英文标题：
《Simplifying credit scoring rules using LVQ+PSO》
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作者：
Laura Cristina Lanzarini, Augusto Villa Monte, Aurelio F. Bariviera,
  Patricia Jimbo Santana
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最新提交年份：
2017
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英文摘要：
  One of the key elements in the banking industry rely on the appropriate selection of customers. In order to manage credit risk, banks dedicate special efforts in order to classify customers according to their risk. The usual decision making process consists in gathering personal and financial information about the borrower. Processing this information can be time consuming, and presents some difficulties due to the heterogeneous structure of data. We offer in this paper an alternative method that is able to classify customers\' profiles from numerical and nominal attributes. The key feature of our method, called LVQ+PSO, is the finding of a reduced set of classifying rules. This is possible, due to the combination of a competitive neural network with an optimization technique. These rules constitute a predictive model for credit risk approval. The reduced quantity of rules makes this method not only useful for credit officers aiming to make quick decisions about granting a credit, but also could act as borrower\'s self selection. Our method was applied to an actual database of a credit consumer financial institution in Ecuador. We obtain very satisfactory results. Future research lines are exposed.
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中文摘要：
银行业的一个关键要素是对客户的适当选择。为了管理信用风险，银行专门根据客户的风险对其进行分类。通常的决策过程包括收集借款人的个人和财务信息。处理这些信息可能非常耗时，并且由于数据的异构结构而带来一些困难。我们在本文中提供了另一种方法，可以从数字和名义属性中对客户档案进行分类。我们的方法称为LVQ+PSO，其关键特征是发现一组简化的分类规则。这是可能的，因为竞争性神经网络与优化技术相结合。这些规则构成了信贷风险审批的预测模型。规则数量的减少使得这种方法不仅对信贷官员有帮助，目的是快速做出信贷发放决策，而且还可以作为借款人的自我选择。我们的方法已应用于厄瓜多尔一家信用消费金融机构的实际数据库。我们取得了非常令人满意的结果。揭示了未来的研究方向。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Risk Management        风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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一级分类：Quantitative Finance        数量金融学
二级分类：Computational Finance        计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
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