MATRIX SEQUENTIAL HYBRID CREDIT SCORECARD BASED ON LOGISTIC REGRESSION AND CLUSTERING

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SADATRASOUL SEYED MAHDI

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Paper Information

Journal: Interdisciplinary Journal of Management Studies Year:2018 | Volume:11 | Issue:1 Page(s): 91-111

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Information Journal Paper

Title

MATRIX SEQUENTIAL HYBRID CREDIT SCORECARD BASED ON LOGISTIC REGRESSION AND CLUSTERING

Author(s)

SADATRASOUL SEYED MAHDI | Issue Writer Certificate

Keywords

CREDIT SCORINGQ2

BANKING INDUSTRYQ1

CREDIT SCORECARDQ1

PROFIT SCORINGQ1

MATRIX SCORECARDQ1

Abstract

The Basel II Accord pointed out benefits of credit risk management through internal models to estimate Probability of Default (PD). Banks use default predictions to estimate the loan applicants’ PD. However, in practice, PD is not useful and banks applied CREDIT SCORECARDs for their decision making process. Also the competitive pressures in lending industry forced banks to use profit scorecards, which show the profitability of customers. Applying these scorecards together makes the loan decision making process for banks more confusing. This paper has an obvious and clean solution for facilitating the confusion of loan decision making process by combining the credit and profit scorecards through introducing a matrix sequential hybrid CREDIT SCORECARD. The applicability of the introduced matrix sequential hybrid scorecard results are shown using data from an Iranian bank.

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APA: Copy

SADATRASOUL, SEYED MAHDI. (2018). MATRIX SEQUENTIAL HYBRID CREDIT SCORECARD BASED ON LOGISTIC REGRESSION AND CLUSTERING. IRANIAN JOURNAL OF MANAGEMENT STUDIES, 11(1 ), 91-111. SID. https://sid.ir/paper/240891/en

Vancouver: Copy

SADATRASOUL SEYED MAHDI. MATRIX SEQUENTIAL HYBRID CREDIT SCORECARD BASED ON LOGISTIC REGRESSION AND CLUSTERING. IRANIAN JOURNAL OF MANAGEMENT STUDIES[Internet]. 2018;11(1 ):91-111. Available from: https://sid.ir/paper/240891/en

IEEE: Copy

SEYED MAHDI SADATRASOUL, “MATRIX SEQUENTIAL HYBRID CREDIT SCORECARD BASED ON LOGISTIC REGRESSION AND CLUSTERING,” IRANIAN JOURNAL OF MANAGEMENT STUDIES, vol. 11, no. 1 , pp. 91–111, 2018, [Online]. Available: https://sid.ir/paper/240891/en

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