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

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, th...

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Main Author: S. Matveevskii
Format: Article
Language:English
Published: Publishing House of the State University of Management 2019-11-01
Series:Вестник университета
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Online Access:https://vestnik.guu.ru/jour/article/view/1806
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author S. Matveevskii
author_facet S. Matveevskii
author_sort S. Matveevskii
collection DOAJ
description 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.
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series Вестник университета
spelling doaj-art-4e48b954b9c74f3aaf9340d1559e166c2025-02-04T08:28:01ZengPublishing House of the State University of ManagementВестник университета1816-42772686-84152019-11-0101018218710.26425/1816-4277-2019-10-182-1871533JAPAN’S EXPERIENCE IN USING ANALYTICS OF BIG DATA TO REDUCE CREDIT RISK IN FINANCING SMALL AND MEDIUM ENTERPRISESS. Matveevskii0Financial University under the Government of the Russian FederationThe 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.https://vestnik.guu.ru/jour/article/view/1806big data analyticsmultiple regressionsmall and medium enterprisesdevelopment bankprobability of defaultcredit rating
spellingShingle S. Matveevskii
JAPAN’S EXPERIENCE IN USING ANALYTICS OF BIG DATA TO REDUCE CREDIT RISK IN FINANCING SMALL AND MEDIUM ENTERPRISES
Вестник университета
big data analytics
multiple regression
small and medium enterprises
development bank
probability of default
credit rating
title JAPAN’S EXPERIENCE IN USING ANALYTICS OF BIG DATA TO REDUCE CREDIT RISK IN FINANCING SMALL AND MEDIUM ENTERPRISES
title_full JAPAN’S EXPERIENCE IN USING ANALYTICS OF BIG DATA TO REDUCE CREDIT RISK IN FINANCING SMALL AND MEDIUM ENTERPRISES
title_fullStr JAPAN’S EXPERIENCE IN USING ANALYTICS OF BIG DATA TO REDUCE CREDIT RISK IN FINANCING SMALL AND MEDIUM ENTERPRISES
title_full_unstemmed JAPAN’S EXPERIENCE IN USING ANALYTICS OF BIG DATA TO REDUCE CREDIT RISK IN FINANCING SMALL AND MEDIUM ENTERPRISES
title_short JAPAN’S EXPERIENCE IN USING ANALYTICS OF BIG DATA TO REDUCE CREDIT RISK IN FINANCING SMALL AND MEDIUM ENTERPRISES
title_sort japan s experience in using analytics of big data to reduce credit risk in financing small and medium enterprises
topic big data analytics
multiple regression
small and medium enterprises
development bank
probability of default
credit rating
url https://vestnik.guu.ru/jour/article/view/1806
work_keys_str_mv AT smatveevskii japansexperienceinusinganalyticsofbigdatatoreducecreditriskinfinancingsmallandmediumenterprises