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Timing Tracing and Multidimensional Modelling Risk Assessment and Strategy Analysis of Cross-Border Flow of Financial Data based on Risk Quantification

Author(s)

Leyan Zhou

Affiliation(s)

School of Politics and Public Administration, Soochow University, Suzhou, Jiangsu, China

Abstract

In the context of accelerating digital transformation of the global economy, financial data cross-border flows are large in scale but frequent in risk events, and existing static research methods are difficult to capture the dynamic correlation of risks. This study aims to construct a dynamic risk assessment framework to provide decision support for relevant subjects. The ARIMA model, rolling time window regression and event study method are adopted to integrate the risk factors of technical, legal and political dimensions, and to construct a dual-driven early warning model and dual-cycle comparative analysis method. The results show that the framework can effectively identify the temporal fluctuation pattern of data flow and quantify the dynamic influence of risk factors and policy impact effects. The study fills the gap of quantitative assessment of cross-border data flow risk dynamics, provides methodological support and strategic references for regulators, fintech companies and multinational banks, and helps improve the risk prevention and control capability of cross-border financial data flow.

Keywords

Cross-Border Flow of Financial Data; Time Series Modelling; Dynamic Risk Assessment; Risk Quantification

References

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