Avaliação do impacto do desempenho de uma cooperativa de crédito através da automação por RPA

Abstract

This study analyzes the impact of implementing Robotic Process Automation (RPA) and Business Process Management (BPM) on the operational performance of Brazilian credit cooperatives, focusing on credit granting processes. The research problem lies in the inefficiency of manual activities related to credit analysis, registration, and approval, characterized by excessive processing time, high error rates, and elevated operational costs, which undermine the competitiveness of these institutions compared to digital banks and fintechs. The main objective was to evaluate, through real case analyses, the quantitative and qualitative impacts of automation on these critical processes, identifying benefits, challenges, and key success factors. The methodology is applied, exploratory, and descriptive in nature, with a mixed qualitative–quantitative approach, using multiple case studies and document analysis of cooperatives that implemented automation solutions with tools such as UiPath, Python, and BPM platforms like Bizagi. The comparative analysis of pre- and postimplementation indicators revealed significant reductions in processing time and operational costs, accompanied by a notable decrease in error rates and an increase in daily processing capacity. In addition to quantitative gains, qualitative impacts were also observed, such as the strategic reallocation of human resources to activities focused on relationship management and analytical decision-making, reinforcing the cooperative principles of personalized and human-centered service. The study concludes that automation through RPA and BPM represents an effective strategy for improving operational efficiency and competitiveness in credit cooperatives, while proposing practical guidelines for adopting these technologies across diverse cooperative contexts.