Upstart manager seeks to unseat S&P 500 by asking investors for personal data instead of fees

Delphia's unique business model hopes to drive performance by culling data provided by investors. Skeptics say it might be too clever to succeed.

In a world where investors can gain exposure to the entire global equity markets for just a few basis points, it’s hard to say if there is still room to compete on price. But New York upstart Delphia is pulling out all stops to carve out a niche.

The venture capital-backed enterprise, marketed as a “membership-based investment collective where people pool their data to gain access to exclusive investment strategies,” hopes to gain traction with its Delphia 500 strategy that aims to beat the S&P 500 Index.

“The S&P 500 is foundational amongst almost all investor portfolios, and the Delphia 500 will look to improve upon its reliable returns by leveraging the same AI used to pick the stocks in the company’s hedge fund,” Delphia announced.

“In order for Main Street to compete with Wall Street when it comes to building wealth, people need access to premium investment strategies that can fit within any financial plan,” said Delphia Chief Executive Andrew Peek.

“The Delphia 500 was created to meet these needs and rival a staple of modern portfolio construction, the S&P 500,” he added. “Instead of aiming for average returns, our strategy will actively re-balance the portfolio based on trends identified in vast amounts of data. This dynamic approach is what makes the strategy unique and allows our members to pursue above-average returns at a time when markets are falling flat.”

Critics of any strategy looking to unseat the proven success of a dirt-cheap, large-cap growth index are plentiful even if they do offer the occasional hat tip to Delphia for its creativity.

“This is such a tough area to sell active management; almost nobody believes you can beat the large-cap index,” said Eric Balchunas, fund analyst at Bloomberg Intelligence.

On Delphia’s strategy to offer free investment management in exchange for the personal data it needs to operate the strategy, Balchunas isn’t convinced the investor appetite is there.

“Giveaways are not enough to overcome beta when it comes to the large-cap space,” he said. “If Vanguard or BlackRock did this, I’d give it a little more credibility, but as a new issuer, it makes it more difficult. People are skeptical of the unknown and they’re pretty OK paying three or four basis points.”

Paul Schatz, president of Heritage Capital, is writing Delphia off as “another gimmick in the investing world.” He also pokes fun at Delphia’s 13-year, back-tested performance models that show an average annual return over the S&P 500 of 1.5%.

“It looks like the company has outperformed the S&P 500 in one single year, and everything else is a hypothetical back-test,” he said. “In my 33 years in the business, I have never met anyone who sells products based on poor back-tests.”

Performance skepticism aside, Schatz said he would not be comfortable sharing his personal data in lieu of investment management fees.

“The idea of selling my personal data doesn’t sit well for investment research although I have no idea what that means exactly,” he said.

Todd Rosenbluth, head of research at VettaFi, also cited the data sharing as a potential red flag.

“While artificial intelligence that can help in making stock selections and hedge fund strategies available to the general public is admirable, investors should be wary of anything available for free as it means they are the source of revenue,” he said.

Delphia has set the no-fee minimum investment at $150. Any investments beyond $150 are charged a data fee, according to Peek.

“Our users can select exactly what sources of information we have access to and will use to inform the Delphia 500 and other investment strategies in the near future,” he said. “We ask our users to give us access to their credit card, social media, location, and trading data. The analysis of the data that our users elect to share with us will play an integral role in the evolution of our trading algorithms, which will continue to improve our stock selection as the data set grows.”