Imagine Financial Planning 2030
Imagine receiving an email like this:
Thank you for all you’ve done for me over the past couple of decades, but I’ve decided to terminate our financial planning relationship. Like many other people, I too will be moving to an artificial intelligence-based advisor.
Is this far-fetched? Though a few years ago I would have thought so, artificial intelligence (AI) is here and is a very disruptive technology. AI’s arrival will have an increasingly large impact on our lives. That includes investing and, especially, other aspects of financial planning.
As just one example, last month at the Morningstar Investor Conference, I met Mo, Morningstar’s new beta version AI chatbot. We had a nice discussion on investing. A couple of weeks later, on May 11, a Morningstar press release introduced Mo to the public. "AI has huge potential to support a better investor experience at scale, and this is just the beginning," said James Rhodes, Morningstar's chief technology officer and president of data, research, and enterprise solutions.
Not only do I agree with Rhodes that this is only the beginning, but AI’s potential is in being the bridge that integrates investing with other facets of financial planning, especially taxes but also risk management, and retirement and estate planning. These are where AI will have its greatest impact.
Only two years ago, I wrote in Barron’s that I did not see robo advisors as a threat because rarely do clients come to advisors fully invested in cash. There is complex analysis required to decide what to hold or sell to design the new portfolio. I stated AI could be a threat at some point. But I wrote, “I don’t think artificial intelligence has advanced to the level of taking into account all tax situations.”
That’s still true today. But with the rapid advances in AI, it’s quite possible this will change in the next few years.
One of the biggest advantages of using AI in financial planning is its ability to process large amounts of data quickly and accurately. AI can analyze a person's financial situation and make recommendations based on their individual needs and goals. AI can monitor investments and make real-time adjustments based on market changes and other factors that could impact a person's financial future.
Advisor Michael Kitces recently wrote why ChatGPT is no threat to real advisors, concluding that its main benefit is that of a communications “tool to help human advisors convey important financial concepts to clients through writing faster and easier.” While I agree that AI can be useful in client communications, the main benefit will come from the integrated analysis to optimize all segments of financial planning.
The financial information I gather from clients is complex and difficult to collect as it comes from different sources in varied formats. I collect all investments, cost bases, options, 401(k)-type plans, tax-returns, insurance data, and estate plans, among other data. I learn about their willingness to take risk (often by past behavior) and assess their need.
With this information, I build the portfolio with the goal of minimizing fees and maximizing diversification. I do complex tax analysis in constructing the new portfolio. In withdrawal mode, not only do I have to consider marginal tax rates, but one dollar of extra income can cost the client thousands of dollars in extra IRMAA Medicare premiums.
It is sophisticated and takes a lot of time to analyze.
Imagine financial planning 2030
Though history is full of predictions that never came true, let’s imagine financial planning in the beginning of the next decade. The client hires the Artificial Intelligence Based Advisor (AIBA), a financial planning firm that uses AI extensively. The interaction starts with a principal planner of AIBA who explains how the process works and how it leads to optimal financial planning with far lower costs. The AIBA planner discovers and inputs the client’s goals.
With appropriate permissions, the AI engine automatically collects all of the data from the client by going directly to the sources. It then integrates the data, synthesizes and summarizes the financial position, and submits it to the client for review to determine if anything is missing or misinterpreted by the AI engine, noting which pieces of data might be especially suspect. For example, it might note a possible inconsistency between the client stating they have a high-risk tolerance and a large tax-loss carryforward on the return.
When both the planner and the client are comfortable with the accuracy of the financial position, the AI engine kicks in to the analysis stage, analyzing such items as:
- Cost benefit of selling less desirable securities (expensive and narrow) to build a lower-cost and more diversified portfolio;
- How to build the new portfolio with more tax-efficiency and an allocation more aligned with the client’s goals;
- Which recommendations represent more tax-efficient ways of continuing to contribute to charitable causes such as contributing highly appreciated securities using a donor-advised fund;
- Where the client is over or under insured, as well as what rates are higher than average for the area the client is domiciled;
- Which accounts are titled in such a way that they may conflict with the estate plan; and
- Whether retirement spend rates and the specific withdrawal strategy from various accounts maximizes tax-efficiency.
The AI engine would generate a report of specific recommendations. It does automatically what I do today and with far more complex analysis. It evaluates many additional scenarios than I could reasonably do manually and it does it in seconds. The AI engine produces a draft report that is reviewed by the planner for completeness.
The planner then sits down with the client and the AI engine for a review. The client may ask questions to both the planner and the AI engine. But rather than taking 15-20 hours of human time, perhaps only two to three hours is spent by the advisor before reviewing with the client.
But that’s not all.
The AI engine will assist in the implementation of the portfolio once the client has agreed to the new plan. It will monitor investments and make real-time adjustments based on market changes and other factors that could impact a person's financial future. AI is constantly learning as well as keeping up with tax and estate law changes. It also makes changes based on updates of the client’s income and other financial situations such as needing cash to buy a new home.
AI will not be successful in stock picking to beat the market. One firm, Danilfin, claims, “The AI-powered Danelfin best stocks strategy generated a return of +158% from January 3, 2017, until December 30, 2022, vs. only +70% of the S&P 500 in the same period.” Stock-market alpha will always be zero, and its success will be its ultimate demise when too many investors use it.
AI – an opportunity and a threat
While AI can provide customized advice based on data, it may not be able to consider the nuances of a person's financial situation or their unique goals. AI will not replace financial planners, as clients want a personalized experience.
Financial advisors will continue to play a key role in shaping client behavior. And much like self-driving cars, it’s critical that a human be present overseeing the process and overriding it to avoid any catastrophic outcomes. Regulators will likely require human interaction and oversight.
AI will be a disruptive force in financial planning. It will dramatically improve outcomes for clients and create a more streamlined planning process with more thorough analysis. Those advisors who ignore AI will eventually get “goodbye” emails from clients such as the one in the beginning of this article.
Many companies are working to change the future of finance with AI. Capital will quickly flow to firms working on integrated AI financial planning applications. Financial planning will be very different in a few years from what it is today. Keep up with these changes and embrace them.
Author’s note: I would like to thank Morningstar’s Mo and OpenAI’s ChatGPT for contributions to this article on how AI will be able to integrate and analyze complex data sets and work with advisors.
Allan Roth is the founder of Wealth Logic, LLC, a Colorado-based fee-only registered investment advisory firm. He has been working in the investment world of corporate finance for over 25 years. Allan has served as corporate finance officer of two multi-billion-dollar companies and has consulted with many others while at McKinsey & Company.