Binary Logistic Regression Analysis: The Indicators Underlying the Granting of a High Value Personal Loan
Binary Logistic Regression Analysis: The Indicators Underlying the Granting of a High Value Personal Loan
Author(s): Liliana Aurora Constantinescu, Carmina Elena MihaiSubject(s): Business Economy / Management, Socio-Economic Research
Published by: Editura Universitară & ADI Publication
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;
Summary/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.
Journal: Academic Journal of Economic Studies
- Issue Year: 5/2019
- Issue No: 2
- Page Range: 193-200
- Page Count: 8
- Language: English
