Streamlining Risk Operations: The Impact of Rule-Based Automation on Payout Requests


The company faced a growing challenge with their labor-intensive manual customer validation process for payout requests. As the volume of payout requests increased, the existing process became increasingly cumbersome, resulting in several issues, including delays, validation rule violations, elevated financial risks, and difficulties in identifying fraudulent cases.


The company partnered with to create a Rule Engine platform, automating manual validation and reducing turnaround time. The Rule Engine utilizes APIs to collect data from various source systems and categorizes payouts based on risk conditions stored in AWS RDS. Reports are generated by the "Generate Report microservice " following a schedule, saving them in an S3 bucket and emailing them as attachments, while an auditing mechanism maintains process oversight and error handling.


The Rule Engine automated validation, significantly improving SR processing speed and reducing errors. The system now handles 6,000 SRs monthly, a substantial upgrade. It increased Straight-Through Processing (STP) cases by an average of XX per month, enhancing efficiency.

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