they reach for their coffee.
The system:
- Extracts 150+ attributes from each document
- Identifies non-standard clauses and risks
- Flags compliance issues automatically
- Learns from lawyer feedback to improve accuracy
Implementation Challenges
Building COIN wasn't straightforward. Legal language is notoriously complex—intentionally so. Early models struggled with:
- Nested conditional clauses
- Cross-references between sections
- Industry-specific terminology
- Deliberate ambiguity (a feature in legal drafting)
The breakthrough came from training on JP Morgan's own historical documents, annotated by experienced lawyers. This domain-specific training data proved more valuable than generic legal corpora.
The Results
COIN's impact exceeded expectations:
- 360,000 hours saved annually on document review
- Error rate reduced by 90% compared to manual review
- Loan servicing errors dropped from several per month to near zero
- Processing time from days to seconds
But the real value wasn't just efficiency—it was consistency. COIN applies the same rigorous analysis to every document, eliminating the variability inherent in human review.
Expanding the Platform
Success with loan agreements led to expansion:
- COIN 2.0 now handles credit default swaps and custody agreements
- Research analysis uses similar techniques to process financial reports
- Regulatory compliance applies AI to monitor changing requirements
JP Morgan now processes over 12,000 commercial credit agreements annually through COIN, with plans to expand to 150 additional document types.
Lessons for Financial Services
JP Morgan's experience offers guidance for AI adoption in finance:
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Start with high-volume, rule-based tasks: Document review was ideal because it was repetitive and had clear success criteria
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Domain expertise is essential: General-purpose AI couldn't match models trained on actual JP Morgan documents
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Lawyers remain crucial: AI handles extraction; humans handle judgment calls on complex issues
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Measure everything: Clear metrics (hours saved, error rates) built organizational support
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Iterate rapidly: COIN improved continuously based on lawyer feedback
The Competitive Advantage
Banks that master AI operations gain structural advantages:
- Lower costs enable more competitive pricing
- Faster processing improves customer experience
- Reduced errors minimize regulatory risk
- Freed-up talent focuses on higher-value work
JP Morgan's investment in operational AI isn't just about efficiency—it's about building capabilities competitors will struggle to match.
The future of financial services belongs to institutions that can process information faster, more accurately, and at lower cost. COIN is just the beginning.