Robo-Advisors Need To Leverage Machine Learning to Meet the Financial Needs of Gen Y
Names like Betterment, Personal Capital, and Wealthfront have come on the scene in the last eight years to disrupt the wealth management industry. These fintech startups have been able to garner interest from the millennial generation that is quickly approaching their peak earning years. Thanks to Gen Y’s comfort with digital finance tools, these robo-advisors have been able to build a sizable book of business estimated to be $19 Billion in assets under management according to a Deloitte white paper. However as these startups have proved the concept of shifting wealth management to a digital platform, it has given the green light to incumbent asset managers like Charles Schwab and Vanguard have entered the market. And who came blame them of shifting to this new strategy with the prospect of low-cost, automated, on-demand capabilities meeting the client expectations.
It is estimated that these large platforms will contribute to the anticipated increase in the market to approximately $2 Trillion by 2020. There is no question that there is an opportunity in this industry especially with the prediction that $30 trillion will be transferred in wealth from Baby Boomers to Generation X to Millennials. So there is an opportunity to scoop these new customers that financial advisors have not developed a relationship with yet. So with acceptance from traditional wealth management shops that clients are comfortable with these platforms, where should fintech robo-advisors push innovation to leverage technological advancements and create real disruption?
The answer is AI. Not that AI (although he was the only man to ever persuade me to buy Reebok’s as a kid) but artificial intelligence. There are various fintech tools that attempt to guide consumers to their financial goals, whether it be saving for notable events, paying down personal or student debt or wealth creation through investment vehicles. Currently in the market, I have to gain knowledge on the best credit card options from Nerd Wallet, track all of my current purchases and cash flow from Mint or Personal Finance, and build an investment portfolio through trading apps like Robin Hood or passive investing robo-advisors that I mentioned before. Each of those startups sends me content offering general advice on issues such as how much should you spend on an engagement ring (not a joke I can show you the email), how to prepare for a down payment on a house, and are you on track for retirement. Retirement? Really? It couldn’t be further from my thoughts and other millennials agree with with it not being one of their top priorities according to a study done by TD Bank (see infographic below).
Needless to say there is a huge opportunity for robo-advising fintech startups to use data analytics and machine learning to pinpoint the exact financial needs of millennials (especially older ones like myself) who are in an interesting point in their lives. Although Millennials are entering their peak years of income generation they also face different financial pressures from student loan debt and the decrease in earnings due to the financial crises in 2008. Imagine if the personalize touch that a robo-advising could offer it tracked the all the personalized financial information that is already out there.
There could be Netflix like suggestions that take into account your specific saving goals, your cash flow history, and your financial lifestyle. This offering would add a personal touch that is missing from most wealth management products no matter if it is on a platform or from a traditional financial advisor. Incorporating platforms were the first step to testing innovation in the wealth management industry but the key step is providing highly customized advising through the use of data analytics and machine learning. We should be getting very close to a point where AI provides much better advising each hour than Pat at my local Schwab office can during our quarterly portfolio call. That’s what Robo-Advisors 2.0 should look like. That’s what I’m looking for.
Earnest Sweat is a Startup Adviser and Business Ops professional for various accelerators. Sweat specializes in sourcing, managing and mentoring startups within the fin tech, ed tech, and real estate tech sectors. If you have any questions, comments or requests please connect with Earnest through LinkedIn, Twitter, or AngelList.
If you liked what you read please ☞ Please tap or click “♥︎” to help to promote this piece to others.
