Author(s)

Hao Li

Corresponding Author

Hao Li

Abstract

The purpose of this study is to build a risk assessment and management model in inclusive finance based on big data technology, so as to improve the ability of financial institutions to identify and manage loan default risks. First of all, the paper collected a lot of data including personal loan application information, personal credit history, income, work information, etc., and preprocessed and extracted its features. Then, the paper chooses Logistic regression model as the evaluation model, and evaluates and optimizes the model by using cross-validation and other methods. The empirical analysis results show that our model performs well on the test set, with high accuracy, precision, recall rate and F1 value, and can effectively identify the risk of loan default. In addition, through the analysis of the characteristics and importance of the model, it is found that personal credit score and debt ratio have great influence on the prediction of loan default risk. To sum up, this study provides a risk assessment and management method based on big data for inclusive finance, which has important theoretical and practical significance.

Keywords

Big Data; finance Risk; Management Model; inclusive finance