AI-Powered Predictive Analytics in Financial Forecasting: Implications for Corporate Planning and Risk Management

Authors

  • Sunil Kumar Das, Urvee Tulsyan, Shoukath TK, Venkata Subrahmanyeswara Adithya Dwadas, Sayyad Jilani, Sharath Kumar Y.

Keywords:

Corporate Strategy, Risk Management, Financial Forecasting, Predictive Analytics

Abstract

This study examines the influence of AI-powered predictive analytics on financial forecasting and its consequences for corporate strategy and risk management. Data from 300 individuals in the Delhi NCR region were acquired using a mixed-methods approach, which involved surveys and semi-structured interviews. The quantitative findings demonstrate substantial enhancements in the precision and efficiency of financial forecasting subsequent to the integration of artificial intelligence (AI), with a notable 15% augmentation in accuracy and a commendable 20% decrease in forecast errors. The ANOVA results indicate that there were consistent improvements in accuracy across different industries. Additionally, the correlation analysis reveals that there are positive associations between the adoption of AI and the use of advanced risk management strategies. Qualitative analysis uncovers the influence of artificial intelligence on corporate planning and proactive risk management. The results emphasize the capability of AI-driven predictive analytics to improve the ability of businesses to withstand and adjust to changes in a quickly changing environment.

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Published

26.03.2024

How to Cite

Sunil Kumar Das. (2024). AI-Powered Predictive Analytics in Financial Forecasting: Implications for Corporate Planning and Risk Management. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 3512–3516. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6061

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Section

Research Article