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How AI is Transforming the Investment Landscapeby@renjitphilip

How AI is Transforming the Investment Landscape

by Renjit PhilipOctober 23rd, 2023
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Generative AI is stepping in, offering more nuanced and personalized financial services. Firms like [Q.ai] offer customers investment kits picked by an AI that considers various data points, from market metrics to social media sentiment. While AI's promise is high, its performance is still under scrutiny. The human oversight in AI-driven systems is necessary to safeguard against biases.

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Dive into how AI is transforming the investment landscape

Remember the early days of robo-advisors? They were like the first smartphones—revolutionary but limited. Now, generative AI is stepping in, offering more nuanced and personalized financial services. For instance, Q.ai offers customers investment kits picked by an AI that considers various data points, from market metrics to social media sentiment.


📊 Performance Metrics

While AI's promise is high, its performance is still under scrutiny. ETF Managers Group's AIEQ, which uses IBM's Watson, has returned 4.9% over the last five years, trailing the S&P 500 index fund's 11.78%. It's like a new athlete who shows promise but has yet to win significant titles.


🛠️ Guardrails and Accountability

AI isn't given free rein. Companies like Q.ai and AIEQ (see examples below) have human oversight to monitor AI output for biases and errors. Think of it as a self-driving car with a human driver ready to take over in complex situations.


🌐 Accessibility and Inclusion

AI is democratizing financial advice. Firms like Fisdom in India use automated tools to offer financial guidance to a broader base of customers. It's like opening up an exclusive club to the general public, making high-quality advice accessible to all.


🤖 The Future: AI in the Back Office

Even if AI isn't directly advising clients, it's finding a place in back-office systems. For example, it summarizes meeting transcripts, monitors risky transactions, and generates reports.


Examples of startups / smaller companies using AI for investment management:

🤖 Q.ai

Location: Jersey City, N.J.

About: Q.ai offers no-fee "investment kits" consisting of 4 to 20 securities in a market sector. These kits are selected by an AI that evaluates market metrics, news, Google search trends, and social media sentiment.


📊 ETF Managers Group’s AIEQ

Location: Summit, N.J.

About: AIEQ uses IBM’s Watson AI platform to analyze millions of data points from various sources like news, social media, and financial statements of over 6,000 U.S. companies.


🌐 Nemo

Location: Abu Dhabi

About: Nemo uses a ChatGPT model to allow investors to ask questions they might typically ask a human broker. The company emphasizes that they don't let their AI go "off-leash."


📈 Toggle AI


Location: Not specified


About: Toggle AI aims to implement ChatGPT that will be programmatically constrained to provide reality-grounded answers to investors' questions.


🌟 Fisdom


Location: India


About: Fisdom uses automated tools to provide financial guidance to a broader base of customers, including individuals with low net-worth.


💼 Betterment

Location: New York

About: Betterment, one of the first mass-market robo-investing firms, remains cautious about using AI for financial advice. However, they do use AI in their back-office systems for tasks like summarizing meeting transcripts and diagnosing software issues.

Examples of incumbent banks using AI for investment management:

  • JPMorgan Chase: This financial giant is leveraging AI to optimize asset management and offer personalized investment solutions.
  • Morgan Stanley is using AI to enhance its asset management strategies.
  • UBS: Known for its wealth management services, UBS is adopting AI to improve its investment strategies and customer engagement.
  • HSBC: This global bank is using AI to bolster compliance and risk management functions and augment and automate data analysis in the investment sector.

🔮 Summary

  1. The integration of generative AI into investment management is a significant development, offering more personalized and nuanced services.

  2. Performance metrics are crucial for assessing the efficacy of AI-driven investment platforms, and they currently show a mixed picture.

  3. The human oversight in AI-driven systems is a necessary safeguard, ensuring that the technology does not go "off-leash."


    Whether it's automating data analysis, enhancing customer engagement, or optimizing asset management, AI is playing a pivotal role in shaping the future of investment management.


    Excerpt from One More Thing in AI Newsletter.


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