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

Authors

  • Puneet Chopra Panjab University, India Author

DOI:

https://doi.org/10.32628/CSEIT241051017

Keywords:

AI in Finance, Ethical Implications, Bias Mitigation, Transparency, Accountability

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.

Downloads

Download data is not yet available.

References

Cambridge Centre for Alternative Finance and World Economic Forum, "Transforming Paradigms: A Global AI in Financial Services Survey," 2020. [Online]. Available: https://www.jbs.cam.ac.uk/faculty-research/centres/alternative-finance/publications/transforming-paradigms/

World Economic Forum, "The New Physics of Financial Services – How artificial intelligence is transforming the financial ecosystem," 2022. [Online]. Available: https://www3.weforum.org/docs/WEF_New_Physics_of_Financial_Services.pdf

Autonomous NEXT, "Augmented Finance & Machine Intelligence," 2018. [Online]. Available: https://www.smallake.kr/wp-content/uploads/2018/08/AutonomousNEXT_06_MachineIntelligenceAugmentedFinance.pdf

R. Bartlett, A. Morse, R. Stanton, and N. Wallace, "Consumer-Lending Discrimination in the FinTech Era," National Bureau of Economic Research, Working Paper No. 25943, 2019. [Online]. Available: https://www.nber.org/papers/w25943 DOI: https://doi.org/10.3386/w25943

Consumer Financial Protection Bureau, "Data Point: Credit Invisibles," 2015. [Online]. Available: https://files.consumerfinance.gov/f/201505_cfpb_data-point-credit-invisibles.pdf

FICO and Corinium, "State of Responsible AI in Financial Services," 2021. [Online]. Available: https://www.fico.com/en/latest-thinking/analystpartner-collateral/state-of-responsible-ai-in-financial-services

Deloitte, "AI Leaders in Financial Services: Common traits of frontrunners in the artificial intelligence race," 2019. [Online]. Available: https://www2.deloitte.com/content/dam/insights/us/articles/4687_traits-of-ai-frontrunners/DI_AI-leaders-in-financial-services.pdf

European Banking Authority, "Report on Big Data and Advanced Analytics," 2020. [Online]. Available: https://www.eba.europa.eu/sites/default/documents/files/document_library/Final%20Report%20on%20Big%20Data%20and%20Advanced%20Analytics.pdf

Financial Stability Board, "Artificial intelligence and machine learning in financial services," 2017. [Online]. Available: https://www.fsb.org/wp-content/uploads/P011117.pdf

Downloads

Published

01-11-2024

Issue

Section

Research Articles

Similar Articles

1-10 of 256

You may also start an advanced similarity search for this article.