JPMorgan Chase

JPMorgan's lawyers and loan officers spent approximately 360,000 hours annually manually reviewing commercial loan agreements. The manual process was slow, prone to human error and inconsistency, and consumed resources that could otherwise go toward more strategic work. As the volume of agreements grew, the manual review process became increasingly unsustainable.

JPMorgan built COIN (Contract Intelligence), an in-house AI platform launched in 2017 through the bank's Center of Excellence within Intelligent Solutions. COIN uses unsupervised machine learning and image recognition to identify and automatically classify clauses in commercial loan agreements into roughly 150 contract "attributes," running on a private cloud infrastructure for scalability.

COIN cut the time needed to review about 12,000 annual commercial credit agreements from 360,000 hours down to seconds. The system also demonstrated higher accuracy than manual review by human lawyers, reduced operational costs, and freed legal teams to focus on more complex, strategic tasks.

• Automating repetitive, high-volume contract review can eliminate hundreds of thousands of hours of manual legal work annually.
• Unsupervised learning paired with pattern recognition can reliably classify and extract structured attributes from legal contract text at scale.
• Building AI capability in-house (via a dedicated Center of Excellence) let JPMorgan scale document processing without proportional headcount growth.