With the development of the times, the financial industry has gradually ushered in changes and formed new financial models. This article briefly explores the characteristics of AI (Artificial Intelligence) in financial risk analysis, and evaluates its application scenarios and risk analysis. Compare traditional financial risk control with AI risk control models and analyze the performance of the latter. Compared to the former with a feature count of 50, the latter has a feature count greater than 1000, making it easier to capture more detailed risk features and effectively identify complex nonlinear risk factors, thereby establishing a more accurate risk prediction model. In the study, a specific case of bank card crime was used to deeply explore and analyze the advantages, opportunities, and threats of AI in preventing bank card crime, and to propose effective prevention of bank card crime through risk prevention triggering mechanisms. This mechanism can automatically trigger warnings based on the recognition and risk harmfulness of AI, enhance human intervention, and thus achieve more efficient risk prevention and prevention. At the end of the paper, the Pathogen transmission of financial risk is evaluated. Through these achievements, we can provide certain assistance for the challenges and prevention of financial risks.

Xiaochen Liu. New Characteristics of AI Analysis of Financial Risks and their Transmission Traceability Paths. International Journal of Big Data Intelligent Technology (2023), Vol. 4, Issue 1: 42-52. https://doi.org/10.38007/IJBDIT.2023.040105.

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