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

Journal Title: Academic Journal of Economic Studies - Year 2019, Vol 5, Issue 2

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.

Authors and Affiliations

Liliana Aurora Constantinescu, Carmina Elena Mihai

Keywords

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  • EP ID EP598420
  • DOI -
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How To Cite

Liliana Aurora Constantinescu, Carmina Elena Mihai (2019). Binary Logistic Regression Analysis: The Indicators Underlying the Granting of a High Value Personal Loan. Academic Journal of Economic Studies, 5(2), 193-200. https://europub.co.uk/articles/-A-598420