Transforming Fraud Detection: PureSoftware’s Automated Solution for a Leading Global Telecommunication Company

February 5, 2025

Business Problem

The fraud detection process, a crucial security task for identifying defaulters whose credit cards had been barred or cheques had defaulted, was handled manually. This involved identifying and working on the defaulters and inactive user list, which required significant effort for comparison and validation. Employees had to download data from one application and upload it to another portal, consuming considerable time and resources.

Business Analysis

PureSoftware conducted an in-depth analysis to understand the specific requirements and challenges of the fraud list process. The analysis revealed that the manual handling of this process was inefficient, error-prone, and time-consuming. There was a need for an automated solution to streamline the process, reduce manual effort, and improve accuracy. The goal was to automate the comparison, validation, and data transfer tasks, thereby freeing up employees to focus on more value-added activities.

Our Implementation

PureSoftware’s RPA Center of Excellence (CoE) designed and implemented a phased-driven deployment approach to automate the fraud detection process. The RPA solution was developed to handle the process optimally. The bot was configured to compare, download, and upload files, and log into different portals, significantly saving employee time. For any discrepancies, a Single Point of Contact (SPOC) received all the information via email from the first step to the end. This automation not only streamlined the process but also ensured that all steps were monitored and any issues were promptly addressed.

The Impact Delivered

The entire fraud list process can now be automated with RPA, handling over 90% of all transactions through RPA bots, leading to a 95% effort reduction in each run.

Manual effort has been reduced by 75% with the RPA solution in place.

The overall process execution time has been reduced to 10 minutes from the original 30 minutes.

Total execution and maintenance costs have been reduced by 70%.

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