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Credit Scoring Process using Banking Detailed Data Store

Meera Rajan, Tulasi . B Published in Information Sciences

International Journal of Applied Information Systems
Year of Publication: 2015
© 2015 by IJAIS Journal
10.5120/ijais15-451332
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  1. Meera Rajan and Tulasi .b. Article: Credit Scoring Process using Banking Detailed Data Store. International Journal of Applied Information Systems 8(6):13-20, April 2015. BibTeX

    @article{key:article,
    	author = "Meera Rajan and Tulasi .b",
    	title = "Article: Credit Scoring Process using Banking Detailed Data Store",
    	journal = "International Journal of Applied Information Systems",
    	year = 2015,
    	volume = 8,
    	number = 6,
    	pages = "13-20",
    	month = "April",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Credit scoring process has become the current popular need of the sectors like Banking, Telecom, and Insurance. The current paper discusses credit scoring for banking Sector. It discusses about Credit Scoring for BASEL II, also to build an integrated solution for it. The framework of credit scoring solution is to enable a bank to build Analytic models for application score or Probability of Default (PD),Loss Given default(LGD), Credit Conversion Factor (CCF). The credit scoring process is integrated with the Credit Risk Management. In this paper the SAS tool named SAS E-Miner is used to perform Credit Scoring using DDS (Detailed Data Store) and SEMMA methodology is applied.

Reference

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Keywords

Credit Scoring, Logistic Regression, SEMMA, Detailed Data Store, SAS E-miner