The iPay project applies the data mining technique to Big Data in order to develop algorithms that allow financial intermediation in the environment of mobile cloud computing (MCC).

The aim of the project is threefold. First, we propose the design and development of graph algorithms for the analysis and detection of fraud patterns and data mining on payments. In this module we will design algorithms for the analysis of payments made by users. We will model payment data as graphs and identify behavior patterns to detect fraudulent actions performed by organized networks for money laundering, arbitration of exchange, etc. Second, we will proceed to the design of a prediction system based on a historical record of payment transactions. In this module we will design and develop algorithms to predict user behavior and identify future purchases of interest, as well as operations outside the usual casuistry which are likely to be fraudulent. Finally, for the completion of these tasks we will develop algorithms based on the state-of-the-art and will proceed to create advanced and improved versions.