机器学习算法在中小企业信用风险评估中的应用研究

CONVERTER Pub Date : 2021-07-10 DOI:10.17762/converter.220
Huichao Mi
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引用次数: 1

摘要

受新冠肺炎疫情影响,中小企业尤其是制造业面临更大的资金压力,出现不良贷款的可能性越来越大。金融机构在为中小企业提供金融支持的同时降低金融风险,对促进产业发展和经济复苏具有十分重要的意义。为了了解机器学习算法在企业信用风险预测中的作用,本研究设计了Logistic回归、决策树、Naïve贝叶斯、支持向量机和深度神经网络5个模型,并采用SMOTE和欠采样对不平衡数据进行处理。实验表明,机器学习算法对大规模数据和小规模数据都有很高的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the Application of Machine Learning Algorithms in Credit Risk Assessment of Minor Enterprises
Under the influence of COVID-19, minor enterprises, especially the manufacturing industry, are facing greater financial pressure and the possibility of non-performing loans is increasing. It is very important for financial institutions to reduce financial risks while providing financial support for minor enterprises to promote industrial development and economic recovery. In order to understand the function of machine learning algorithms in predicting enterprise credit risk, the research designs five models, including Logistic Regression, Decision Tree, Naïve Bayesian, Support Vector Machine and Deep Neural Network, and adopts SMOTE and Undersampling to process imbalanced data. Experiments show that machine learning algorithms have high accuracy for both large-scale data and small-scale data.
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