2014-09-02

Co.Labs

How The Super-Rich Use Data Science To Get Even Richer

This is hyper-personalized wealth management for the 1%.



A little-known analytics company in Silicon Valley with ties to one of the NSA’s favorite tech tools is using big data for an unlikely end: managing the personal finances of the world’s super-wealthy.

Addepar is a wealth management platform whose engineer base comes largely from companies Google and Facebook, and is headed by Palantir cofounder Joe Lonsdale and early-stage engineer Eric Poirier. The company’s selling point is simple—they feel the rich can become even richer by harnessing real-time analytics, and they can help.

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Co.Labs spoke with Poirier, Lonsdale (the company’s executive chairman), and COO Karen White earlier this year. In the conversation, Lonsdale claimed that Addepar’s products would "transform" the way wealth portfolios are handled. Essentially, the company’s core product—a wealth management platform that is able to work in real time with wildly different sorts of data and detect relationships between them in real time—is designed to act as a dashboard and a sort of consultant to personal wealth advisors.

Palantir, where both Lonsdale and Poirier play key roles, is a data analysis firm that produces relational software that’s used by the NSA, the CIA, the FBI, and others to examine huge data sets and track relationships between individuals and groups. Alongside Palantir’s intelligence- and law-enforcement uses, its tools are commonly used by the finance sector for purposes like tracking relationships between exotic financial instruments and predicting the returns of complicated investment packages. On Quora, Lonsdale said that Addepar’s platform is instead designed to create an integrated dashboard for wealth managers.

The company’s leadership all comes from the murky intersection of finance and big data. Before joining Palantir, Lonsdale was one of PayPal’s early employees and reportedly played a key role in building the company’s financial arm while still a student at Stanford. Poirier is a former Lehman Brothers quant who started a coding business at 14, and White held executive roles at database giant Oracle and hedge fund Pequot Capital.

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During our conversation, White noted the evolution of databases and their capabilities over the past several years. As cloud computing and distributed systems have gotten more prevalent, it’s become easier and easier for individuals to be able to harness huge data sets for their own purposes. Poirier also emphasized that most wealth managers in the demographic Addepar is aiming for use a suite of software tools on the job instead of one integrated platform, and that the constant switching both compromised productivity and held users back.

In a sense, Addepar and their competitors are following in the steps of consumer cloud tools such as Mint, which leverage huge data sets to automate financial record-keeping and generate insights. Personal wealth managers for the ultra-wealthy operate in a famously closed world filled with non-disclosure agreements, clubby relationships between managers, and—as the New Yorker has noted—a deliberately esoteric work culture. Addepar, with their intelligence agency data wonk backgrounds and GitHub repository, stand poised to offer a product with the enviable selling point of making its users more money… and making Addepar tons of cash in the process.

And there is a ton of cash to be made. The New York Times reports that Addepar can charge anywhere from $50,000 to over $1 million per customer. Competitors like Advent’s Black Diamond and Envestnet Tamarac also reportedly work with similar sums. However, Addepar has a strong suit: Name recognition and strong roots in a Silicon Valley flush with suddenly rich tech stars with more money than they know what to do with. Addepar and their competitors are applying the same machine learning and predictive analytics techniques found in nearly every other vertical to wealth management—except here, they can make much more money from it.

[Stock market graph: leungchopan via Shutterstock]




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