Having worked in financial services for nearly twenty years, I’ve witnessed the rise of Artificial Intelligence (AI). Today, that rise is rapidly expanding across various sectors, with personal finance being one of the critical areas experiencing this transformation.

AI brings an innovative approach to managing personal finances, possessing abilities such as devising comprehensive financial plans, guidance on investment allocation, and even aiding in decisions like home buying.

However, like any other technology, AI has its limitations and challenges, such as a lack of personalized data understanding or the disregard for behavioral factors.

Let’s look at the nuances of using AI to manage personal finances, providing insight into its capabilities, challenges, and the potential future of this blend of finance and technology.

The Power Of AI In Personal Finance

In the early days, AI was used by major financial institutions to analyze the behaviors of their customers. These institutions would then use this data primarily for marketing purposes.

For example, fifteen years ago, I worked in a bank. We had an AI technology that could predict how much someone was worth, and it was scary accurate.

In addition, this technology could tell us how long the customer would likely have idle funds. Therefore, we could predict which financial products they most likely interested in.

Times are changing, though as these AI solutions become more widespread and cheaper to build.

AI Opens Up The Financial Planning World

According to research performed by Kitces.com, it currently takes a financial planner approximately 40 hours in the first year to collect data, analyze data, create plans, meet with clients, and implement a plan per client!

Financial planners have to eat. Therefore, they must be compensated for their time. The three common ways of compensation are:

• AUM: Charging a percentage of assets under management is very common. However, since financial planners have limited time, those who get compensated via AUM can’t help those who have a low amount of investable assets.
• Commission: Another way to make money is to get paid a commission for using certain products, such as annuities. This can lead to a massive bias in which planners make recommendations.
• Charging fees: This is where planners charge flat fees. According to Com, Initial engagement fees average $2,500. Annual ongoing fees have a median price tag of $4,000 a year.

Due to the compensation structure of traditional financial planners, lower and middle income individuals and the younger generation can’t get sound advice or its biased advice based on what the advisor makes a commission on.

AI changes all this. For example, our AI financial planning technology at FitBUX reduces the 40 hours as mentioned earlier a year needed per client to less than an hour a year. Therefore, we can charge less than $200 a year.

In short, AI is redefining the landscape of personal finance, making it more accessible and cost-efficient.

How Planners Have Used AI In The Past

Financial planners leverage AI to automate repetitive tasks, increasing efficiency and allowing more time for client interaction.

To date, AI has primarily focused on back-office tasks such as portfolio construction, email follow-ups, etc.…

Past technologies increased the amount of time a financial planner could be face-to-face with a client. However, it didn’t simplify financial planning for you as a client, i.e., you still depended on your financial planner.

That is beginning to change.

What AI Is Being Developed & Implemented Today

AI is now being used to build comprehensive financial plans in record times.

For example, collecting data from an individual typically takes a financial planner 4 – 7 meetings. It takes this long because they have to build rapport and manage documents. In addition, it typically takes about 3.5 years to break even for each new client when you look at costs and client retention rates.

With the current technology we’ve developed at FitBUX, we collect over 2,000 data points before we meet the individual. These data points tell us everything we need to know, from financial data to behavioral data.

Instead of taking 10 hours to build a plan, we can get on a call to build multiple projects, compare and contrast them, and decide on the right plan within 30 minutes.

In addition, AI is used to follow up with people. Therefore, our retention rates using AI are similar to or better than those of traditional financial planners. Thus, our break-even point for each client is roughly three months instead of 3.5 years!

In addition to comprehensive plans, AI can now evaluate the feasibility of substantial financial decisions, such as buying a house, by analyzing and interpreting vast amounts of real estate and personal finance data in seconds.

This leads to more informed and confident decision-making.

Also, AI is being used in new ways to manage investment portfolios based on your ability to take risks by factoring in your entire financial profile.

For example, it can factor in items such as the risk to your income, equity in your house, and the risk of debt you currently have. Then, it can recommend investment allocations that reduce the overall risk to your entire financial plan.

This is a significant leap forward since investment allocation decisions typically only look at your liquid investment portfolio today.

Why AI Is Better Than Traditional Financial Planners

AI has its flaws. However, before getting into them, I’ll dive deeper into the question I get daily: Is AI better than traditional financial planners?

AI Is Unbias

One of the significant advantages of leveraging AI to manage personal finances is its unbiased nature.

Even with the best intentions, traditional financial planners often exhibit bias towards certain financial products they are familiar with or gain more commission from.

This selective bias can skew the financial advice received and may not always be in the client’s best interest.

On the other hand, AI, being a product of complex algorithms and big data analytics, is immune to such biases. It treats all financial products equally and evaluates them based on their merits and alignment with its client’s financial goals.

This objectivity brings a new level of transparency and fairness to financial planning that was previously unattainable.

Knowledge Capacity

Human financial planners are bound by their knowledge capacity, which can be limited and outdated. In contrast, AI can access vast amounts of up-to-date financial data and learn and adapt in real time.

It can evaluate a broad spectrum of investment options and strategies, many of which traditional planners may not know or consider.

Accessibility

Finally, the limitations of human financial planners make them expensive and often out of reach for many.

