The fintech industry absolutely loves buzzwords and jargon.
There are no products, only “solutions.” There are artificial intelligence-powered marketing visualization tools powered by machine learning analytics in the cloud. Or my personal favorite: the frictionless end-to-end fully integrated platform, which just about everyone claims to provide these days.
Meaningless is the point, of course. It’s designed to, at best, get you to ask for more details and move down the prospect funnel toward the demo stage; or, at worst, cover up for the fact that a company has received funding but hasn’t actually built anything yet.
The jargon obfuscates, intentionally or not, what the product actually does. Don’t worry about it too much, just buy in so you don’t get left behind.
That’s not to say that there isn’t good technology in the industry. As slow as progress may seem, wealth management has come a long way over the past decade. Today, advisors can keep track of clients with a digital CRM instead of a Rolodex. Financial planning can be done with interactive software instead of a spreadsheet; client risk tolerance can be assessed quantitatively instead of with ad hoc rules of thumb; and portfolios can be automatically rebalanced, just to name a few improvements.
But where is this all going? What is the vision for the future? What is the point of all this data-driven automation, how will it improve the lives of advisors or their clients, and why should firms buy into it?
Or perhaps most importantly, why should clients keep paying financial advisors when more and more of the work behind the scenes is automated?
I’d argue that the vision should be to evolve wealth management from being a reactive industry to one that is proactive. This is how advisors utilize technology to become something truly invaluable to investors.
What if instead of waiting for a quarterly meeting to discuss performance, the client’s portal detects more logins than usual and automatically alerts the CRM which areas of the portfolio he or she was examining? This could automatically generate some digital outreach materials — such as an email with links to relevant news articles or compliance-approved commentary — that the advisor could approve, tweak or ignore entirely in favor of calling the client to talk to them.
Or instead of a new mother calling in to ask an advisor to set up a new college fund, the advisor is alerted to the client’s social media posts about the baby and knows to send a friendly congratulations along with a note saying, “It’s probably time to update that financial plan. Let me know when you have time and we can do it together online.”
Imagine a world where the advisor logs on in the morning to find a list of opportunities for clients across their book of business, organized in order of priority, that the advisor’s tech stack spent all night to surface.
This is what a tightly integrated, efficient technology looks like. This is just some of what is possible with automated data analytics and machine learning, and it is much closer to being a reality than you may think it is.
But it requires a vision of the future that goes beyond empty buzzwords.
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