  In this paper we present a novel approach to credit scoring of retail
customers in the banking industry based on deep learning methods. We used RNNs
on fine grained transnational data to compute credit scores for the loan
applicants. We demonstrate that our approach significantly outperforms the
baselines based on the customer data of a large European bank. We also
conducted a pilot study on loan applicants of the bank, and the study produced
significant financial gains for the organization. In addition, our method has
several other advantages described in the paper that are very significant for
the bank.
