JAPAN’S EXPERIENCE IN USING ANALYTICS OF BIG DATA TO REDUCE CREDIT RISK IN FINANCING SMALL AND MEDIUM ENTERPRISES

Abstract

The experience of Japanese experts in using big data analytics to reduce credit risk when financing small and medium-sized enterprises has been reviewed. Three multiple regression models were used to predict the likelihood of medium-sized enterprises default. The results of the study have showed, that the bank account model complements the financial model well, which will allow credit organizations to increase lending to medium-sized enterprises. It has been concluded, that the use of big data analytics requires the development of an information model of the subject area, which will provide a significant improvement in lending to medium-sized enterprises in Russia. The experience of the Asian Development Bank in researching the activities of medium-sized enterprises shows the practical possibility of using big data analytics by any development bank.

Keywords

• big data analytics
• multiple regression
• small and medium enterprises
• development bank
• probability of default
• credit rating