Behavioral analytics: the data trend that has asset managers looking inward

Vanguard and others are building tools that “nudge” investors to make better investment decisions.

To distinguish themselves from the crowd, some asset managers are turning to behavioral science and psychology to help investors make better decisions by using insights and pattern data derived from an individual’s behavior.

Jing Wang is the head of the Center for Analytics and Insights at Vanguard. The firm started investing in applied behavioral sciences about two years ago. Equipped initially with a skeleton team and an antiquated technology stack, today, the center has more than 100 members whose job is to experiment with the latest technology and data available.

Behavioral finance focuses on how the psychological profiles of investors affect market outcomes. A subset of behavioral economics, proponents of behavioral finance posit that individual personal biases and influences, as well as investors’ mental and physical health, affect their performances in the stock market. The reasoning for its use is the belief that tailored personalization and bespoke customization options for investors can yield better returns.

Vanguard, for its part, goes to the source by creating solutions that cater to the investors themselves rather than to portfolio or fund managers. Behind these solutions is a form of social engineering that Wang’s team has dubbed “nudging.”

Nudging consists of building a highly detailed emotional and psychological profile of individual investors to understand the specific challenges they face and help them to make decisions that will get them the best returns on their investment. Once these are properly parsed, that data is used by Vanguard to design and implement specific interventions within the user experience—a “nudge”—which are then deployed to influence investors to make the right decisions.

Wang draws on a recent example within Vanguard that has benefitted from implementing nudges. She says that when an investor comes to open an account at Vanguard, the first step is normally to move money into the Vanguard account. The landing spot for that money, initially, is a settlement fund. The settlement fund is attached to a money market fund, which is not the ideal destination for a customer’s own purpose-built portfolio aligned with their risk tolerance and investment goals.

“We have observed that a lot of investors stop at that first step due to a misperception that the settlement fund is an investment product,” Wang says. “I mean it is an investment product—it is a money market fund—but it is not the ultimate investment product for this money. We need to correct that misperception.”

Wang accepts that decision paralysis may be one of the main problems causing investors to fail at proceeding properly with their accounts. Vanguard offers hundreds of potential choices that allow increased flexibility in building portfolios for customers, but the number can prove daunting and lead to new investors stalling.

Wang finds that people tend to procrastinate, and then if they don’t do it within a week, they forget about it and park their money in the settlement fund.

This is where nudges come in. Vanguard has implemented a series of small pop-ups, in line with their research on decision-making, as well as forms to fill in that coax investors into completing the next steps of the process. The nudges are subtle because investors have shown that being railroaded into completing certain tasks makes them less likely to follow through.

Vanguard’s suggestions are tailored to be simple, such as a list that describes current progress and lays out clear next steps for investors in the digital space. As the company has already compiled a detailed investor profile based on their answers to a questionnaire, it can also provide a list of personality-based suggestions to new investors to faintly influence them into making strong choices.

The nudge system is unlike some more intrusive advertisements, such as the controversial targeted advertisements based on user data touted by Instagram and Facebook, executives say. Vanguard’s chief data analytics officer, Ryan Swann, likens it more to a series of helpful tips based on an established user profile and goals clearly stated by the investor.

“Imagine that you wanted to build a shed and you go to Home Depot and you buy all the wood. You know you need the wood, but before you leave, Home Depot says, ‘Hey, I know you want to build a shed and you’ve got the wood. You’re probably going to need these nails, these screwdrivers, this glue, and something for the foundations to make it really sturdy to get you where you’re going,’” Swann says.

‘People don’t like being told what to do’

Swann and Wang’s nudging system has its admirers among behavioral analytics zealots, such as Helen Yang, CEO and founder of wealth manager Andes Wealth Technologies. When she built the company seven years ago, she says she specifically had behavioral finance at the top of her mind.

A client of financial advisers herself, she noticed that her own advisers were unable to give her the level of insights she was asking for. Due to her previous experience in fintech—Yang had worked as a product manager at Charles River Development and Thomson Reuters (now Refinitiv)—she realized the problem was, at its source, a fintech one, and her advisers were lacking the tools to give her what she wanted.

“Thinking about it deeper, I realized that the current cookie-cutter service is based on the traditional financial theory that the markets are efficient, and investors are rational,” Yang says.

In the middle of her career, Yang studied for an MBA at the Massachusetts Institute of Technology, where she met famed finance professor Andrew Lo and learned about his adaptive market hypothesis, which combines principles of the efficient market hypothesis, which her previous wealth managers had operated under, and behavioral finance.

