Review of credit risk and credit scoring models based on computing paradigms in financial institutions

被引：1

作者：

Sharma, Deepika ^{[1
]}

Vashistha, Ashutosh ^{[1
]}

Gupta, Manoj Kumar ^{[2
]}

机构：

[1] Shri Mata Vaishno Devi Univ, Sch Business, Katra 182320, Jammu & Kashmir, India

[2] Shri Mata Vaishno Devi Univ, Sch Comp Sci & Engn, Katra 182320, Jammu & Kashmir, India

来源：

JOURNAL OF CREDIT RISK | 2021年 / 17卷 / 03期

关键词：

credit risk; big data analytics; financial risk; credit default prediction; credit scoring; CRITERIA;

D O I：

10.21314/JCR.2021.006

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

Modem financial credit-disbursing institutions are characterized by fairly complex processes that struggle to improve the accuracy and predictability of credit scoring models. A bewildering array of studies have proposed methodologies to adapt big data analytics to this problem. This paper offers a brief overview of major studies and compares techniques along the following five dimensions: expected response time, threshold of input data, accuracy of output, reliability and computational overhead.

引用

页码：63 / 77

页数：15

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