Mitigating Risks for Financial Firms Using Generative AI Tools

22 Pages Posted: 23 May 2023

Date Written: May 18, 2023

Abstract

Generative AI tools have gained popularity in the financial industry, offering automation and innovative solutions. However, their usage also poses unique security risks. This article examines the potential risks associated with generative AI tools in the financial sector and proposes mitigation strategies for businesses. The industry faces security concerns such as intellectual property infringement, offensive or discriminatory content generation, and data breaches. To mitigate these risks, financial firms should employ generative AI tools on closed networks, use secure training data, implement robust security measures, provide employee training, and actively monitor the output. They should establish governance frameworks, employ anomaly detection techniques, incorporate external data sources, and validate the generated content. Partnering with trusted vendors and collaborating with regulatory bodies and industry associations can also enhance security. Additionally, the risk of financial fraud and manipulation should be addressed through strong governance frameworks, advanced algorithms, expert validation, robust cybersecurity measures, and continuous monitoring. While hallucinations present challenges, businesses can mitigate them by using high-quality training data, well-designed model architectures, data cleaning, and regular monitoring. By implementing these strategies, financial firms can leverage the benefits of generative AI tools while safeguarding against security risks. Proper education, industry collaboration, and adherence to standards ensure responsible and secure use of generative AI in the financial industry.

Keywords: artificial intelligence, financial services, risk mitigation, prompting, financial analysis

JEL Classification: C61, G17, G18, K42

Suggested Citation

Krause, David, Mitigating Risks for Financial Firms Using Generative AI Tools (May 18, 2023). Available at SSRN: https://ssrn.com/abstract=4452600 or http://dx.doi.org/10.2139/ssrn.4452600

David Krause (Contact Author)

Marquette University ( email )

College of Business Administration
P.O. Box 1881
Milwaukee, WI 53201-1881
United States

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