Recommendation System Development for Potential Factoring Service Customer Identification

Today, an extremely urgent problem is Big Data handling, namely the processing and monetization of information accumulated by banks and other financial institutions over the past decades. The business goal of this work is due precisely to this tendency. The business goal is to create a recommendation system for potential factoring service customer identification on the basis of the information contained in the databases of the largest Russian banks. To achieve this goal, the financial statements of many companies from different industries and market segments were analyzed, which resulted in the identification of key economic indicators that most accurately reflect the client’s need for factoring. The results formed the basis for building a recommendation system, which allowed to increase the efficiency of sales staff by 20% or more percent. The algorithm is implemented in a simple and extremely common programming language VBA, which is used in freely distributed open source software, thus providing a competitive advantage over existing solutions on the market and can be easily translated into another programming language. Keywords: factoring, recommendation systems, IFRS, cluster.