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Dan's new book for millennials, Wealthier: The Investing Field Guide for Millennials, will be published on May 15, 2024, and available on Amazon.
Our profession is being transformed by powerful, AI-based technologies that will replace human-based financial advice. They will drive down costs, reduce valuations, and deflate the multiples paid in M&A transactions.
You wake up to the reports of a new competitor. He looks like George Clooney, and he has the same engaging personality. He has the combined investing and financial planning knowledge of Charlie Ellis, Jack Bogle, Bill Bernstein, Burton Malkiel, Morgan Housel, and Larry Swedroe.
He’s available 24/7, 365 days a year.
He’s sensitive, self-aware, thoughtful, and empathetic.
If he can’t answer a question or the client wants more information, he immediately refers you to an hourly CFP® in his office.
The charge to access him is modest (assume $100 per month or less for unlimited access).
Would you be concerned about this competitor?
Current technology
This technology speaks from text and uses speech recognition, natural-language processing, chatbox frameworks, and avatar animation.
It’s currently available.
Here’s how I will be using it.
I already have an avatar, which I created on the HeyGen platform. I will use that platform to create a streaming avatar. I will use large language model (LLM) technology to upload the content of my new book. Readers can interact with my avatar through voice and text and ask questions about the book. They will receive an immediate response.
It’s not much of a leap to anticipate an enterprising firm licensing content from the prominent authors listed above (or others) and uploading their books to a streaming avatar.
What about financial planning?
Here’s how AI-generated financial planning would work.
Data collection
AI-powered software can collect client data through online forms, questionnaires, or direct access to financial accounts. This data may include income, expenses, assets, liabilities, risk tolerance, and financial goals.
Financial planning algorithms
AI algorithms can analyze the client's data to create a personalized financial plan. This plan may include recommendations for savings, investments, retirement planning, tax strategies, and more.
Monte Carlo analysis
AI can perform a Monte Carlo analysis to simulate various possible future outcomes of the client's financial plan.
Plan optimization
AI can continuously optimize the financial plan based on changing market conditions, life events, and client preferences.
Client communication
AI-powered tools can communicate the financial plan to the client in a clear and easy-to-understand manner, highlighting key recommendations and potential outcomes.
AI can make the financial planning process efficient, personalized, and data-driven.
What about the “human touch”?
Would you bet against MIT?
“Affective computing” focuses on developing systems and devices that can recognize, interpret, process, and simulate human emotions. The goal of affective computing is to enable machines to interact with humans in more natural and personalized ways by understanding and responding to human emotions.
Affective computing systems use sensors, machine learning, and artificial intelligence to analyze different aspects of human emotions, like facial expressions, voice tone, gestures, and physiological signals (like heart rate and skin conductance). By examining these signals, affective computing systems can infer a person's emotional state and adapt their responses or behavior accordingly.
MIT has been a pioneering institution in affective computing, playing a significant role in its development and advancement. Several researchers at MIT have made notable contributions to the field, particularly in emotion recognition, human-computer interaction, and the development of affective computing applications.
Platforms and systems demonstrate empathetic interaction between computers and humans, showcasing the capabilities of affective computing technologies. Here are a few examples:
Woebot
Woebot is a chatbot developed by Stanford University researchers that provides users with cognitive-behavioral therapy (CBT). It uses natural language processing and machine learning to simulate a therapeutic conversation, providing empathetic responses and emotional support to users dealing with mental health issues.
Replika
Replika is an AI chatbot designed to be a personal AI friend for users. It uses machine learning algorithms to learn from users' interactions and simulate human-like conversations, including empathetic responses and emotional understanding.
Ellie
Ellie is a virtual human developed by the University of Southern California's Institute for Creative Technologies. Ellie is designed to be an empathetic interviewer for assessing mental health issues in military personnel and veterans. She uses facial expression recognition and natural language processing to engage in empathetic conversations with users.
Koko
Koko is a platform that uses AI to provide emotional support and peer counseling. It allows users to share their thoughts and feelings anonymously, and the AI provides supportive responses and encourages positive coping strategies.
Affectiva's Emotion AI
Affectiva specializes in emotion-recognition technology. It enables developers to incorporate emotion-recognition capabilities into their applications. These technologies, like virtual assistants and customer service chatbots, can create platforms demonstrating empathetic interaction between computers and humans.
