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

Autor:	S. Matveevskii
Jazyk:	English<br />Russian
Rok vydání:	2019
Předmět:	big data analytics multiple regression small and medium enterprises development bank probability of default credit rating Sociology (General) HM401-1281 Economics as a science HB71-74
Zdroj:	Вестник университета, Vol 0, Iss 10, Pp 182-187 (2019)
Druh dokumentu:	article
ISSN:	1816-4277 2686-8415
DOI:	10.26425/1816-4277-2019-10-182-187
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/4e48b954b9c74f3aaf9340d1559e166c Zobrazit plný text záznamu View record in DOAJ