Risk Assessment System for Digital Inclusive Finance Based on Convolutional Neural Network

With the continuous development of digital inclusive finance, people’s requirements for risk assessment have become increasingly high, traditional systems can no longer meet people’s requirements. In order to improve the accuracy and efficiency of risk assessment, this paper proposes a convolutional neural network technology to construct a digital inclusive finance risk assessment system. This article is based on a convolutional neural network model and designs a digital inclusive finance risk assessment system. By collecting a large amount of customer data, including personal information, financial information, etc., the data is preprocessed and feature engineering is carried out to extract features related to risk assessment. Then a convolutional neural network model was constructed, and the collected data was used for model training and testing. After experiments, the accuracy of the algorithm in this article is $91 \%-98 \%$. The digital inclusive finance risk assessment system based on convolutional neural networks has shown high accuracy and recall in risk assessment tasks. It can accurately predict the risk level of customers, correctly divide customers into high-risk and low-risk, and help financial institutions accurately assess the credit status of customers.