Hume
Hume is a platform that uses artificial intelligence to analyze human behavior and emotions. It combines natural language processing, sentiment analysis, and other AI techniques to understand and interpret human emotions expressed in text and voice interactions.
One key feature of Hume is its ability to analyze large volumes of data from various sources, like social media, customer reviews, and surveys, to extract insights about emotions, opinions, and behavior.
Hume can also create personalized user experiences based on their emotional state. It can tailor content and recommendations to match a user's mood or emotional needs, enhancing the user experience.
Your new competitor (the George Clooney avatar) will use these technologies to full advantage.
Will “George” replace you?
No, but this service will reduce the number of clients willing to pay an AUM-based fee.
“George,” supplemented by a staff of hourly CFPs®, will be available for a fraction of that cost. This significant difference in fees will reduce revenues for traditional advisory firms as clients increasingly opt for lower-cost, AI-driven solutions.
Impact on M&A
The potential impact on revenues raises questions about the multiples paid for advisory firms in M&A transactions. If revenues are expected to decline due to lower fees, the multiples paid for these firms will be adjusted accordingly.
The paradox of M&A activity
Despite AI's disruptive potential, the financial advisory profession has witnessed a significant increase in M&A activity in recent years. This activity suggests a desire to maintain the status quo and preserve traditional business models.
Several factors contribute to this resistance to change:
Regulatory concerns
The financial advisory profession is heavily regulated, and firms may hesitate to adopt new technologies that could violate compliance requirements.
Client preferences
Some clients, particularly older generations, may prefer the human touch and face-to-face interactions that traditional advisory models provide.
Fear of losing the human element
Financial advisors may fear that adopting AI will lead to losing the human touch and the personal relationships they have built with clients over the years.
Wealthier:
The Investing Field Guide for Millennials.
Why have so many financial advisors agreed to review an advance copy of Wealthier: The Investing Field Guide for Millennials. It empowers millennials to be responsible DIY investors and financial planners. You can see some of their reviews here.
Wealthier will be published on May 15, 2024
Here’s what one advisor said: "Saplings grow into trees. We need to help the next generation of investors get to where they need our services."
For more information, visit the website for Wealthier:
To review Wealthier send an e-mail to: [email protected]
Caveats
My disruptive predictions for the impact of AI and the future of M&A activity are subject to these caveats:
- I may be underestimating the ability of human advisors to adapt and use AI to enhance their services in a cost-effective manner while still preserving margins. Advisors may be successful in establishing hybrid human-AI models which could compete with a fully autonomous AI model.
- I may be overestimating the pace and scope of AI advancement. I am influenced by my own experience and by this quote attributed to Ray Kurzweil, who Bill Gates believes is “the best person I know at predicting the future of artificial intelligence”: “We’re not quite there (when AI will overtake human intelligence), but we will be there, and by 2029 it will match any person. I’m actually considered conservative. People think that it will happen next year or the year after.”
- While AI has made significant strides, creating a fully autonomous financial advisor with the combined knowledge of multiple experts and human-like empathy is a formidable task.
- The assumption that clients will readily switch to AI-based advisors due to lower costs may oversimplify consumer behavior. Factors like trust, personal relationships, and the perceived value of human judgment may keep many clients with traditional advisors.
- I can’t predict the regulatory and legal implications of AI-based financial advice. Significant hurdles could exist to full (or even partial) AI autonomy. Established players may resist disruptive change and even lobby for regulations that preserve their role.
- I don’t have data on the potential impact of AI on advisor revenues and firm valuations. My views of the potential for a bubble in M&A activity would be more persuasive with a data-driven analysis. But an analysis by Autonomous Research predicted a 22% cost reduction in financial services by 2030 through AI, totaling $1 trillion.
My thoughts
The M&A mania may not fully reflect AI's potential impact on fees and revenues, especially if human-level AI becomes a reality shortly. As AI adoption continues to grow, the industry may need to reevaluate its valuation of advisory firms and adjust its M&A strategies accordingly.
It looks like a bubble to me.
Dan coaches evidence-based financial advisors on how to convert more prospects into clients. His digital marketing firm is a leading provider of SEO, website design, branding, content marketing, and video production services to financial advisors worldwide.
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