BUILDING A CONCEPTUAL FRAMEWORK FOR USING BIG DATA ANALYTICS IN THE BANKING SECTOR

Abstract

Big Data and Big Data Analytics (BDA) are becoming trending technologies of the future. This topic has garnered considerable interest from researchers and businesses. However, BDA research in the banking sector has proven to be extremely limited and mixed. Addressing the challenges of BDA application and laying the foundation for BDA to improve banking efficiency raises significant questions about strategic management in the banking sector. Through a systematic review of the literature and a case study in Hungarian banks, this study intends to address the major inconsistencies in existing ideas about BDA applications. This study also proposes a conceptual model to evaluate the impact of factors influencing the use of BDA in the banking sector and investigates whether BDA affects the performance of banks. Our study finds that the use of BDA in the banking sector has to be aligned with the creation of dynamic capabilities that positively and directly affect banking in terms of the market and operational performance. Meanwhile, the dynamic capabilities created by BDA usage have a moderating impact on bank performance through improved risk management performance. Furthermore, this research helps managers focus on key factors, namely technological infrastructures, Big Data skills, data quality, and top management support, to boost the efficiency of using BDA.