A Novel Contending Risks Method for Calculating Prepayment and Default Utilizing Data Mining

Authors

  • Dr. S. Audithan  Principal, Sri Aravindar Engineering College, Sedarapet, Villupuram District, India

Keywords:

Microfinance, Data Mining, Contending Risks Method, Prepayment, Default, Logistic Regression.

Abstract

With the change of financial condition, microfinance has turned out to be progressively dynamic. Be that as it may, the quick development of it has numerous potential dangers caused by imperfect improvement, which prompts management emergency confronted by monetary organizations and even in risk of fall. In this way, money related establishments ought to distinguish the borrowers' credit hazard effectively and receive chance control technique to diminish the misfortunes and maximize the advantages. This examination built a contending dangers model to foresee default and prepayment in the meantime by utilizing Logistic Regression. The outcomes can be the administration premise of advance business executed by financial institutions.

References

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International Journal of Scientific Research in Science and Technology

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Published

2017-08-30

Issue

Volume 3, Issue 6, July-August-2017

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. S. Audithan, " A Novel Contending Risks Method for Calculating Prepayment and Default Utilizing Data Mining, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 6, pp.651-653, July-August-2017.