Hope springs eternal in the digital wealth management world.

Two new startups are advocating approaches that they say set them apart from the heated competition between Betterment, Wealthfront or even Vanguard and Schwab's digital offerings.

As part of their pitch, both young firms tout the specific expertise of their founders providing unique value to their offerings.

Seattle-based Kavout bills itself as powered by a machine learning engine built by engineers with impressive tech pedigrees; qplum, based in Jersey City, NJ, stresses the rigor of its algorithms, developed and self-financed by high frequency trading veterans.

Kavout's core program is called Kai, and it constantly is filtering millions of data points, such as SEC filings and historical market data, to find correlations and come up with suggestions and viewpoints, says Cindy Zu, Kavout's head of business development.

"It's powerful enough and smart enough to find the things that humans can't find and make the invisible, visible," adds Zu, who was so impressed by the technology offered by Kavout she joined from JP Morgan Asset Management.

Kavout's co-founder and CEO is Alex Lu, a former senior engineer at Google who also was the engineering director at Chinese search engine Baidu, and Zu says he's been able to attract top engineering talent to the startup as a result.

Kavout's offering is different than the "cute AI," currently in wealth management, says Cindy Zu, its head of business development.
Kavout's offering is different than the "cute AI," currently in wealth management, says Cindy Zu, its head of business development.

The platform, though, does not have a Wall Street ethos -- it is currently being offered for free and Zu says the motivation in developing Kavout was to offer hedge fund tools to the individual investor.

"We can't deny the landscape is changing," Zu says. "The playing field should be leveled."

She stresses that Kavout's artificial intelligence is unlike other "cute AI" being offered in digital advice, as it is being applied to the difficult task of sentiment analysis -- delving into unstructured text such as business news -- to determine stock indicators.

The firm officially launched at the beginning of August, and is backed by angel investors at this time, Zu notes. It has plans to target the adviser market too and is considering strategic partnerships, she says.

"We'd want to empower wealth advisers," Zu says. "Kai could power a brokerage, be a platform for trading, or the basis for a robo adviser."

A GOOD START
Already operating as a registered adviser with 31 clients and $4.5 million in assets is qplum, which its co-founder, Mansi Singhal, says is a good start for a firm that quietly launched in February.

With a decade of experience as a portfolio manager and trader, Singhal says it was in 2015 that she and qplum's co-founder, Gaurav Chakravorty -- a successful algorithmic trader -- began discussing the implications of the financial world's digitization.

Like Kavout, Singhal and Chakravorty decided it was time to bring the knowledge of hedge funds to retail investing, sensing an opportunity in the rise of passive investing and robo advice.

"At some point people are going to look at, 'What am I being sold?" Singhal says. "We have always been traders and asset managers. We want to manage the money where it sits."

Spoken like the computer scientist that she is, Singhal takes pride in qplum's data-driven approach. "I am a believer of data over tradition," she says. "If I have a hypothesis in my head, I'll test it with data."

Because of the team's trading experience, qplum is able to pass on savings to its clients, she says, such as executing its own trades rather than placing market orders, and utilizing its own algorithms for investing. "We provide trading strategies instead of products," Singhal says.

She adds that the firm will explore institutional offerings, but it is still early stages.

Contemplating the rise of robo advice, Singhal raises a point of concern. The onboarding process for qplum clients is longer than most, she says, but that's intentional.

"There's a perception being put out by some brands that investing is a lot of short term work for the long term benefit, and that's misleading. The wrong expectations are being set.

"Investing is a lot of hard work," she continues. "Trading was a humbling experience for me."