• High manual workload due to mixed-format documents, including scanned and handwritten claims.
• Inconsistent or incomplete data causing delays in internal verification.
• Long claim processing times, often taking days, impacting customer satisfaction.
• Need for high accuracy in extracting sensitive personal and medical information.
• Scalability concerns, as claim volumes increased steadily over time.

• Built an AI document processing engine with full OCR capabilities for PDFs, scanned images, and handwritten forms.
• Automated key information extraction, including medical details, personal info, and claim-specific fields.
• Implemented data validation and verification checks to highlight missing or inconsistent information.
• Integrated the AI engine into the client’s claim workflow, enabling faster approvals and reduced errors.
• Provided monitoring and reporting tools to track extraction accuracy and operational efficiency.

Impact

• 40-50% reduction in manual effort for claim processing.
• Claim processing time reduced to under 8 hours, down from multiple days.
• Data extraction accuracy improved to approximately 90%, reducing errors and rework.
• Backlog volume reduced by 30-35% within the first quarter.
• Enhanced operational efficiency and customer satisfaction, while enabling the client to scale claim processing without adding headcount.