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Assessing credit risk of mortgage lending using MACBETH: a methodological framework

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Purpose ‐ Considered the largest investment for most households, buying a house requires careful and transparent analysis by all parties involved in the transaction. The aim of this paper is to propose a methodological framework allowing for the readjustment of trade-offs among risk evaluation criteria, considered of extreme importance in the lending decision process of mortgage loans. Design/methodology/approach ‐ Multiple criteria decision analysis (MCDA) has proved over the years to be effective and versatile in handling compensations among criteria. Measuring attractiveness is applied by a categorical based evaluation technique (MACBETH) to a pre-established structure of credit-scoring criteria for mortgage lending risk evaluation. This pre-established structure is currently used by one of the largest banks in Portugal. Findings ‐ The framework allowed the authors to provide the credit experts who participated in the study with a more informed, transparent and accurate mortgage-lending risk-evaluation system. The sensitivity and robustness analyses carried out also helped in promoting discussion and supporting the readjustments made. Research limitations/implications ‐ The study shows the usefulness of using the MACBETH approach to assist credit analysts in making better informed decisions, and opens avenues for further research. However, due to the dependence on the participants involved, extrapolations without proper caution are discouraged. Practical implications ‐ The credit analysts who participated in this study considered the framework more discerning in terms of Basel directives. Originality/value ‐ The integration of MACBETH and credit-scoring mechanisms holds great potential for risk assessment and decision support. No prior work reporting the application of MACBETH in terms of mortgage-lending risk-evaluation is known.
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Keywords: Credit-scoring; Decision making; MCDA; Macbeth; Mortgage lending; Risk assessment

Document Type: Research Article

Publication date: 2014-03-11

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