Over a decade ago, robo-investing services emerged with the promise of using algorithms to make and monitor investments. These robo-advisors were touted as a hassle-free alternative to traditional human advisors, offering the convenience of 24/7 service. However, the landscape is rapidly changing, thanks to the rise of generative AI. This new breed of AI can engage in open-ended conversations, giving investors the impression of interacting with a knowledgeable entity rather than a rigid algorithm.
AI’s leap into investment management
Generative AI represents a significant leap forward in investment management. Unlike traditional robo-advisors, which rely on machine learning and algorithms, generative AI harnesses deep learning algorithms. According to Suchi Mishra, an associate dean and finance professor at Florida International University, this shift to deeper learning capabilities is a game-changer.
A glimpse into AI-powered investment services
One promising example of AI in investment services is Q.ai, a new offering from Quantalytics Holdings. Q.ai provides no-fee “investment kits” composed of four to twenty securities within a specific market sector. These kits are curated by an AI system that considers various factors, including market metrics, news, Google search trends, and social media sentiment. Year-to-date returns for these kits have shown a wide range, from 52.36% for a cryptocurrency kit to -8.28% for a “Recession Resistance” offering as of July 7.
Another player in the AI investment space is ETF Managers Group’s AIEQ, powered by IBM’s Watson AI platform. AIEQ analyzes millions of data points, including news, social media, financial statements, and technical data, among others. Over the past five years, the fund has returned 4.9%, trailing behind benchmark index funds and actively managed funds.
Challenges and concerns
Despite the promise of AI-driven investing, there are challenges and concerns. Pawan Jain, an assistant professor of finance at West Virginia University, points out that AI has been a part of investing for a long time, including the role of high-frequency trading algorithms in market fluctuations. However, the real concern lies in the potential of generative AI systems to “hallucinate” or produce inaccurate information.
Setting guardrails for AI
To address these concerns, AI-powered investment services emphasize the need for human oversight. ETF Managers Group’s AIEQ, for example, monitors its AI output for signs of bias and is developing transparency tools for data inputs and investment decisions. Abu Dhabi-based startup Nemo also employs AI but ensures it remains under human supervision to prevent errors.
The quest for accountability
Holding AI systems accountable remains a challenge. Reverse-engineering AI decisions can be complex, making it difficult to identify and correct mistakes. Until the process of accountability becomes more transparent, skepticism about AI in investment management may persist.
The human touch vs. AI efficiency
Traditional robo-advisors like Betterment still prioritize human oversight. John Mileham, CTO of Betterment, emphasizes the importance of explainable and deterministic algorithms. He highlights that many AI systems, such as ChatGPT, may fall short of these properties, hindering their use in providing financial advice.
AI’s potential in financial planning
While AI may not replace human advisors entirely, it has the potential to excel in specific aspects of financial planning. It can efficiently handle repetitive tasks like answering client questions and providing personalized financial guidance. AI can also improve efficiency by continuously learning from its interactions and experiences.
Broadening access to financial guidance
AI is expanding access to financial guidance, particularly for individuals with lower net worth and those without employer-based retirement benefits. Fintech firms like Fisdom are using automated tools to provide financial advice to a broader customer base, empowering more people to invest and save for their future needs.
The integration of AI into investment management is evolving, offering both opportunities and challenges. While AI-driven investment services show promise in providing more nuanced and personalized advice, concerns about accountability and accuracy remain. As the industry continues to embrace AI, investors and firms must strike a balance between harnessing its potential and maintaining human oversight. Ultimately, AI’s role in investment management is likely to complement, rather than replace, the expertise of human advisors.
