Transforming Banking with Artificial Intelligence

Purpose of the article: The purpose of this article is to provide a comprehensive analysis of the role of artificial intelligence (AI) in the banking sector, focusing on its applications, challenges, and implications. By synthesizing existing research and empirical studies, the article aims to inform researchers about the transformative potential and inherent challenges of AI-driven innovation in banking. Methodology/methods: Using a systematic review approach, the relevant literature on AI integration in banking was identified from electronic databases and leading corporate research departments, ensuring a synthesis of scholarly and industry perspectives. Scientific aim: With limited academic research on AI in banking, this study aims to shed light on its applications, challenges, and implications. Findings: The integration of AI in the banking sector has significantly transformed various operational areas, including customer interactions, risk management, compliance, and operational efficiency. AI applications, such as chatbots and smart virtual assistants, have enhanced customer service by offering personalized, 24/7 support, and have demonstrated significant cost and revenue benefits. AI-driven credit scoring and fraud detection have improved risk assessment and mitigation, enabling more precise and informed decision-making. However, AI adoption faces challenges such as high computational costs, data quality issues, the "curse of recursion" where models trained on AI-generated data degrade, and the need to balance trust in AI outputs with their reliability. Furthermore, regulatory considerations play a crucial role in AI integration. While the European Union's AI Act aims to ensure the ethical use of AI in finance, it also presents challenges related to compliance and potential over-regulation. Conclusions: In conclusion, the integration of AI in the banking sector has revolutionized customer service, risk management, compliance, and operational efficiency. However, the adoption of AI also raises concerns about data privacy, security, and the need for regulatory frameworks to ensure ethical use. As AI continues to evolve, it will be crucial for banks to balance technological innovation with responsible practices to maximize benefits and mitigate risks.

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Publication Details

Journal
Trends Economics and Management
Published
2024-08-31
DOI
https://doi.org/10.13164/trends.2024.42.21
Citations
9
Primary Topic
Insurance and Financial Risk Management
Type
article
Field-Weighted Citation Impact
10.16
Controls
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article

Transforming Banking with Artificial Intelligence

Monika Mucsková
9 citations
Trends Economics and Management
Insurance and Financial Risk Management
10.16
article

Transforming Banking with Artificial Intelligence

Monika Mucsková
article en
9 citations

Abstract

Purpose of the article: The purpose of this article is to provide a comprehensive analysis of the role of artificial intelligence (AI) in the banking sector, focusing on its applications, challenges, and implications. By synthesizing existing research and empirical studies, the article aims to inform researchers about the transformative potential and inherent challenges of AI-driven innovation in banking. Methodology/methods: Using a systematic review approach, the relevant literature on AI integration in banking was identified from electronic databases and leading corporate research departments, ensuring a synthesis of scholarly and industry perspectives. Scientific aim: With limited academic research on AI in banking, this study aims to shed light on its applications, challenges, and implications. Findings: The integration of AI in the banking sector has significantly transformed various operational areas, including customer interactions, risk management, compliance, and operational efficiency. AI applications, such as chatbots and smart virtual assistants, have enhanced customer service by offering personalized, 24/7 support, and have demonstrated significant cost and revenue benefits. AI-driven credit scoring and fraud detection have improved risk assessment and mitigation, enabling more precise and informed decision-making. However, AI adoption faces challenges such as high computational costs, data quality issues, the "curse of recursion" where models trained on AI-generated data degrade, and the need to balance trust in AI outputs with their reliability. Furthermore, regulatory considerations play a crucial role in AI integration. While the European Union's AI Act aims to ensure the ethical use of AI in finance, it also presents challenges related to compliance and potential over-regulation. Conclusions: In conclusion, the integration of AI in the banking sector has revolutionized customer service, risk management, compliance, and operational efficiency. However, the adoption of AI also raises concerns about data privacy, security, and the need for regulatory frameworks to ensure ethical use. As AI continues to evolve, it will be crucial for banks to balance technological innovation with responsible practices to maximize benefits and mitigate risks.

Trends Economics and ManagementVol. 18(42)
School of Business and Management (FR)
Openalex Percentile: Top 2%
Insurance and Financial Risk Management
10.16
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