When and how will big data and blockchain impact the FinTech industry?
Interview with Michael Kitces,
Partner and Director of Wealth Management
at Pinnacle Advisory Group
“I like to think of ideas as potential energy. They’re really wonderful, but nothing will happen until we risk putting them into action.” –Mae Jemison, first black woman to travel to outer space
Are advisors facing big data problems?
Using behavior analytics to predict user behavior and select more accurate financial strategies has been a hot topic in recent years. That said, it’s debatable how useful these capabilities actually are. I was eager to talk to Michael Kitces, partner and director of wealth management at Pinnacle Advisory Group, about his opinion.
Because Michael wears many hats at Pinnacle Advisory Group (in addition to his two primary roles, he covers wealth-technology and financial planning strategies on his popular Nerd’s Eye View blog), and is the co-founder of the 900-advisor XY Planning Network and his own FinTech company AdvicePay, he has a unique point of view as both a skeptic and a user.
Michael says that when it’s applied to individual advisors, big data isn’t that useful. Why? Because individual advisors don’t have enough clients (most have only about 50–100 active client relationships) for big data to properly function. Instead, advisors have “small data” challenges (of keeping track of their individual client needs).
However, for the industry as a whole, client datasets can become unimaginably large. As CRM and portfolio-accounting systems become more connected, we might start learning more about aggregate client and advisor behavior.
“I think big data is a rich space for research, but advisers don’t work in big data with clients. They work in small data.”
The big data “river” analogy
To prove his point, Michael uses the following analogy for applying big data and machine-learning algorithms to clients:
“With number-crunching and analysis, you calculate that a river has an average depth of 3.12 feet. This takes into account the seasons, the water cycle, tides, and so on. What happens when the deepest part of the river is seven-feet tall, but the client is only six-feet tall? The client is still going to drown. And big data can miss the small-data issue with an individual client.“
Albeit somewhat dark, this analogy perfectly illustrates how a “sample size of one” doesn’t work.
“As an advisor, you can do as much big data analytics and crunching as you want, [but] it doesn’t do much to unmask how a sample size of one, for any particular individual client, does or doesn’t relate to that giant data set. And often they don’t.”
Like Michael says, we live in the real world, where people have peculiarities that predictive algorithms cannot account for. If it was an easy process to automate, advisors would become obsolete in the same way that doctors would if obesity, addictions, and other diseases could be predicted and self-corrected using information alone to tell people what they need to do.
For advisors like Michael, it seems that these “hot” technologies might be a better fit for back-office automation than for user-facing processes:
“I see these technologies almost entirely as tools that increasingly automate the back office. I don’t know if it actually changes much about the front-office, client-to-advisor relationship.”
Big data applied to active and passive portfolio management
The idea of applying big data to markets is not a FinTech innovation. Hedge fund firms have been doing it for years, using the most powerful computers made by mankind.
Before computers, people analyzed datasets with abacuses. We’ve come a long way since then, but the goal has always been to squeeze out as much revenue as possible. Technology has allowed investors and investment markets to find opportunity where there was once none. This requires smart minds and a lot of money.
Michael believes that the idea of a FinTech startup coming along and using Big Data to analyze markets and compete against much larger and better-capitalized firms that have had 10–20 year headstarts is a nonstarter. He says that it’s a gross underestimation of how powerful and efficient investment markets are, given that investors have been using big data algorithms for decades.
Nevertheless, Michael isn’t an advocate for a 100%-passive management approach, either. Markets are still driven by human beings, and as mentioned previously, human beings do irrational things. Michael cites an example: the events leading up to the 2008 financial crisis.
“You could’ve taken any big data algorithm, and it would’ve told you [that] real estate might be a little overbought in 2006. Doesn’t mean that those people didn’t keep buying in 2007, and it doesn’t mean they avoided the crash that followed in 2008.”
Michael points out that we didn’t need fancy technology to see that real estate was dangerously priced in 2006, or that tech companies were overpriced in 1999. People still bought into it, the herd mentality still took hold, and as we all know, many experienced tremendous losses.
“We literally wrote a book called Irrational Exuberance in the years leading up to the tech bubble peak, and then people kept buying anyway, because herds do what herds do.”
Is blockchain the future of FinTech?
According to a Gartner report, blockchain’s business value-add will grow to $176 billion by 2025. The idea of a decentralized technology that can change how we handle security, transparency, and financial transactions seems almost utopian.
FinTech firms are already taking advantage of smart contracts, which are similar to standard paper contracts, except that the conditions and terms are programmed in computer code. Because smart contracts are regarded as irrevocable, they cannot be stopped or cancelled unless the outcome of a contract depends on an unmet condition.
In Michael’s opinion, whether blockchain is adopted will depend on operational efficiency; can the cost of services be lowered by leveraging technology?
“My guess is blockchain will be revolutionary technology in 10–15 years. When you look at something like investment markets in particular, which are entirely driven by transactions and assets trading hands, the potential for Blockchain to record those transactions and build efficiencies in trading and delivery off of centralized open ledger systems is incredibly powerful.”
Blockchain might replace some backend clearing and settlement processes, where stock trading and transfers happen, and it could save enormous amounts of time by performing these actions in minutes instead of weeks. But for the average advisor, it won’t likely change the advice they give to clients.
“It doesn’t change how I relate to my clients. It doesn’t actually change my business model as an advisor. It just makes the back-office plumbing of investments hopefully much more efficient. Which is a plus, but it’ll be a cost-savings my clients get when trading and investing becomes cheaper.”
Everyone is excited to see these technologies at work in our personal and professional lives. We like the idea of becoming even more “cyborg-like.” Most of us are well on our way; we wear glasses, use wearable smart devices, and some of us interact more with technology than we do with actual humans! These new toys and emerging technologies are cool, no doubt, but for the time being, so long as the average advisor has only 50–100 actively-engaged affluent clients, these tools won’t greatly affect their workflows.
Michael Kitces has nearly 20 years of experience in finance. He is currently a partner and the director of wealth management for Pinnacle Advisory Group, a private wealth-management firm with approximately $1.8 billion AUM. He is the co-founder of the XY Planning Network, AdvicePay, New Planner Recruiting, the publisher of the e-newsletter, “The Kitces Report,” and the author of the popular financial-planning industry blog, “Nerd’s Eye View.”
Interviewed by Vasyl Soloshchuk, CEO and co-owner at INSART, FinTech engineering company. Vasyl is also the author of WealthTech Club, which conducts research into Fortune and Startup Robo-advisor and Wealth Management companies in terms of the technology ecosystem.