Statistical Methods for Banking Sectors to Detect the Eligible Customers for Home Loan
1Sujatha. V, Assistant Professor, Department of Mathematics, VIT University, Vellore, India.
2Kalpanapriya. D, Assistant Professor, Department of Mathematics, VIT University, Vellore, India.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1849-1853 | Volume-8 Issue-4, November 2019. | Retrieval Number: A3115058119/2019©BEIESP | DOI: 10.35940/ijrte.A3115.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Nowadays people are interested to avail loans in banks for their needs, but providing loans to all people is not possible to banks, so they are using some measures to identify eligible customers. To measure the performance of categorical variables sensitivity and specificity are widely used in Medical and tangentially in econometrics, after using some measures also if banks provide the loans to the wrong customers whom might not able to repay the loans, and not providing to customers who can repay will lead to the type I errors and type II errors, to minimize these errors, this study explains one, how to know sensitivity is large or small and second to study the bench marks on forecasting the model by Fuzzy analysis based on fuzzy based weights and it is compared with the sensitivity analysis.
Keywords: Sensitivity Analysis, Specificity Analysis, Triangular Fuzzy Number, True Positive, True Negative.
Scope of the Article: Internet and Web Applications.