基于logistic回归的信用反欺诈预测模型

随着时代的飞速发展,互联网离我们的生活越来越近。互联网可以说是一把双刃剑,即带来了更加便捷的网络金融服务;又带来了如信用卡盗刷,电信诈骗,网络钓鱼等危害。文章基于对信用贷款业务的理解,利用银行业务数据,结合机器学习模型实现了一种基于逻辑回归算法的信用反欺诈预测模型。该模型能有效减少信用卡盗刷事件的发生,减少银行的损失;同时,该模型还能提高银行的工作效率,具有较好的工程应用价值。

Credit Anti-fraud Prediction Model Based on logistic Regression

With the rapid development of the times,the Internet is getting closer to our lives.The Internet can be said to be a double-edged sword,which brings more convenient online financial services and also brings harm such as credit card theft,telecommunications fraud,phishing,and so on.Based on the understanding of credit loan business,this paper uses bank business data and machine learning models to implement a credit anti-fraud prediction model based on logistic regression algorithm.This model can effectively reduce the occurrence of credit card fraud and reduce bank losses.At the same time,the model can also improve the bank's work efficiency and has good engineering application value.