Sarah Hammer, an adjunct professor at the University of Pennsylvania Carey Law School and executive director of financial technology programs at the Wharton School, wrote the following opinion piece. The first place it appeared was MarketWatch.
Generative AI is a new technology that the financial services sector can employ to transform financial advice.
Generative AI tools are revolutionizing financial advice by integrating personal data, user preferences, and economic insights, transforming the traditional process of human advisers and enabling them to handle everything from retirement savings to financial planning.
These technologies can improve forecasts, maximize efficiency, and improve customer communication, whether they are used directly by investors or in conjunction with advisers. However, the sector needs to thoroughly analyze the ramifications before embracing AI-generated financial advice.
Alphabet CEO Sundar Pichai believes that investing in AI is worth it, but not all investors agree. The recent tech stock fall highlights the need for AI-related companies to demonstrate increased revenues, reduced costs, and productivity. Businesses must evaluate and project return on investment for AI initiatives to ensure value for both businesses and clients.
Hallucinations can happen when generative AI technologies provide inaccurate or deceptive information, which raises concerns about AI safety. Not all AI financial advice improves over time, and some tools may produce minor inaccuracies or even serious misleading information. The Mata v. Avianca case in New York illustrates this issue, where an attorney used ChatGPT for legal research and was found to have bogus internal citations and quotes, leading to severe legal and disciplinary consequences.
A 2023 study found that AI-generated advice can amplify gender and racial stereotypes, as it relies on a set of data. This bias can lead to discriminatory treatment of individuals or groups in the AI model’s outputs, as the model’s training data may be biased, affecting the accuracy of its advice.
A 2023 study found that AI-generated advice can amplify gender and racial stereotypes, as it relies on a set of data. This bias can lead to discriminatory treatment of individuals or groups in the AI model’s outputs, as the model’s training data may be biased, affecting the accuracy of its advice.
The potential advantages of using AI in financial advice outweigh these difficulties. Both individuals and advisors can take certain actions to responsibly traverse this new terrain.
To evaluate the value of AI-based financial advice, investors should compare it to existing tools or human advisers. Advisers should project the cost reduction and added benefit of using generative AI tools and prioritize AI efforts with the most significant and tangible benefits.
AI-based financial advice should involve a human, as it may not be suitable for all situations. Hallucinations and inquiries concerning the operation of the advising model should be avoided by advisers. They should also monitor for potential issues and stay updated on the development of generative AI.
To address bias in AI-based advice, ensure your advice application has robust guardrails, including strong AI governance, data governance, and regulatory compliance, although no single solution can eliminate it entirely.
AI governance involves establishing policies for AI development, including bias assessment, ethics, privacy practices, and information integrity. Data governance enhances data accuracy and consistency, controls access, and optimizes system architecture for accessibility. Both policies aim to maintain the integrity of information presented by AI and data, ensuring a secure and efficient system.
AI-based models should be licensed, registered, and compliant for advisers to enhance their practice. Robo-advisors must comply with securities laws and fiduciary obligations, including the 1940 Investment Advisers Act. The SEC has proposed similar rules for AI-based advice models and users, including requiring broker-dealers and investment advisers to address conflicts of interest associated with predictive data analytics. Despite their automated services, roboadvisors must adhere to these regulations to ensure their compliance.
AI-powered financial advice is a significant force in the investment industry, but its full potential can be harnessed through robust AI and data governance, human oversight, and regulatory compliance. By combining algorithmic prowess with human insight, we can unlock its potential and ensure its successful and responsible adoption.
