Ethical Implications of AI in Financial Services: Bias, Transparency, and Accountability

This article examines the ethical implications of artificial intelligence (AI) in financial services, focusing on issues of bias, transparency, and accountability. As AI adoption in finance grows rapidly, with 85% of institutions now using AI, it brings both tremendous benefits and significant ethical challenges. The article explores how AI can perpetuate biases in lending and credit scoring, the "black box" problem of opaque AI decision-making, and the complexities of establishing accountability for autonomous AI systems. It analyzes strategies for mitigating these issues, including developing interpretable AI models, implementing robust governance structures, and creating industry-specific ethical guidelines. The discussion highlights the critical need for evolving regulatory frameworks and ethical standards to ensure responsible AI use while harnessing its potential to transform financial services.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2024-10-06
DOI
https://doi.org/10.32628/cseit241051017
Citations
9
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
4.73
Controls
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article

Ethical Implications of AI in Financial Services: Bias, Transparency, and Accountability

Puneet Chopra
9 citations
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Ethics and Social Impacts of AI
4.73
article

Ethical Implications of AI in Financial Services: Bias, Transparency, and Accountability

Puneet Chopra
article en
9 citations

Abstract

This article examines the ethical implications of artificial intelligence (AI) in financial services, focusing on issues of bias, transparency, and accountability. As AI adoption in finance grows rapidly, with 85% of institutions now using AI, it brings both tremendous benefits and significant ethical challenges. The article explores how AI can perpetuate biases in lending and credit scoring, the "black box" problem of opaque AI decision-making, and the complexities of establishing accountability for autonomous AI systems. It analyzes strategies for mitigating these issues, including developing interpretable AI models, implementing robust governance structures, and creating industry-specific ethical guidelines. The discussion highlights the critical need for evolving regulatory frameworks and ethical standards to ensure responsible AI use while harnessing its potential to transform financial services.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 10(5)
Panjab University (IN)
Openalex Percentile: Top 5%
Ethics and Social Impacts of AI
4.73
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