ABSTRACT
Mortgage lending strengthens countries’ economies, contributing to their development and economic growth. For this to occur, a financial commitment is required between credit institutions that transfer credit and the individuals who request it. This relationship is usually supported by risk analysis and assessment tools that seek to anticipate the success or failure of credit lending and thereby protect both parties. Given the growing demand for more realistic and informed credit risk assessment mechanisms, the present study sought to create a multiple criteria credit risk assessment system for mortgage loans using cognitive maps and the Measuring Attractiveness by a Categorical Based Evaluation Technique. Despite the idiosyncratic nature of this study, the results show that this methodological combination allows for a more transparent and realistic mortgage risk assessment. The advantages and limitations of the proposed approach are also discussed.
Acknowledgments
Records of the expert panel meetings, including pictures, software outputs and non-confidential information of the study can be obtained from the corresponding author upon request. The authors gratefully acknowledge the superb contribution of the expert panel members: Alexandre Tendinha, Conceição Mendes, Fernando Chau, Marco Almeida, Miguel Cafum, Rute Marreiros and Teresa Pires.
Disclosure statement
No potential conflict of interest was reported by the authors.