Year: 2018

24 Apr 2018

Digit’s first move beyond saving money is a feature to pay down credit card debt

Digit, the developer of a wildly popular automatic savings mobile app, is moving beyond its core business with a new feature enabling users to pay down credit card debt from their Digit account.

Announced earlier today the new Digit Pay service, which uses savings in a Digit account to pay off credit card debt for any registered account.

The new feature works by enabling users to create a “credit card debt” goal in their Digit settings and activate the Digit Pay service. Digit automatically will begin to save money from a linked checking account — and use those funds to pay off credit cards. Credit card payments can even be prioritized through Digit’s boost feature.

So far, the Digit app has been used to save roughly $1 billion for its customers according to chief executive officer Ethan Bloch .

Bloch says that Digit has been focused on solving the biggest financial pain points for the most customers it can reach in the U.S. For the company, that meant starting with savings…. and moving on to the next biggest threat to customers’ financial health in the U.S. — debt.

Roughly 75% of the company’s customers have credit card debt (hi, my name is Jon and I’m a Digit customer).

In the U.S. there’s about $1 trillion of credit card debt outstanding — a stat that’s very no bueno for the U.S. economy. Add to that, an average U.S. household owes about $16,883 and pays about $1,292 in interest each year (credit card companies thank you).

For folks who need a refresher in how Digit works, the company’s app provides a service that connects to checking accounts from almost any bank . Digit’s software analyzes income and spending and then sets aside small amounts of money at intervals that won’t impact an account. The company offers a 1% annualized savings bonus for people who save with Digit for three months, and the service costs $2.99 per month after a free 100 day trial period.

Those savings are placed in a rainy day fund or toward any other financial goals that a user sets in the app. They can be customized, and the latest customization is this Digit Pay option.

It’s the first time that Digit is linking back out to other vendors and it paves the way for other services using the Digit balance.

One thing that users shouldn’t expect to see anytime soon is an investment feature in Digit, according to Bloch. “Digit was founded to make financial health effortless,” Bloch said. While investment tools are good for helping their users make more money, Bloch said they weren’t core to his view of financial health.

“We’ll be focused on those two… savings and credit card debt,” he said.

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24 Apr 2018

New numbers illustrate how fast fundraising has changed for young startups

Fundraising is never easy, but it’s even harder when the goal posts are being moved around. Such is the challenge facing today’s youngest startups, which are looking at very different fundraising metrics than new startups did just six or seven years ago.

We explored the issue yesterday with Peter Wagner, who spent more than 14 years with Accel as a managing partner before co-founding the early-stage firm Wing Venture Capital in 2013 with another veteran investor, Gaurav Garg, formerly of Sequoia Capital.

Wagner has an obvious interest in how rounds are changing. Wing has to know how much is reasonable to expect to invest in a company, even while it prefers to invest in companies that don’t yet have revenue or customers. In a competitive funding landscape, its now four-person investing team is also looking to raise the firm’s profile by publishing smart industry research, including, not so long ago, on the state of IoT.

Whatever Wing’s motivations, its findings are worth tracking if you’re a founder who is thinking about raising either a seed or Series A round any time soon. More from our chat with Wagner, along with Wing’s data, follows.

TC: Your second fund, $300 million, was nearly twice the size of your $160 million debut fund. Do you expect your third fund will be even larger? Is this going to be an Accel-size firm some day?

PW: No, we’re actually working hard to keep a lid on our fund size. Early-stage investing doesn’t scale. For us to grow, we’d have to change our investing strategy.

TC: So many firms are doing exactly that, with the notable exception of Benchmark, which has maintained its fund size for the last 18 years roughly. 

PW: I was at Accel when we were [expanding into] having a later-stage practice. We sought out different skills [from potential hires] because it’s a different process. It fact, the more we learned about it, the more we realized how different a discipline it is.

TC: Given that you’re so focused on early-stage financing dynamics, tell us what you’ve learned. How did you put together this new report?

PW: We looked at companies that were funded by the 20 or so leading venture firms between 2010 and 2017. It’s 2,700 companies altogether, and 5,800 financings. If a company raised a seed fund from another firm, but Sequoia led its Series A, all of its financings rounds, including that seed round, were incorporated into our research. We also focused on these companies’ downstream financings [no matter the investors].

TC: So some of these companies are pretty new. Others are eight years old. What should founders know about the numbers?

PW: Today’s seed round is larger than the average Series A round was in 2010, which wasn’t all that long ago. The average Series A in 2010 was $4.9 million; by last year, it had reached $12.1 million. The average seed round in 2010 was $1.4 million; as of last year, it was $6.3 million.

TC: That’s a massive uptick, obviously. Do you find it worrying?

PW: Not necessarily. It’s a reflection of the changing strategies of major venture firms. Those defined as Series A investors have mostly adopted a later-stage posture and at scale. And when you’re scaling a venture firm, you’ll do more later-stage investing because you can invest more money. That’s one of the things pulling up Series A sizes.

TC: Looking at another of your charts, it looks like the companies raising A rounds have to be a lot further along than was formerly the case. That’s not exactly a news flash, but it’s still interesting. Perhaps more telling is that 67 percent of them were already generating revenue, unlike 11 percent of their peers in 2010. The same is playing out for seed investments, looks like.

PW: Yes, just 9 percent of seed-funding companies were generating revenue back in 2010; last year, more than half of them were.

VC: So much for “venture” investing. Since everyone is taking so much less risk on these companies at the seed and Series A stage, are they getting less in terms of their ownership of these startups?

PW: Ownership percentages [outside of Wing] are hard to get, other than in IPO prospectuses. Based on anecdotal data and what I’ve observed, major firms are still looking for the same ownership percentages. They’re just paying a lot more for it.

TC: You have other interesting data, including around the number of financings that startups are sealing up before they get to the Series A. It used to be A was the second round. Now, companies have raised nearly three rounds before they get to that point.

That seems not great for founders, who are giving away part of their company with every financing.

PW: As you know, “pre-seed” is a thing now, as are “seed plus” financings. So you have this segmentation within the world of seed before you get to post-adoption, where you have some evidence that things are working and investors can see how rapidly. Seed is the new A.

As for whether founders own less because of this trend, that’s a hard one to track, again because ownership stats are the last ones you’ll find.

TC: Well, you’re investing very early on, at the pre-seed or pre-adoption phase in many cases. Are you still taking the 20 percent that you looked to own when you were doing Series A deals that looked more like seed deals?

PW: Ideally. Other times, we’ll start with a smaller position and build up to that. We play the role of go-to partner, so we want to be in that ownership position.

TC: With things shifting around so much, where is the Valley of Death these days? You obviously have to have a strong startup to land Series A funding.

PW: It’s interesting. Major firms have adopted these scaled-up strategies and they’ve outsourced a lot of the adoption work to investors and incubators and angel investors, who are launching a fleet of a thousand ships. That enables the firms to hang around and see which startups look the best and pick and choose.

What’s notable is they don’t have as much vested interest in companies at the Series A because it’s very different when you make a new investment versus a follow-on investment. It used to be that individuals at these firms were involved much earlier. 

I’m not sure if that’s a healthy or unhealthy development. But it does mean that seed firms have been presented with this expanded territory from which these other firms have backed away. Somebody has to do the foundation building. It’s a great opportunity for seed investors to play a bigger role, but it can certainly be a confusing time for founders, with investors changing, along with the criteria for who you let into your inner circle.

TC: You’ve been in venture for more than 20 years. Is there a correction coming or has something fundamentally changed?

PW: There will be a correction. There will always be a correction. Every time we’ve ever thought the cycle has been broken, we’ve been proven wrong. VC is cyclical. What I don’t know is the date of that correction or how deep it will be.

TC: Do you think venture firms should be raising such gigantic funds right now, given this likelihood? 

PW: The last time around [in the late ’90s], a bunch of people raised really big funds and wound up releasing half the capital or more back to their limited partners when the market changed. Returns on big funds have always disappointed. Things do change and tech is a much more important ingredient. But I do think this is still a boom-bust business.

24 Apr 2018

New numbers illustrate how fast fundraising has changed for young startups

Fundraising is never easy, but it’s even harder when the goal posts are being moved around. Such is the challenge facing today’s youngest startups, which are looking at very different fundraising metrics than new startups did just six or seven years ago.

We explored the issue yesterday with Peter Wagner, who spent more than 14 years with Accel as a managing partner before co-founding the early-stage firm Wing Venture Capital in 2013 with another veteran investor, Gaurav Garg, formerly of Sequoia Capital.

Wagner has an obvious interest in how rounds are changing. Wing has to know how much is reasonable to expect to invest in a company, even while it prefers to invest in companies that don’t yet have revenue or customers. In a competitive funding landscape, its now four-person investing team is also looking to raise the firm’s profile by publishing smart industry research, including, not so long ago, on the state of IoT.

Whatever Wing’s motivations, its findings are worth tracking if you’re a founder who is thinking about raising either a seed or Series A round any time soon. More from our chat with Wagner, along with Wing’s data, follows.

TC: Your second fund, $300 million, was nearly twice the size of your $160 million debut fund. Do you expect your third fund will be even larger? Is this going to be an Accel-size firm some day?

PW: No, we’re actually working hard to keep a lid on our fund size. Early-stage investing doesn’t scale. For us to grow, we’d have to change our investing strategy.

TC: So many firms are doing exactly that, with the notable exception of Benchmark, which has maintained its fund size for the last 18 years roughly. 

PW: I was at Accel when we were [expanding into] having a later-stage practice. We sought out different skills [from potential hires] because it’s a different process. It fact, the more we learned about it, the more we realized how different a discipline it is.

TC: Given that you’re so focused on early-stage financing dynamics, tell us what you’ve learned. How did you put together this new report?

PW: We looked at companies that were funded by the 20 or so leading venture firms between 2010 and 2017. It’s 2,700 companies altogether, and 5,800 financings. If a company raised a seed fund from another firm, but Sequoia led its Series A, all of its financings rounds, including that seed round, were incorporated into our research. We also focused on these companies’ downstream financings [no matter the investors].

TC: So some of these companies are pretty new. Others are eight years old. What should founders know about the numbers?

PW: Today’s seed round is larger than the average Series A round was in 2010, which wasn’t all that long ago. The average Series A in 2010 was $4.9 million; by last year, it had reached $12.1 million. The average seed round in 2010 was $1.4 million; as of last year, it was $6.3 million.

TC: That’s a massive uptick, obviously. Do you find it worrying?

PW: Not necessarily. It’s a reflection of the changing strategies of major venture firms. Those defined as Series A investors have mostly adopted a later-stage posture and at scale. And when you’re scaling a venture firm, you’ll do more later-stage investing because you can invest more money. That’s one of the things pulling up Series A sizes.

TC: Looking at another of your charts, it looks like the companies raising A rounds have to be a lot further along than was formerly the case. That’s not exactly a news flash, but it’s still interesting. Perhaps more telling is that 67 percent of them were already generating revenue, unlike 11 percent of their peers in 2010. The same is playing out for seed investments, looks like.

PW: Yes, just 9 percent of seed-funding companies were generating revenue back in 2010; last year, more than half of them were.

VC: So much for “venture” investing. Since everyone is taking so much less risk on these companies at the seed and Series A stage, are they getting less in terms of their ownership of these startups?

PW: Ownership percentages [outside of Wing] are hard to get, other than in IPO prospectuses. Based on anecdotal data and what I’ve observed, major firms are still looking for the same ownership percentages. They’re just paying a lot more for it.

TC: You have other interesting data, including around the number of financings that startups are sealing up before they get to the Series A. It used to be A was the second round. Now, companies have raised nearly three rounds before they get to that point.

That seems not great for founders, who are giving away part of their company with every financing.

PW: As you know, “pre-seed” is a thing now, as are “seed plus” financings. So you have this segmentation within the world of seed before you get to post-adoption, where you have some evidence that things are working and investors can see how rapidly. Seed is the new A.

As for whether founders own less because of this trend, that’s a hard one to track, again because ownership stats are the last ones you’ll find.

TC: Well, you’re investing very early on, at the pre-seed or pre-adoption phase in many cases. Are you still taking the 20 percent that you looked to own when you were doing Series A deals that looked more like seed deals?

PW: Ideally. Other times, we’ll start with a smaller position and build up to that. We play the role of go-to partner, so we want to be in that ownership position.

TC: With things shifting around so much, where is the Valley of Death these days? You obviously have to have a strong startup to land Series A funding.

PW: It’s interesting. Major firms have adopted these scaled-up strategies and they’ve outsourced a lot of the adoption work to investors and incubators and angel investors, who are launching a fleet of a thousand ships. That enables the firms to hang around and see which startups look the best and pick and choose.

What’s notable is they don’t have as much vested interest in companies at the Series A because it’s very different when you make a new investment versus a follow-on investment. It used to be that individuals at these firms were involved much earlier. 

I’m not sure if that’s a healthy or unhealthy development. But it does mean that seed firms have been presented with this expanded territory from which these other firms have backed away. Somebody has to do the foundation building. It’s a great opportunity for seed investors to play a bigger role, but it can certainly be a confusing time for founders, with investors changing, along with the criteria for who you let into your inner circle.

TC: You’ve been in venture for more than 20 years. Is there a correction coming or has something fundamentally changed?

PW: There will be a correction. There will always be a correction. Every time we’ve ever thought the cycle has been broken, we’ve been proven wrong. VC is cyclical. What I don’t know is the date of that correction or how deep it will be.

TC: Do you think venture firms should be raising such gigantic funds right now, given this likelihood? 

PW: The last time around [in the late ’90s], a bunch of people raised really big funds and wound up releasing half the capital or more back to their limited partners when the market changed. Returns on big funds have always disappointed. Things do change and tech is a much more important ingredient. But I do think this is still a boom-bust business.

24 Apr 2018

MobileCoin, a cryptocurrency from the creator of Signal, just raised $30M for private mobile payments

A new privacy-centric cryptocurrency project with some big names on board just raised a round worth noting. On Tuesday, the team at MobileCoin announced that Binance Labs, the major blockchain incubator associated with the Binance exchange, led a $30 million round denominated in bitcoin and ether for the new cryptocurrency. MobileCoin will enjoy “priority consideration” for being listed on Binance as part of the relationship.

New cryptocurrency projects are a dime (or less) a dozen, but the legitimacy of an established name can make all the difference. Moxie Marlinspike, the founder of end-to-end encryption messaging app Signal and Open Whisper Systems, is one such name. As Wired reported in December, Marlinspike began working with MobileCoin as a technical advisor in August of 2017.

Marlinspike is joined by Joshua Goldbard, a general partner at hedge fund Crypto Lotus and MobileCoin technologist, and Shane Glynn, legal counsel, to help the company navigate the choppy waters of cryptocurrency regulation. Glynn has served since 2010 as senior product counsel at Google, though it’s not clear if he is leaving his longtime role for the new project.

In the MobileCoin whitepaper, published in December, the project’s creators describe its mission:

…Most attempts at building a compelling crypto-currency user experience unfortunately resort to trusting a third party service to manage keys and validate transactions. This largely sacrifices the primary benefits offered by crypto-currency to begin with.

MobileCoin is an effort to develop a fast, private, and easy-to-use cryptocurrency that can be deployed in resource constrained environments to users who aren’t equipped to reliably maintain secret keys over a long period of time, all without giving up control of funds to a payment processing service.

MobileCoin transactions will synchronize to the coin’s network using the Stellar Consensus Protocol for scalability and speed. The end product will emphasize user privacy and integration into mobile messaging apps, including WhatsApp and Signal — two apps that use Marlinspike’s end-to-end encrypted Signal Protocol.

“MobileCoin is designed so that a mobile messaging application like WhatsApp, Facebook Messenger, or Signal could integrate with a MobileCoin wallet,” the team described in its whitepaper.

Marlinspike is a rare sort of reverse tech celebrity, a figure who eschews both spotlight and Silicon Valley-style excess and has instead cultivated quiet respect in digital privacy and cryptography circles. That makes him an odd fit for the fraud-laden universe of empty multi-million-dollar ICOs with no product to speak of, but it also means that MobileCoin is probably worth paying attention to. At the very least, the prominent cryptographer’s new project should amuse anyone who’s complained about the digital currency world’s habit of using the term “crypto” as shorthand for “cryptocurrency.”

MobileCoin has funding and talent, but it’s still very early days for the nascent cryptocurrency. As an incubator, Binance Labs concentrates on pre-ICO projects and MobileCoin will use the funding to “build out [its] team and processes” as it develops its product.

“A mobile-first, user-friendly cryptocurrency, like MobileCoin, plays a critical role in driving mainstream cryptocurrency adoption,” Binance Labs said of the funding. “The MobileCoin team and Binance Labs share a common vision and we are proud to be a supporter of what they are doing.”

Along with the news, MobileCoin announced that it is recruiting a “core team” of engineers:

“Specifically, we are looking for those who have worked on large systems (greater than 10,000,000 daily active users) in a senior role who enjoy working on low-level code. Direct memory access is a critical part of our problem set.”

Given the legitimacy of Marlinspike’s best-known project and his reticence to attach his name to things, it’s not unreasonable to give MobileCoin the benefit of the doubt, even if aspects of its raison d’être remain unarticulated. Beyond the core question of why a new cryptocurrency needs to exist at all, MobileCoin will need to position itself as a compelling alternative to existing mainstream mobile payment services like Venmo and PayPal for normal users.

MobileCoin will also face the full slate of regulatory challenges, including fraud prevention, that plague other digital currency projects, though given its stealthy behavior and the fact that one-third of the three-member team listed on its website represents legal counsel, its founders are don’t appear to be charging in recklessly.

“This is a journey and we are excited to build a simple system for trusted payments,” Goldbard wrote in the announcement.

In the digital currency realm, too much style — think celeb-endorsed ICOs and endless press release hype cycles — can signal a lack of substance. The reverse can be true too, and in MobileCoin’s case, a modest mission could be a strong signal for a compelling product a bit further down the blockchain.

24 Apr 2018

MobileCoin, a cryptocurrency from the creator of Signal, just raised $30M for private mobile payments

A new privacy-centric cryptocurrency project with some big names on board just raised a round worth noting. On Tuesday, the team at MobileCoin announced that Binance Labs, the major blockchain incubator associated with the Binance exchange, led a $30 million round denominated in bitcoin and ether for the new cryptocurrency. MobileCoin will enjoy “priority consideration” for being listed on Binance as part of the relationship.

New cryptocurrency projects are a dime (or less) a dozen, but the legitimacy of an established name can make all the difference. Moxie Marlinspike, the founder of end-to-end encryption messaging app Signal and Open Whisper Systems, is one such name. As Wired reported in December, Marlinspike began working with MobileCoin as a technical advisor in August of 2017.

Marlinspike is joined by Joshua Goldbard, a general partner at hedge fund Crypto Lotus and MobileCoin technologist, and Shane Glynn, legal counsel, to help the company navigate the choppy waters of cryptocurrency regulation. Glynn has served since 2010 as senior product counsel at Google, though it’s not clear if he is leaving his longtime role for the new project.

In the MobileCoin whitepaper, published in December, the project’s creators describe its mission:

…Most attempts at building a compelling crypto-currency user experience unfortunately resort to trusting a third party service to manage keys and validate transactions. This largely sacrifices the primary benefits offered by crypto-currency to begin with.

MobileCoin is an effort to develop a fast, private, and easy-to-use cryptocurrency that can be deployed in resource constrained environments to users who aren’t equipped to reliably maintain secret keys over a long period of time, all without giving up control of funds to a payment processing service.

MobileCoin transactions will synchronize to the coin’s network using the Stellar Consensus Protocol for scalability and speed. The end product will emphasize user privacy and integration into mobile messaging apps, including WhatsApp and Signal — two apps that use Marlinspike’s end-to-end encrypted Signal Protocol.

“MobileCoin is designed so that a mobile messaging application like WhatsApp, Facebook Messenger, or Signal could integrate with a MobileCoin wallet,” the team described in its whitepaper.

Marlinspike is a rare sort of reverse tech celebrity, a figure who eschews both spotlight and Silicon Valley-style excess and has instead cultivated quiet respect in digital privacy and cryptography circles. That makes him an odd fit for the fraud-laden universe of empty multi-million-dollar ICOs with no product to speak of, but it also means that MobileCoin is probably worth paying attention to. At the very least, the prominent cryptographer’s new project should amuse anyone who’s complained about the digital currency world’s habit of using the term “crypto” as shorthand for “cryptocurrency.”

MobileCoin has funding and talent, but it’s still very early days for the nascent cryptocurrency. As an incubator, Binance Labs concentrates on pre-ICO projects and MobileCoin will use the funding to “build out [its] team and processes” as it develops its product.

“A mobile-first, user-friendly cryptocurrency, like MobileCoin, plays a critical role in driving mainstream cryptocurrency adoption,” Binance Labs said of the funding. “The MobileCoin team and Binance Labs share a common vision and we are proud to be a supporter of what they are doing.”

Along with the news, MobileCoin announced that it is recruiting a “core team” of engineers:

“Specifically, we are looking for those who have worked on large systems (greater than 10,000,000 daily active users) in a senior role who enjoy working on low-level code. Direct memory access is a critical part of our problem set.”

Given the legitimacy of Marlinspike’s best-known project and his reticence to attach his name to things, it’s not unreasonable to give MobileCoin the benefit of the doubt, even if aspects of its raison d’être remain unarticulated. Beyond the core question of why a new cryptocurrency needs to exist at all, MobileCoin will need to position itself as a compelling alternative to existing mainstream mobile payment services like Venmo and PayPal for normal users.

MobileCoin will also face the full slate of regulatory challenges, including fraud prevention, that plague other digital currency projects, though given its stealthy behavior and the fact that one-third of the three-member team listed on its website represents legal counsel, its founders are don’t appear to be charging in recklessly.

“This is a journey and we are excited to build a simple system for trusted payments,” Goldbard wrote in the announcement.

In the digital currency realm, too much style — think celeb-endorsed ICOs and endless press release hype cycles — can signal a lack of substance. The reverse can be true too, and in MobileCoin’s case, a modest mission could be a strong signal for a compelling product a bit further down the blockchain.

24 Apr 2018

Four MIT students have launched DeepBench to democratize access to expert networks

New European financial regulations requiring fund managers at investment firms to pay banks for research and trading services separately could open the door for new entrants in the professional advisory services marketplace.

The rules, which were approved in 2014, but only took effect in January, are proving to be a boon for four MIT students who launched a company last year to try to grab some of the market.

DeepBench, founded by Devin Basinger, Yishi Zuo, Derek Hans and Nikhil Punwaney, is proposing some novel business model solutions to address what the MIT students see as flaws in the existing market — particularly around the use of expert networks in financial advisory services.

DeepBench co-founders Devin Basinger, Nikhil Punwaney, Derek Hans and Yishi Zuo

Expert networks are communities of experienced professionals in a given field. