The Future of Financial Advice

For as long as we’ve had systems of money, we’ve had systems of people telling us what to do with it. Today, financial advice is a $70+ billion dollar market and growing, but emerging technologies like AI and machine learning are threatening to disrupt more traditional incumbents. While many think simply adding a digital product or service with a chatbot can replace the thoughtful advice of a human advisor, the real winning formula will be those who can cleverly combine personality matched chatbots to drive a better human to human advice offering.

The way advisors are typically connected to clients is based on either referral, geography or random assignment. But one-sized-fits-all advice does not work in an age where customer expectations are high, and different people respond better to different communication styles. Given the emotions around money, it makes sense to match advisors and advice to our clients’ personalities. So imagine intelligent chatbots who can adapt their behavioral style based on client’s preferred and most effective communication style. By designing effective chatbot-to-human ecosystems, firms can gain insights to better understand their clients and make the right match when assigning human advisors.

Let’s examine these chatbot archetypes across three basic segments of financial advice: Spending and Savings, Investments, and Tax Law and Estate Planning.

Spending and Savings

For those who are looking for help with overall budgeting, financial planning or developing health financial habits, the key players can span from more traditional financial planners or debt consolidation/settlement/reduction firms to book authors who’ve made a name for themselves giving financial advice. Dave Ramsey, Suze Ormon, and George Clason are all examples of contemporary financial advice gurus, but this tradition of advice spans all the way back to Benjamin Franklin and his timeless adage, “Beware of expenses, a small leak will sink a might ship.”

There’s a ton of wisdom out there for budgeting and savings, but the key is to get the personality and voice matched to what will be most effective with a particular customer.

Investments

Today’s investment advisors take many forms, including that of a mutual or index fund that provides a basket of investments and charges a management fee; brokerages who provide current day “robo-advisors” primarily around risk tolerance, asset allocation and potentially tax-loss harvesting; and good old fashioned financial advisors, who provide financial advice for a fee. The main areas of value derived from these services are capital preservation and growth, low cost investment options, dynamic asset allocation and financial planning. We already have many automated elements one could consider “advice” in the form of automatic withdrawals and 401k plans, to Target Date Funds that automatically change your investment allocation and Robo-Advisors that match client risk profiles and goals.

Tax and Estate Planning

For the nuts and bolts of minimizing of tax liabilities and reducing wealth transfer fees, most turn to tax and estate planning lawyers, advisors or firms.

Given the tax overhaul, the reduction in SALT allowance, the new limits in the mortgage interest deduction and the changes to pass-through income, there’s a lot for individuals to keep up with and to plan for. But if financial institutions have a full picture of their clients’ financial situation, there’s an opportunity to offload the majority of basic tax and legal advice to bots, including warning a client of the pros and cons of any particular taxable event they might engage in. Keep in mind that this type of help can be very expensive and potentially available to only a few who can afford (Robo-advisors are already including tax-loss harvesting features).

The Human Touch

Creating a great bot to interact with your customers will not be the singular challenge. In the words of famed piano player Artur Schnabel, the bots may play all the standard notes quite well, but we need human beings for those moments when reading off the sheet music is inferior to riffing off the client’s rhythm, handling emotional situations and providing advice where clear answers don’t exist.

Designing for success in these scenarios is about designing for the inevitable failures of our bot characters and not leaving our clients in dead ends or recurring non-helpful loops. Bots have boundaries, and many people will only trust a bot up to a point. There will be moments where bots—even with all the knowledge they have—fail to answer a clients’ questions, or even to help them think through more abstract issues. The real differentiator is ensuring that the transition between bot and human happens elegantly and quickly.