Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/118429
Title: Credit Risk Assessment Models in Retail Business Loan Portfolio a Case Study of Delhi Financial Corporation
Researcher: Kamal Kumar Jain
Guide(s): Sanjiv Mittal and P.K. Gupta
University: Guru Gobind Singh Indraprastha University
Completed Date: 2011
Abstract: Several schemes and policies have been undertaken to provide adequate newlinecredit to Micro Small and Medium Enterprises. Of all the problems faced by newlinesuch enterprises, non-availability of timely and adequate credit at reasonable newlineinterest rate is one of the most important. The biggest impediment for the newlinegrowth of small and medium enterprises in India is the high cost of credit. It newlinehas constrained the growth and competitiveness of SMEs in the domestic newlineand global market. This was the finding of a survey conducted by the PHD newlineChamber for small and medium units located in Uttar Pradesh, Haryana, newlinePunjab, Rajasthan, Madhya Pradesh, Himachal Pradesh, J and K, Uttarakhand, newlineChhattisgarh, Chandigarh and Delhi. newlineOne of the major causes for low availability of bank finance to this sector is newlinethe high risk perception of the banks in lending to MSEs and consequent newlineinsistence on collaterals which are not easily available with these enterprises. newlineThe non-availability of funds at reasonable rates had led to an increase in the newlinecost of working capital thereby lowering the competitiveness of firms in newlinemarket place. The problem is more serious for micro enterprises requiring newlinesmall business loans and the first generation entrepreneurs. newline newlineTo evaluate the validity of model, the study has divided the data into training newlineand testing samples; 70% the data were taken as training and 30% for newlinetesting the results. The accuracy of model has been measured by newlineclassification error and prediction power has been measured by gain chart. newlineThe results obtained from training and testing samples were then crossverified newlineto see the difference in prediction. The models had shown similar newlineresults for both training and testing samples, this shows that the model newlinegenerated by training sample can be generalized to the population. newline newlineIt is expected that data mining techniques newlineshall benefit immensely the lending agencies in India in time to come newlinespecially in evolving risk assessment model for small size enterprises in newlineunorganised sector as well as MSMEs in India.
Pagination: 
URI: http://hdl.handle.net/10603/118429
Appears in Departments:University School of Management Studies

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02_certificate.pdf55.18 kBAdobe PDFView/Open
03_acknowledgement.pdf43.98 kBAdobe PDFView/Open
04_toc.pdf60.79 kBAdobe PDFView/Open
05_summary.pdf70.5 kBAdobe PDFView/Open
06_list of tables.pdf53.54 kBAdobe PDFView/Open
07_list of figures.pdf50.44 kBAdobe PDFView/Open
08_list of abbribrvation.pdf48.72 kBAdobe PDFView/Open
09_chapter-01.pdf361.86 kBAdobe PDFView/Open
10_chapter-02.pdf286.91 kBAdobe PDFView/Open
11_chapter-03.pdf419.16 kBAdobe PDFView/Open
12_chapter-04.pdf448.96 kBAdobe PDFView/Open
13_chapter-05.pdf336.09 kBAdobe PDFView/Open
14_chapter-06.pdf277.82 kBAdobe PDFView/Open
15_chapter-07.pdf303.42 kBAdobe PDFView/Open
16_chapter-08.pdf78.37 kBAdobe PDFView/Open
17_references.pdf113.59 kBAdobe PDFView/Open
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