Assessing factors of behavioral intention to use Big Data Analytics (BDA) in banking and insurance sector: proposition of an integrated model

Abstract

Banking and insurance sectors have long been largely data-driven by nature. However, with the rise in the predominance of data flooding from several sources resulting from the introduction of new customers and markets, with the help of Big Data Analytics, value can be extracted more effectively, and analysis of this type of unstructured data combined with a wide range of datasets can be used to efficiently and precisely extract commercial value. The aim of this paper is to develop a conceptual framework to explain the intention of information technology practitioners in banks and insurance companies to use Big Data Analytics by exploiting the Technology Acceptance Model (TAM) joined by the Task-Technology-Fit paradigm, information quality, security, trust, and the moderating effect of managerial commitment by top management on the relationship between users’ perception and their intention to use, in order to conceptualize and test an integrated framework for analyzing and measuring attitudes toward the usage of Big Data Analytics.

This paper contributes by proposing the model to assess the factors that influence users’ intention towards the use of Big Data Analytics, by asserting users’ perception towards the technology, trust factor, security and the effect of managerial commitment. Although the model we developed in this paper is conceptual and still needs to be tested empirically, it will serve as a basic framework for further research that is designed to evaluate factors affecting IT practitioners’ attitudes towards the adoption of Big Data Analytics within the finance sector.

Keywords: Big Data Analytics, TAM, TTF, Security, Trust, Managerial commitment, Bank, Insurance 

JEL Classification: O32

Paper type: Theoretical Research