The Future of AI in Financial Planning
Planning is changing, but the best financial planners will have work for a long time to come.
As of today, in January 2024, we seem to be at a little bit of a pause in the AI hype cycle in the media. It's been close to a year since GPT-4 was released; people are no longer surprised by what ChatGPT can do, and it's becoming more normalized to see AI features integrated into software products.
But make no mistake -- more changes are coming soon. Sam Altman, CEO of OpenAI, has said that GPT-5 is already under development. Google's most capable model, called Gemini, has been announced (though not without controversy surrounding that announcement). These advancements are not only not slowing down—they're accelerating.
Financial planners and advisors—the customers we love and serve—need to be prepared. So in this article, we're going to dive in to the changes that will be coming specifically to financial planning as models become more capable, and more customized to particular work. Let's get into it.
1. Assessment of Financial Health
One thing AI is really good at—better than most humans—is not missing anything. Humans can get tired, lazy, and just plain old miss things!
If there is a financial red flag in a client's data, then AI is very likely to see it. A recent analysis showed that even inside very long documents, GPT-4 was capable of finding a "needle in a haystack"—a tiny piece of information buried randomly in surrounding text.
By integrating AI algorithms with clients' financial data, AI can identify spending patterns, investment behaviors, and potential financial risks, offering a comprehensive and nuanced analysis. This will not only save time but also uncover insights that might be missed in manual analysis, leading to more informed decision-making, for both the financial planner and the client.
So what will this actually look like? In the near future, it will mean uploading documents to a software product (likely cloud-based), that will pass them into a large language model (like GPT-4), and
2. Goal Setting
Personalized goal setting will become more nuanced with AI. Technologies like predictive analytics and natural language processing (NLP) will help in understanding client conversations and feedback, enabling AI systems to suggest tailored financial goals.
This personalization is not just about setting goals but also about understanding client motivations and adjusting recommendations in real-time based on ongoing financial behavior and market changes.
Products like Jump (our AI notetaker for financial advisors) don't currently make goal recommendations, but given the rich conversational data available, you can very easily imagine that goal setting will be subject to not just review by the planner and the client, but also by AI that can look for clues in conversation that typically lead to particular goals.
3. Developing Financial Plans
This one's a biggie. A lot of data goes into a financial plan—and not just client data. AI can process current market data, historical trends, and individual client profiles to create dynamic, adaptive financial plans. These plans will automatically adjust to changes in the market or in clients' financial situations, ensuring that the financial advice remains relevant and timely. Additionally, AI-driven simulation models can present various financial scenarios, helping clients understand the potential outcomes of their financial decisions.
Uploading static documents is the start here, but eventually, expect to connect client accounts to a platform that will assess their goals, market conditions, current portfolio, and more, to propose tweaks to plans on an ongoing basis. Of course, this is where human advisors come in—one thing AI won't have is the relationship to truly understand where a client's coming from, and will be able to help the client make the final call.
4. Investment Advice
In investment advice, AI brings two major innovations: enhanced market analysis and the rise of robo-advisors. Advanced AI algorithms can analyze market trends and predict future movements more accurately, offering insights beyond the capacity of traditional analysis.
Meanwhile, robo-advisors automate routine investment advice, freeing up human advisors to focus on complex, bespoke advice that requires a human touch. While many investment advisors and financial planners currently invest primarily in predefined portfolios or ETFs, and others are more custom, expect more to be delegated to AI—especially as conversational data becomes available to these systems and is able to gain deeper understanding of a client's goals and preferences.
It's likely that financial planners and advisors will be clicking fewer buttons to actually place bets, but they will continue to be needed to help clients understand the decisions they're making and help stay the course.
5. Risk Management
AI's ability to analyze large data sets can significantly improve risk management. By using machine learning to identify risk patterns and predict potential issues, AI can provide more personalized risk assessments.
This includes not just financial risks but also life event risks, market volatility, and more, offering a holistic view of potential challenges a client might face. Expect platforms to come up which allow for quick changes to portfolios based on real-time market analysis, but also that look for gaps in insurance policies, under-coverage problems, or portfolios that are generally weighted inappropriately for a client's risk profile.
6. Tax Planning
AI-driven tax planning tools will be able to stay abreast of the latest tax laws and regulations, using this information to suggest the most tax-efficient strategies for clients. This is particularly valuable for RIAs, as it automates the labor-intensive process of keeping up with constantly changing tax legislation, ensuring that clients are always maximizing their tax-saving opportunities.
As an example, starting in 2022, companies could no longer write off 100% of research and development expenses—a massive change in tax policy depending on industry. AI systems could help advisors identify clients who might be affected by this change, absorb their situation, and identify mitigation strategies.
7. Retirement Planning
For retirement planning, AI can utilize predictive models to forecast long-term market trends and retirement needs. By simulating various retirement scenarios, AI helps in creating more robust, flexible retirement plans. These models can factor in various uncertainties like inflation rates, market returns, and changes in personal circumstances, offering a comprehensive view of a client's retirement outlook.
While existing software is massively helpful in creating long-term retirement scenarios, they do depend on a lot of manual inputs and need to be kept up to date based on changes in clients' situations. Those changes are likely to come out in conversations with their advisor, and systems in the future could immediately adapt and even alert advisors and their clients if a change is going to make a meaningful impact to the retirement plan.
8. Estate Planning
In estate planning, AI can automate and streamline complex processes like document analysis, asset valuation, and legal compliance checks. AI can assist in drafting estate planning documents by providing up-to-date legal templates and ensuring all financial and legal aspects are accurately addressed.
Language models specifically trained for legal documents are already underway, and startups are popping up with this specific functionality. Before estate plans are drafted completely by AI, expect to have existing and new plans run through AI systems to check for oversights and mistakes.
9. Education Funding
AI tools will advance the precision of forecasting educational costs. By analyzing current trends in education costs and correlating them with individual savings plans, AI can provide more accurate, personalized strategies for education funding.
An interesting side note here is that AI is likely to disrupt education itself significantly; it's possible that future language models, combined with video and image models, are able to act as virtual "tutors" with course content and curriculum tailored to individual students' needs—all at a fraction of the cost of a human teacher. Not only could AI help plan for education expenses, it might change the landscape itself.
10. Client Education
We've arrived at the final point, and it's related to the last one. A key job of every advisor is to educate their clients and help fill in their gaps in understanding. Expect to have software that will help educate your clients on their own situations as well as on markets and other dynamics that affect their financial picture.
In the near future, look for platforms that will help write regular newsletter content that advisors send to their clients. As models advance, expect that those communications will become more and more custom to clients and integrate more about their specific situation.
The takeaway
The TL;DR is this: if you look at each of the above points, the financial planner is still in the picture. Yes, work that happens manually today can and will be automated by AI. But clients will always need the steady hand, the advice, and the second pair of eyes that financial planners can provide.
As we integrate AI tools like Jump into more and more firms, we're not just adapting to technological advancements; we're leveraging them to allow financial planners to provide unparalleled service. AI is the partner that amplifies human expertise, enabling planners to focus on what they do best – guiding our clients towards financial success.
About Tim Chaves
Tim is the COO and Co-founder of Jump. He's the former founder and CEO of ZipBooks, which was acquired by Divvy 2019 (subsequently acquired by Bill.com). He's a design nerd and software engineer who earned an MBA with Distinction from Harvard Business School in 2015.