Transforming Data Into Behavioral Finance Insights and Actions

Yainvest, a Swiss-based B2B SaaS company, uses more than 15 years of quantitative behavioral finance research to help firms improve the performance of their portfolio managers.

While the company has its roots in academia, established by BhFS Behavioural Finance Solutions, and featuring top academics from the Universities of St. Gallen and Zurich, its goal is to turn behavioral insights into action by providing unbiased financial management services to firms worldwide.

For Yainvest’s Co-Founder and Chief Executive Officer, Yulia Myronova, learning how the market might react to their product was a key first step. Before co-founding Yainvest, Yulia was a member of the Chief Technology Officer’s team at a leading wealth management bank in Zurich. In her role, she drove the adoption of cutting-edge technologies and innovative solutions. During this time, she met and collaborated with the founders of BhFS, a consulting firm involved in advising on the bank’s platform development.

“Our company is the result of years of rigorous academic research combined with experiments and validation with real firms,” Myronova says. “We’ve seen a growing demand for behavioral-based products—we know that human behaviour and biases can have a huge impact on portfolios and performance, sometimes positively, but most times negatively.

In 2023, I submitted our concept to the Accenture FinTech Innovation Lab in New York City. Accenture screened thousands of startups. We were selected as part of the top candidates and sent to pitch to Wall Street banks, who voted on the solutions. From here, we made the top 30, and the banks confirmed this was a product that needed building.

It validated our hypothesis that behavioral finance has a significant role to play in helping wealth managers, asset managers, and hedge funds derive value at scale.”

Building sophisticated APIs that reveal insights into behavioral gaps requires huge volumes of data. But Yainvest knew to turn to Morningstar.

“We have several products that rely on data,” Myronova says. “Let’s take our Investor Behaviour Impact product. Our models use Morningstar’s data—such as market price information—providing us with comprehensive market coverage and enabling us to analyse any portfolio across any asset class.

We’ll also plug in Morningstar’s ETF coverage, which is essential. This gives us insights on everything from active ETFs to thematic ETFs. Our models take this data to assess what investment decisions have been made. We can analyse thousands of ETFs and their daily disclosures or drill down into the portfolio holdings data to better understand the structure of a fund.”

As Myronova knows, while quality data is the first step, transforming it into a clear and cohesive narrative is the key to adding value.

“Our Behaviour Impact report involves a series of advanced analytics that assess transaction history for six behaviours which may be the result of biases and impact performance” Myronova says. “We look at:

1. Concentration
2. Under-diversification
3. Excessive trading
4. Overreaction to volatility (risk tolerance overestimation)
5. Disposition effect
6. Trend catching

We’ll then rank an individual’s tendency towards each bias on a scale from one to ten. The higher the score, the higher the influence of that specific bias. We then attribute the behavioral tendencies to the Investor Behavior Gap, which is the difference between the actual performance achieved by the manager and our proprietary benchmark, which reflects the average actions taken.

We analyse this data in a neutral, unbiased way to create a hyper-personalised diagnostic report, that in the future will also be enriched by AI-generated insights. It paints a picture of where someone’s strengths and weaknesses may lie, but also, where performance has been below the benchmark, it may explain why.

That’s incredibly valuable to the firms we serve. They can:

• Better understand their clients who choose to make their own decisions about their portfolios.
• Validate their own portfolios managers through performance appraisals and risk measures.
• Assess and validate the quality of external portfolio managers.

Once firms know where they have behavioral gaps, they can begin to address this, which in turn can enhance performance.”

While Yainvest was founded on decades of academic research, the company is seeing a real-world impact through their work.   

“I remember the first proof of concept we did,” Myronova says. “We analysed an ETF with a target performance benchmark of 15%. But the fund underperformed, only returning 8%. That’s a significant gap. Our models independently analysed the fund and found a behavioral gap of 7%—we didn’t set the market benchmarks, but our model correctly identified behavioral gaps which corresponded to the rate of underperformance.   

Our next step was to attribute the gap to certain behaviours on a quarterly basis. The result? We identified a clear overreaction to volatility which led to suboptimal performance. This validated the work we do, and we’re in the process of analysing 30 more ETFs.” 

A sophisticated startup needs a sophisticated data provider.

“We selected Morningstar for a number of reasons,” Myronova says. “The first was the sheer level of coverage. We did our due diligence and assessed other providers, but Morningstar by far had the most comprehensive coverage.

The second reason is that Morningstar is renowned for its research. As a behavioral finance company, that's important to us. We refer to the research often, and it’s something we can share with clients.  

And finally, the overall values of Morningstar align nicely with ours. Our long-term mission is to help clients deliver the best results. Morningstar is focused on empowering investor success, so it’s a natural match.” 

Yulia Myronova has not received any cash or non-cash compensation from Morningstar, directly or indirectly, in exchange for this client success story. 

Disclosure: Yainvest’s advisory board includes an employee of Morningstar.