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Using data mining approaches to build credit scoring model: Case study — Implementation of credit scoring model in microfinance institution

机译:使用数据挖掘方法来构建信用评分模式:案例研究 - 小额信贷机构中信用评分模式的实施

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The aim of this paper is to present a Credit Scoring Model applied by one Microfinance Institution in Bosnia and Herzegovina as well as to show how the most relevant attributes for its implementation were identified. The purpose of created Credit Scoring Model was to predict default clients and reduce credit risk of Microfinance Institution by applying data mining algorithm in order to find patterns for recognition of default clients and, thus, support decision making process of credit approval. Credit Scoring Model was build using Oracle Data Miner software package that uses Generalized Linear Model for classification. Created model showed great predictive confidence and accuracy, but also gave trustworthy results regarding feature selection, so the Microfinance institution decided to adopt this model as help in decision making process.
机译:本文的目的是展示波斯尼亚和黑塞哥维那一家小额信贷机构应用的信用评分模式,并展示了如何确定其实施的最相关的属性。创建的信用评分模型的目的是通过应用数据挖掘算法来预测默认客户,并降低小额信贷机构的信用风险,以便找到默认客户的识别模式,从而支持信用批准的决策过程。信用评分模型是使用Oracle数据矿工软件包构建,该软件包使用广义线性模型进行分类。创建的模型表现出巨大的预测信心和准确性,而且还有关于特征选择的值得信赖的结果,因此小额信贷机构决定采用该模型作为决策过程的帮助。

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