Optimization of Application Testing in Financial Companies Using Robotic Process Automation (RPA)

Abstract

In the rapidly evolving era of digitalization, financial companies face the challenge of enhancing efficiency and accuracy in application testing processes. Manual testing, which is time-consuming and prone to human error, is a major obstacle in ensuring the reliability of applications. This study aims to optimize the application testing process in financial companies by implementing Robotic Process Automation (RPA) as a tool for automated testing. The methodology used includes the analysis of testing requirements, selection of the appropriate RPA tools, and the implementation and performance evaluation of the RPA system. The results of the study indicate that the implementation of RPA can reduce testing time and improve error detection accuracy. For the partner application, there are a total of 6 test sets, 31 test cases, 31 scenarios, and 112 test steps. Meanwhile, for the sales application, 6 test sets, 29 test cases, 29 scenarios, and 115 test steps were identified. Using RPA, the duration of manual testing, which was previously limited to 8 hours per day, significantly increased to 24 hours per day, allowing continuous testing without human intervention. The number of test cases handled increased from 7 cases per day to 63 cases per day, indicating a significant improvement in efficiency. The number of test steps also  increased from 328 steps per day to 2952 steps per day. The implementation of RPA also positively impacted accuracy by reducing human errors that frequently occur in manual testing. Overall, this study demonstrates that the application of RPA in testing applications at AMF Finance significantly improves the capacity, efficiency, and accuracy of the application testing process.