A Comparative Study of Data Mining Techniques for Credit Scoring in Banking
碩士 === 淡江大學 === 資訊管理學系碩士班 === 101 === Credit is becoming one of the most important sources of income for the banking institutions. Prior studies indicated that logistic regression and neural network had been performed better on credit risk scoring. The major purpose of the present study is to propos...
Main Authors: | Shih-Chen Huang, 黃世禎 |
---|---|
Other Authors: | Min-Yuh Day |
Format: | Others |
Language: | zh-TW |
Published: |
2013
|
Online Access: | http://ndltd.ncl.edu.tw/handle/15380705741747958620 |
Similar Items
-
Applications of data mining techniques in establishing credit scoring system for the traditional industry of the SMEs
by: Luo, Hao-Chen, et al.
Published: (2009) -
A comparison of data mining techniques for credit scoring in banking: A managerial perspective
by: Huseyin Ince, et al.
Published: (2009-09-01) -
Credit scoring in banks and financial institutions via data mining techniques:
A literature review
by: Seyed Mahdi sadatrasoul, et al.
Published: (2013-04-01) -
An empirical study of using data mining techniques to credit scoring model for credit card
by: Li-Chuen Lee, et al.
Published: (2007) -
Forecasting credit rating by Using Data Mining Techniques in Taiwan Banking Industry
by: Yen-ming Huang, et al.
Published: (2012)