Leading SE Asian P&C Insurer (Insurance)
Automated Data Validation/Document Processing
Problem
The internal team of this insurance carrier identified quality issues in the KYC documents of numerous customers, prompting the need to validate individual customer information for accuracy.
Solution
An AI-driven system was developed to automatically identify key fields within KYC documents. These fields were then populated into a specific database and validated against manually entered data, ensuring consistency and accuracy.
Outcome
The system significantly streamlined the validation process, reducing manual effort and saving valuable time. The enhanced accuracy and efficiency led to faster document verification and improved operational productivity.



An Automated solution to validate customer information in KYC documents
The compliance team of an insurer identified data quality issues within the KYC documents of approximately 100,000 customers, which required validation of customer information against their corresponding KYC details. To address this, an automated solution was developed, ensuring efficiency while maintaining confidentiality. The system utilized Computer Vision, NLP, and Machine Learning models to automatically identify key fields within the KYC documents and extract relevant information. This data was then stored in a secure database and cross-validated against the manually entered information.



The implementation of the automated validation model drastically reduced processing time, with the system performing the validation within 48 hours. A task that would have taken over 400 man-days to complete manually was now completed quickly, resulting in significant time savings and efficiency gains.
400 man-days reduced to 48 hours.
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