Reducing Risk Through AI-Driven Document Reconciliation
An international financial services company faced compliance risks and inefficiencies due to manual reconciliation between disconnected policy systems, leading to $1M+ in annual underwriting risk. We implemented an AI-powered document comparison solution using NLP to flag clause-level discrepancies, cutting manual effort, reducing errors, and improving compliance, speed, and customer satisfaction.
Challenge
An International Financial Services Company was facing compliance and operational challenges when it came to policy documentation. Policy changes were maintained across two disconnected systems, a Word-based policy booklet, and a mainframe system. This meant analysts had to manually reconcile discrepancies between both systems by comparing documents and Excel exports line by line. This not only was labor-intensive and time consuming, but this error-prone process regularly resulted in mismatched policy clauses between what customers received and what was in the system of record. These clause inconsistencies exposed customers to over $1 million in unrecognized underwriting risk annually and slowed down policy servicing and heightened audit vulnerabilities.
Solutions & Impact
Process modernization was implemented through an AI-powered document comparison solution that automatically ingests the Word-based policy booklet and mainframe exports. Using natural language processing (NPL), clause-level discrepancies are identified and presented in a unified interface for analysts to easily review.
- Eliminated manual reconciliation, saving analyst time, and reducing human error.
- Reduced mismatched policy risk by over $1M/year and improved underwriting accuracy.
- Improved compliance with a full audit trail and tracking of policy changes.
- Accelerated policy servicing, leading to higher customer satisfaction and operational efficiency.
With this solution, the client was able to improve operations, reduce risk, and position the team for scalable, compliant growth.
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