A Critical Significance of Using Machine Learning in Strengthening Financial Risk Management in Banking Firms

Johri, Shiva; Khan, Naila Iqbal; Mehta, Kamakshi; Othman, Bestoon; Waghmare, Sushant; Pant, Bhasker

doi:10.1109/icacite53722.2022.9823653

Cited by 5 publications

(1 citation statement)

References 16 publications

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“…The ML algorithms in the studies conducted in [39][40][41][42][43][44] are among the best AI solutions for the financial industry. Prominent machine learning methods are connected to financial risk and a taxonomy of financial risk management responsibilities, creating a framework for effective risk management strategies.…”

Section: Approachmentioning

confidence: 99%

The Artificial Intelligence Revolution in Digital Finance in Saudi Arabia: A Comprehensive Review and Proposed Framework

Al-Baity

2023

Sustainability

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Artificial Intelligence (AI) has proliferated in the last few years due to the vast data we pro-duce daily and available computing power. AI can be applied in many different sectors, such as transportation, education, healthcare, banking, and finance, among many others. The financial industry is rapidly embracing AI due to its potential for high-cost savings in financial services. AI could transform the financial sector by creating opportunities for tailored, faster, and more cost-effective services. Saudi Arabia is emerging as a fast-growing market in this industry with a strong commitment to technology-driven institutions. While AI is gaining prominence and receiving government support, it has not yet become a critical component for enhancing the efficiency of financial transactions. Limited published research on AI adoption in the Saudi Arabian financial industry calls for a comprehensive literature review to examine the current state of AI implementation in this sector. Therefore, this study explores the benefits, limitations, and challenges of leveraging AI in finance, highlighting the importance of ethical and regulatory considerations for successful AI adoption in the sector. This study’s findings reveal that research has been conducted on how AI improves processes in the financial sector by integrating critical components and efficient algorithms tailored to the industry’s needs. Based on these findings, this study proposes a sequential framework at the macro and micro levels of management to guide AI’s development and integration into the financial sector. Additionally, the framework draws insights from the existing literature to provide a detailed understanding of opportunities, challenges, and areas for improvement to maximize AI’s potential in the Saudi Arabian financial sector.

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