Big Data Analysis Tools Combined with AHP for Improving Bank Services Sales

This paper deals with two important issues related to the decision making in the financial field: Big Data and Multicriteria Decision Making (MCDM) methods. To handle the combination between them, we apply the so-called MapReduce paradigm, which is widely deployed in big data analysis, and the Analytic Hierarchy Process (AHP), which is the most used method among the MCDM methodologies. The main gap to cover is shown in two directions; on the one hand, how big data analysis can help to overcome the limitations of methodologies such as AHP when a vast number of alternatives are present, on the other hand, we look at how MCDM methods can help big data analysis to go one step beyond, that is to say, to move from the predictive to the prescriptive analysis. To illustrate the whole approach, we show its application to a real world decision problem concerning the sale of travel insurances. Our methodology returns an accurate ranking of potential clients before being contacted by the sales agent working for a commercial bank. So it helps to the sales profession by contributing to the creation of value for customers and to the sales professionals by optimizing their functions.