Statistical Models for Credit Risk Management. Comparison Between Logit And Survival Analysis

Angel Matsanov ()
Additional contact information
Angel Matsanov: Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski / UniCredit Bulbank

Yearbook of the Faculty of Economics and Business Administration, Sofia University, 2014, vol. 12, issue 1, 139-167

Abstract: The main purpose of the article is the development and implementation of two main scoring models for segmentation and effective risk management of non-performing loans, namely: logit and survival analysis. In the current economic situation, the number of non-performing loans is growing rapidly, which implies a higher level of expenditures from collection activities and underscores the need for a model optimizing this process as a crucial part of credit risk management. The most popular statistical model in this field is the logistic regression. The goal of statistical modelling is to segment the nonperforming portfolio and to apply different collection strategies to the different segments. The strategies can be applied based on the estimated probability of early repayment of the overdue debt, the probability of long-term insolvency and so on. This peculiarity suggests the need of additional dimension offered by the survival analysis, supplying the ability to predict not only „if“, but „when“ an observed event will occur.

Keywords: Scoring models; survival analysis; logistic regression; discriminatory power; Gini coefficient; Lorenz curve. (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.feb.uni-sofia.bg/sko/yrbook/Yearbook12-09.pdf (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sko:yrbook:v:12:y:2014:i:1:p:139-167

Access Statistics for this article

More articles in Yearbook of the Faculty of Economics and Business Administration, Sofia University from Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria Contact information at EDIRC.
Bibliographic data for series maintained by Prof. Teodor Sedlarski ().