Evaluation and Selection of Robotic Process Automation Platforms Using the AHP–Topsis Method: A Case Study in the Banking Industry

Abstract

Robotic Process Automation (RPA) has become a key technology for improving efficiency and accuracy in operational processes within the banking sector. However, increasing organizational complexity and regulatory demands make the selection of an appropriate RPA platform a challenging decision. This study aims to identify the most suitable RPA platform using a Multi-Criteria Decision-Making (MCDM) approach by integrating the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The evaluation framework is developed based on a hierarchical structure consisting of six main criteria and sixteen sub-criteria, including technology, cost efficiency, compliance, user experience, vendor and implementation support, as well as analytics and monitoring. Four alternatives were compared: UiPath, Automation Anywhere, Power Automate, and Kofax. The AHP weighting results indicate that compliance, technology, and cost efficiency are the most influential criteria in RPA platform selection. The TOPSIS analysis shows that Power Automate achieves the highest relative closeness value (Ci = 0.7344), followed by UiPath (Ci = 0.4604). Based on these findings, Power Automate is identified as the most suitable RPA platform for supporting banking process automation. The study recommends a hybrid RPA implementation strategy whereby Power Automate is adopted as the primary solution and UiPath is used as a complementary platform for complex automation scenarios. The results of this research are expected to serve as a basis for strategic decision-making to support the banks ongoing digital transformation.