An Empirical Case of a Context-Aware Mobile Recommender System in a Banking Environment

Abstract

Traditional E-Commerce applications have evolved in the last years due to the growth of the mobile environment, creating a new research area known as U-Commerce. The application of these techniques in the banking environment has been a direct outcome in order to enhance the services offered to end users. In this paper, we present a context-aware mobile recommender system based on real banking data provided by a well known Spanish bank. The data were composed by customer profiles, credit card transactions and information about places where bank clients have previously spent their money. The system model and its architecture are described taking into account social, mobility and ubiquitous requisites to generate personalized recommendations. The mobile prototype deployed in the bank was evaluated in a survey among 100 users with good results regarding trust, usefulness and effectiveness.