Open AccessResearch on risk assessment of clients before loan based on decision tree algorithm
Author(s) -
Yongkai Wang,
Ditao Duan
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1774/1/012056
Subject(s) - loan , decision tree , risk assessment , risk management , computer science , tree (set theory) , random forest , sustainable development , actuarial science , credit risk , business , risk analysis (engineering) , algorithm , finance , machine learning , mathematics , mathematical analysis , computer security , political science , law
How to transform credit funds into the endogenous development capacity of the market and promote the sustainable development of the economy, the first consideration is how to conduct risk management. How to do a good job in risk assessment has gradually become an important part of current financial risk management. This paper uses the decision tree algorithm to conduct a research on the risk assessment of customers before loan. After the model verification of the cross-validation method and the random validation method, the results show that the risk estimation accuracy of the decision tree algorithm reaches 81.2% and 83.6%, which proves that this model can be an effective reference for pre-loan risk assessment.