PurposeAs banks handle increasingly large amounts of data, traditional systems for storing, processing and evaluating data no longer meet their needs. Big Data systems can efficiently process large volumes of diverse data types to meet organizational needs. But besides all their benefits, this technology carries several challenges that banks must face to ensure appropriate performance and to maximize the positive impact on people's lives. This study aims to analyze Big Data challenges in the Latin American banking sector and identify causal relationships among them.Design/methodology/approachThe challenges analyzed were determined based on the literature, and experts in the field evaluated the impact between them. The data collected was analyzed through fuzzy decision-making trial and evaluation of laboratory methodology.FindingsThe results identify the most relevant challenges and the relations of cause and effect among them for contributing to the resource allocation and decision-making regarding Big Data systems for bank managers. Data quality, team skills and compliance with regulations were considered the main challenges or root causes. In the interrelation analysis, the authors verified that the challenges of data share, management support and organizational structure are all impacting each other, which implies that these three challenges should be considered together, considering their impacts on the others.Originality/valueThe findings of this study are valuable for professionals in the field and present interesting directions for future research. Through the findings of this study, it is possible to focus on the most relevant challenges of the sector, improving the performance of Big Data systems in the sector and enhancing their impact on workers' and clients' reality.