Binary Logistic Regression Analysis: The Indicators Underlying the Granting of a High Value Personal Loan

Constantinescu Liliana Aurora () and Mihai Carmina Elena ()

Academic Journal of Economic Studies, 2019, vol. 5, issue 2, 193-200

Abstract: All clients requesting loan for personal needs in credit institutions are included in certain groups with different default risk. In this respect, banks use a number of quantitative and qualitative indicators to categorize credit applicants in risk categories based on prudence, credibility and solvency. However, many institutions do not have a clear picture of the consumer's importance to these indicators, especially in terms of access to high value credits. Therefore, we present the results of a study aimed at identifying consumer opinions on the influence of the indicators underlying the granting of a high value personal credit, which was performed (n = 102) among the population in Brasov, over 18, in June 2019. The study results indicate the type of income, the amount of the customer's and beneficiary's income, the location, the length of residence, the length of service, the age and the field in which they operate are factors taken into account by banks and non-personal needs of high value.

Keywords: Bank customers, loan, institution; customer income type; Amount of customer and co-payee revenue; customer's location; residence duration at the same address of the customer; customer seniority; information included in the Credit Bureau (BC) databases (search for similar items in EconPapers)
JEL-codes: G21 M31 (search for similar items in EconPapers)
Date: 2019
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