Readjusting trade-offs among criteria in internal ratings of credit-scoring: an empirical essay of risk analysis in mortgage loans

Credit-scoring becomes increasingly important in poor economies and recessions. Decreasing liquidity due to reduced access to both money and debt markets has induced banks to impose restrictions on offering credit, including credit for mortgage loans. In this paper we analyze the internal rating system used by one of the top-five banks in Portugal, and propose a methodological framework which, based on an application of the Delphi technique, allows adjusting trade-offs among evaluation criteria and provides decision makers with a fairer, more accurate and transparent mortgage risk evaluation system.

[1]  Lyn C. Thomas.  Modelling the credit risk for portfolios of consumer loans: Analogies with corporate loan models , 2009, Math. Comput. Simul..

[2]  Kin Keung Lai,et al.  An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring , 2009, Eur. J. Oper. Res..

[3]  N. Dalkey,et al.  An Experimental Application of the Delphi Method to the Use of Experts , 1963 .

[4]  Fernando Alberto Freitas Ferreira,et al.  A snapshot of the Portuguese e-banking activity: insights and a conceptual framework to allocate strategic hindrances , 2011, Int. J. Electron. Bus..

[5]  Arnoldina Pabedinskaitė,et al.  Application of forecasting methods in business , 2003 .

[6]  Fernando A. F. Ferreira,et al.  Adding value to bank branch performance evaluation using cognitive maps and MCDA: a case study , 2011, J. Oper. Res. Soc..

[7]  Jian Ma,et al.  A comparative assessment of ensemble learning for credit scoring , 2011, Expert Syst. Appl..

[8]  Martin Weber,et al.  The Role of Non-Financial Factors in Internal Credit Ratings , 2005 .

[9]  C. Zopounidis,et al.  Assessing financial risks using a multicriteria sorting procedure: the case of country risk assessment , 2001 .

[10]  Alexander Suhobokov.  Application of Monte Carlo simulation methods in risk management , 2007 .

[11]  A. Saunders,et al.  Credit risk measurement: Developments over the last 20 years , 1997 .

[12]  Irena Macerinskiene,et al.  The evaluation model of a commercial bank loan portfolio , 2008 .

[13]  Jose A. Lopez,et al.  Evaluating Credit Risk Models , 1999 .

[14]  R. Avery,et al.  Consumer Credit Scoring: Do Situational Circumstances Matter? , 2004 .

[15]  Huseyin Ince,et al.  A comparison of data mining techniques for credit scoring in banking: A managerial perspective , 2009 .

[16]  Bhekisipho Twala,et al.  Multiple classifier application to credit risk assessment , 2010, Expert Syst. Appl..

[17]  Jonathan N. Crook,et al.  Recent developments in consumer credit risk assessment , 2007, Eur. J. Oper. Res..

[18]  Constantin Zopounidis,et al.  Credit risk assessment using a multicriteria hierarchical discrimination approach: A comparative analysis , 2002, Eur. J. Oper. Res..

[19]  Samuel DiGangi,et al.  Assessing unidimensionality: A comparison of Rasch modeling, Parallel analysis, and TETRAD , 2007 .