标题： 基于账户行为聚类分析的信用风险识别 显示英文标题

标题： Identification of Credit Risk Based on Cluster Analysis of Account Behaviours

摘要： 对现有信用账户的风险等级进行评估对于银行政策的实施和金融产品的提供非常重要。 本文使用信用卡账户行为的聚类分析来帮助评估信用风险等级。 账户行为被参数化建模，然后我们采用一种最近提出的统计模型参数的不相似性度量方法来实施行为聚类分析。 这种新度量方法的优势在于明确利用了从统计模型中估计参数所相关的不确定性。 除了基于聚类结果的账户违约的优越预测和预报外，还获得了有趣的实际信用卡行为聚类。 显示英文摘要

摘要： Assessment of risk levels for existing credit accounts is important to the implementation of bank policies and offering financial products. This paper uses cluster analysis of behaviour of credit card accounts to help assess credit risk level. Account behaviour is modelled parametrically and we then implement the behavioural cluster analysis using a recently proposed dissimilarity measure of statistical model parameters. The advantage of this new measure is the explicit exploitation of uncertainty associated with parameters estimated from statistical models. Interesting clusters of real credit card behaviours data are obtained, in addition to superior prediction and forecasting of account default based on the clustering outcomes.