Application of Artificial Intelligence Technology for Digital Economy: Research on Default Factors of Personal Automotive Consumer Credit

With the continuous development of the digital economy, the automotive finance market continues to expand, generating a large amount of customer information data. The traditional method of manually identifying default risk is costly, inefficient, and prone to errors. This article utilizes artificial intelligence technology and credit management knowledge to mine factors that affect the default risk of personal automobile consumer credit from massive data, aiming to reduce manual screening costs and improve loan decision-making efficiency. This study used data from a certain car loan platform, modeled it using the LightGBM model, and evaluated and optimized the model using confusion matrix and ROC curve to ultimately determine the top ten important factors affecting default risk.