Growing a Financial Advisory Practice Using Data

Lance Rybka is a current finance major at Samford University. He hopes to start a business that uses data analytics to help fee-based financial advisers grow firms.

According to data from the most recent Tiburon Summit, small fee-based financial advisers are increasingly facing pricing pressures that place their businesses at risk. Since 2009 the average fees charged by these advisors have decreased from 1.2% of AUM to .96%,, and 86% of Tiburon CEOs believe that these fees will continue to decrease over the next five years. While robo-advisers and data analytics are partially responsible for this restrictive pricing trend, many traditionalists do not realize the potential they have to grow their practice by embracing this technology instead of resisting it.

Financial advisers can employ data analytics to improve their core services and ultimately strengthen their value proposition to clients. Envestnet reports that data-enabled investing allows advisers to produce “more sophisticated financial planning solutions and strategies” so as to better serve their clients through data aggregation. This technology enables financial advisers to view all of their clients’ portfolios in under thirty minutes each morning. Without this software, the typical adviser might look at each portfolio once or twice every month but not frequently enough to notice small red flags that could put their client’s financial security at risk. Because of data aggregation, advisers can stay up to date on each portfolio’s performance, catch problems before they occur, and present clients with real-time “what-ifs” that both safeguard their assets and strengthen their relationship with the adviser. According to a 2019 Kitces article, the average financial adviser has 113 active clients with roughly 35 dormant clients while the optimal number for an independent financial adviser is closer to 125 active clients and no dormant ones. Because data analytics enables advisers to take on more active clients and engage dormant ones and because the average client is worth between $2,500 and $7,500 annually (according to 2020 Tiburon data), advisers can earn greater revenues without sacrificing the quality and attention to detail.

Data Analytics is not only useful for the monitoring of client’s accounts, but it can be leveraged to assist the adviser in making investment decisions. Using data analytics, a financial adviser can more accurately forecast how various investments are expected to impact a client’s portfolio over an extended period of time. Based on these forecasts and a client’s risk appetite, the adviser can craft custom investment strategies, tax plans, and insurance portfolios that meet the individual needs of each specific client. Because data analytics enables the average financial adviser to offer a more comprehensive suite of services, they can attract new clients, better serve existing ones, and reduce overhead costs. Additionally, 71% of Tiburon CEO’s believe that targeting high-net-worth individuals is the best way for advisers to continue to charge higher fees for their services. These data-driven insights enable advisers to offer more of the higher-revenue-producing services demanded by these individuals. Finally, the leveraging of data analytics has the potential to increase the accuracy and value of each advisers’ recommendations which will lead to increased client satisfaction which can lead to referrals and the growth of the adviser’s practice.  In an age where “average is over,” financial advisers can either ride the wave of data analytics or be crushed by increasing industry pricing pressures.

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