“It’s a great theory and in the end, I figured that theory could be the theoretical foundation for the new way to deal with wealth management,” she says.

Yang says that Vanguard’s nudges make a lot of sense to her, but at her company, they practice a different variation of the method.

“I’m a big fan of that idea—sometimes people just need a little nudge. They know they want to do something and forget about it and now you are telling them that’s the right thing to do. But I’m pretty sure we do it differently from Vanguard,” she says.

Yang says that one of the main reasons for the subtle, inoffensive practice of nudging in behavioral finance in the first place is the cited desire of investors not to be told what to do. She cites a study by Morningstar, which found that when asked to rank 15 attributes investors wanted from a financial adviser, behavioral coaching was ranked in 13th place. Keeping investors in control of their emotions came in dead last.

At face value, it appears impossible to reconcile the perceived value of coaching investors with their unwillingness to listen. But Yang believes the secret is in embedding useful advice within the day-to-day workflow.

“People don’t like being told what to do, so we kind of splice it in. If a child doesn’t like to take their medicine, you blend it into their food or drink, and they don’t realize they’re taking it. If you can recollect the days when you were a child and people all advised you, I’m pretty sure most of it was good advice, but you just didn’t want to listen,” she says.

Yang notes that while there have been other attempts in the industry to increase personalization and utilize behavioral analytics, most of these have ended in failure. She points to a vendor that produces financial tools around behavioral analytics. To better know the investor, the vendor has a survey that asks 50 questions.

“I took it myself, and the problem is that it’s too long. People don’t have the patience to sit through 40-50 questions, and they don’t know which question leads to which result,” Yang says.

If other such vendors weren’t meeting pitfalls like making questionnaires too long, they were sometimes not paying enough attention to their clients’ profiles. She points to a robo-advisor that—after some big market movement—would send out an email to clients saying, “Don’t Panic”.

“That message would have been great for trend followers, but for a passive investor like me, I barely monitor the market. When I get an email like this, my first reaction is, ‘Well should I panic?’ This is the same for contrarian investors—they’d be excited about it. They’d think this would be a perfect opportunity to get in because they’re telling us not to panic. That isn’t providing the right service,” Yang says.

Decisions, decisions

Currently, one of the metrics used by prospective clients to select a fund manager for their portfolio is the manager’s past performance in the market. However, Clare Flynn Levy, CEO of buy-side data analytics provider Essentia Analytics, believes this method is flawed.

“The fund management industry has a real problem in that it says in the fine print that past performance is not predictive of future performance, and yet that is literally what everybody is using to judge whether a fund manager is a good choice to get them their money,” Levy says.

Essentia Analytics uses behavioral analytics chiefly to analyze past decisions of fund managers to maximize future returns on alpha. The company uses a form of behavioral analysis named “decision attribution analysis” to analyze data from fund managers and find and identify patterns.

Levy explains that decision attribution looks at decisions made all along the way rather than just simply after the fact.

“If you decide to buy Tesla today, then you made a decision about it being Tesla versus something else, but you’ve also made a decision about buying it today and you’ve made another decision about how much you’re starting with,” Levy explains. “You’re making a whole series of decisions throughout the life of Tesla in your portfolio,” she says.

Using decision attribution analysis, Essentia Analytics takes a bottom-up approach, rather than a top-down approach, to maximize the number of data points. Levy says that while the maxim of “past performance is not indicative of future performance” is a given within the field of asset management, Essentia is currently conducting further research, finding that previous instances of high-quality decision-making are persistent.

“A good decision-maker—which we define as getting it right more than 50% of the time—when they do get it right, they tend to get it more right than they get it wrong when they get it wrong,” Levy explains.

Slow to take

These personalized, rooted-in-psychology solutions offered by Vanguard, Andes, and Essentia have received positive feedback from users, but the use of behavioral analytics remains an outlier in the asset and fund management space.

Levy believes that the problem lies in the world of asset management, where people and companies are constantly changing but where long-held mindsets are slow to change.

“The historical culture of the industry has not been conducive to this inward-looking approach and being able to admit when you’ve been wrong about something. That’s not how fund managers have been brought up to behave,” she says.

Essentia published a whitepaper on the Behavioral Alpha Benchmark, its tool to assess portfolio manager performance based on demonstrated skill. This is set to be supplanted when the Journal of Investments publishes its own version of the paper, sharing it with a larger audience. Levy believes it is only a matter of time before behavioral analytics becomes commonplace in money management.

“It just takes time,” she says. “You need the old guard to leave.”

Additional reporting by Rebecca Natale

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