AI, on the other hand, provides an affordable and accessible alternative. Its scalability allows it to serve many users simultaneously, making financial planning and advice accessible to the masses, not just the privileged few.

Limitations of AI in Financial Decision-Making

While AI holds significant potential in managing personal finances, it has limitations.

The Human Element

One major drawback is that some AI technologies cannot process and analyze personalized data effectively.

This leads to two results:

• A ‘one-size-fits-all’ approach to financial advice isn’t ideal, given the unique financial situations of individuals.
• I mentioned earlier that one benefit of AI is that it is unbiased. This is also a detriment because many AI models fail to consider behavioral factors significantly influencing financial decision-making. Think of it like getting financial advice from C3P0. e., it will be the most efficient, but it is not a factor in human emotion. A person’s financial decisions are not based solely on numbers and data; personal preferences, risk tolerance, and emotional factors also play a crucial role.

Limited To A Small Piece Of Your Plan

One major problem for consumers is having to triangulate data and make a decision. For example, if you want to buy a house, you speak to a real estate agent, a mortgage broker, and a financial planner.

They all have biases and limitations on knowledge, so you must speak to each other and decide what they say. Let’s face it: most people have minimal financial education and can’t do this.

Therefore, they want a financial planner to build a comprehensive plan. However, they have limited knowledge as well. For example, ask a financial planner which type of mortgage you should use, i.e., 5/1, 10/1, 30-year P&I. Most couldn’t tell you the difference.

If you asked them about paying points or not on your mortgage, most again would know what you are talking about.

Many AI systems work the same way. They only look at a small segment of your financial life.

For example, some AI platforms only look at tax documents and provide suggestions based on that data.

While this can be helpful, it’s not comprehensive and can overlook important factors that don’t appear in those documents.

Therefore, you still have the same problem as before, but instead of a person giving you the data and then you having to triangulate it to make a decision, a machine is giving you the data.

Garbage In, Garbage Out

Lastly, there’s the issue of open vs closed AI. Available AI learns continuously from new data and evolves, while the initial data limit completes the AI set it was trained on.

The issue with Open AI is it depends highly on screen scraping websites for information (i.e., Chat GPT). This doesn’t mean it’s good data and information.

Also, Open AI doesn’t have your personal information. If you ask it a question such as “Should I invest in my 401k or a Roth IRA?” it will give you a generic answer. Even worse, asking it multiple times will provide you with various solutions, often contradicting each other.

As previously mentioned, closed AI is limited by its initial data set. This can significantly reduce its usefulness because financial markets are constantly changing. Using stagnant data can output poor recommendations for users.

Limitations Are Being Addressed

If AI is to revolutionize personal financial management, these limitations must be addressed to be genuinely effective…. And they are.

For example, FitBUX combines 2,000 and 5,000 data points on each individual and financial market. Then, we combine Closed AI for some aspects of finance and Open AI for others. The result is a customized financial plan that can be continually updated as the individual’s situation changes and financial markets evolve.

The technology still has flaws, so it’s not available to the public yet. However, it’s worth noting that FitBUX is just one of many companies working to solve AI’s problems, and it is only a matter of time before these problems are solved.

The Balance of AI and Personal Touch

While AI brings impressive capabilities to personal finance, it’s essential to understand that it cannot entirely replace the human element.

AI has proven over recent years to be a powerful tool for routine transactions, budgeting, and straightforward investment strategies.

However, many individuals still prefer assurance and empathy from human interaction regarding major life-changing financial decisions.

Based on several surveys, approximately 70% say they would not make a significant financial decision unless they spoke to an individual.

However, these surveys are very biased towards age, i.e., of the 30% that said they would use AI, the majority are under 40.

In essence, human financial planners bring a personal touch that AI, despite its intelligence, has yet to achieve. Two factors may change this, though.

Behavioral Finance

The field of behavioral finance has grown significantly over the past 20 years. Based on transactions and other external factors such as social media posts, one can get a perfect picture of your behavior, biases, and what influences your decisions.

The accuracy of these behavioral technologies is scarily accurate. Slowly, these technologies are being incorporated into financial planning AI technologies.

Video

A potential solution lies in the integration of video AI. Video AI could help bridge this gap, providing a more interactive and personalized experience. It could offer human-like interaction, combining the benefits of AI’s data processing capabilities with the empathetic connection people often crave during significant financial decisions.

In addition, if you combine video AI with behavioral technology, you can develop a human-like interaction that fits the user’s personality.

Currently, the hybrid model using humans and AI leverages both strengths, offering a comprehensive, unbiased, and emotionally tuned approach to managing personal finances. This is the model we use at FitBUX, but I can see a future where 95% of the interaction is done between the user and AI.

About the author

Joseph Reinke is a Chartered Financial Analyst (CFA) Charter Holder and founder of FitBUX, which has helped young professionals between 20 and 40 manage more than $2.6 billion in assets and debts. Joseph has been personally investing since he was 12 years old.

In addition, he has experience in student loans, mortgages, wealth management, investment banking, valuation, stock trading, and options trading. He has been on 100s of podcasts and invited to 100s universities to discuss financial planning with their soon-to-be graduates.