Risk Prediction and Prevention Strategies Used by the Financial Industry Are Supported by Artificial Intelligence Technologies

With the advancement of artificial intelligence (AI) and big data technology, traditional financial management faces challenges in meeting modern needs. China's financial sector, although late to start, is embracing AI to mitigate risks like business and credit risks. This study explores risk prediction and avoidance methods in finance using AI. It employs elementary catastrophe theory to analyze dynamic system discontinuity, identifying high-risk periods when the calculated financial stress index (FSI) exceeds 1. Each unit increase in FSI affects its lag period by 0.7327 units. Macro-economic pressure, reflected in the macroeconomic pressure index (MSI), significantly impacts FSI, with the current period having a more pronounced effect than the lag period. Financial institutions must evolve talent into hybrid professionals and invest in AI to enhance risk management while pursuing profitability.

Authors

Publication Details

Journal
International Journal of e-Collaboration
Published
2024-10-26
DOI
https://doi.org/10.4018/ijec.357699
Citations
2
Primary Topic
Insurance and Financial Risk Management
Type
article
Field-Weighted Citation Impact
2.26
Controls
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article

Risk Prediction and Prevention Strategies Used by the Financial Industry Are Supported by Artificial Intelligence Technologies

Xiaowen Fu
2 citations
International Journal of e-Collaboration
Insurance and Financial Risk Management
2.26
article

Risk Prediction and Prevention Strategies Used by the Financial Industry Are Supported by Artificial Intelligence Technologies

Xiaowen Fu
article en
2 citations

Abstract

With the advancement of artificial intelligence (AI) and big data technology, traditional financial management faces challenges in meeting modern needs. China's financial sector, although late to start, is embracing AI to mitigate risks like business and credit risks. This study explores risk prediction and avoidance methods in finance using AI. It employs elementary catastrophe theory to analyze dynamic system discontinuity, identifying high-risk periods when the calculated financial stress index (FSI) exceeds 1. Each unit increase in FSI affects its lag period by 0.7327 units. Macro-economic pressure, reflected in the macroeconomic pressure index (MSI), significantly impacts FSI, with the current period having a more pronounced effect than the lag period. Financial institutions must evolve talent into hybrid professionals and invest in AI to enhance risk management while pursuing profitability.

International Journal of e-CollaborationVol. 20(1)
Openalex Percentile: Top 8%
Insurance and Financial Risk Management
2.26
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Risk Prediction and Prevention Strategies Used by the Financial Industry Are Supported by Artificial Intelligence Technologies — Xiaowen Fu · International Journal of e-Collaboration (2024) | TGRS Research Map | TGRS