Personal values and credit scoring: new insights in the financial prediction
研究了意大利银行客户的财务历史和人格特质，发现将心理特征加入模型能显著降低信用评分分类错误，并评估了各变量的预测重要性。
The objective of quantitative credit scoring is to develop accurate models of classification. Most attention has been devoted to deliver new classifiers based on variables commonly used in the economic literature. Several interdisciplinary studies have found that personality traits are related to financial behaviour; therefore, psychological traits could be used to lower credit risk in scoring models. In our paper, we considered financial histories and psychological traits of customers of an Italian bank. We compared the performance of kernel-based classifiers with those of standard ones. We found very promising results in terms of misclassification error reduction when personality attitudes are included in models, with both linear and non-linear discriminants. We also measured the contribution of each variable to risk prediction in order to assess importance of each predictor.