Alhebshi, Sukainah Hasan Saleh (2026) ARTIFICIAL INTELLIGENCE RESHAPING FINANCIAL MANAGEMENT: APPLICATIONS, IMPACTS, AND OPPORTUNITIES. International Journal of Economic Integration and Regional Competitiveness, 3 (9). ISSN 3032-1301

Text IJEIRC_Artificial+Intelligence+Reshaping.pdf Download (362kB)

Abstract

Objective: This review will provide an overview of the changing nature of artificial intelligence in the realm of financial management and will focus on the applications, organizational implications, risks, governance, and future possibilities of artificial intelligence in financial management. Method: This study employs a narrative literature review approach to examine the applications, organizational implications, risks, governance, and future possibilities of artificial intelligence in financial management. Relevant literature on machine learning, deep learning, natural language processing, generative artificial intelligence, big data analytics, and cloud computing is reviewed to identify their contributions to financial automation, operational efficiency, and predictive performance. The review also examines key challenges associated with data quality, algorithmic bias, model explainability, privacy, cybersecurity, regulatory compliance, and organizational readiness. Results: The development of machine learning, deep learning, natural language processing, generative artificial intelligence, big data analysis, and cloud computing technologies has increased the ability of financial organizations to analyze complicated sets of data and derive useful insights. Based on experience with emerging uses, it is evident that AI-supported financial processes have the potential to boost operational efficiency by 20% and predictive performance by about 15%, though results depend on data quality and organizational readiness. However, with such an innovation comes the risk of several issues ranging from data quality concerns, biases in the algorithms and models, uncertainties in the model, explain ability of AI, privacy issues, cybersecurity issues, regulatory compliance issues, and over-reliance on automation. Novelty: The novelty of this study lies in integrating the technological applications of artificial intelligence with organizational readiness, financial performance improvement, risk management, and governance considerations within a comprehensive framework for intelligent financial management. Unlike studies that focus primarily on individual AI technologies or technical performance, this review connects the potential improvements in operational efficiency and predictive performance with the organizational and regulatory conditions required for successful implementation. It also highlights the importance of balancing AI-driven automation and predictive capabilities with human oversight, data quality, transparency, and responsible decision-making to support sustainable digital transformation in financial management.

Item Type:	Article
Uncontrolled Keywords:	Artificial intelligence, Financial management, Machine learning, Financial analytics, Risk management, Generative AI, Intelligent finance
Subjects:	H Social Sciences
Depositing User:	admin eprints
Date Deposited:	29 Oct 2026 15:30
Last Modified:	29 Oct 2026 15:30
URI:	http://eprints.umsida.ac.id/id/eprint/17322

Actions (login required)

View Item