International Scientific Publications
© 2022 Science Events Ltd
Terms of Use  ·  Privacy Policy
Choose language English French Russian Bulgarian
Conference room
Economy & Business 2022, 21st International Conference
22-25 August, Burgas, Bulgaria
Call for Papers

Economy & Business, Volume 11, 2017

Vesela Mihova, Velizar Pavlov
Pages: 200-208
Published: 22 Aug 2017
Views: 1,299
Downloads: 270
Abstract: Statistical models are commonly used in the banking industry in order to assess the credit risk associated with the approval of people applying for certain products (loans, credit cards, etc.). Based on data from the past, these models try to predict what will happen in the future. This work has studied the causal link between the conduct of an applicant upon payment of the loan and the data that he completed at the time of application. A linear regression is used to estimate the probability of being good for new borrowers, and a scorecard is obtained from the linear model to assess new customers in the time of application.
Keywords: credit risk, modelling, scorecards, data analysis
Cite this article: Vesela Mihova, Velizar Pavlov. AN APPROACH OF ESTIMATING THE PROBABILITY OF BEING GOOD FOR NEW BORROWERS. Journal of International Scientific Publications: Economy & Business 11, 200-208 (2017).
Download full text

Back to the contents of the volume
By using this site you agree to our Privacy Policy and Terms of Use. We use cookies, including for analytics, personalisation, and ads.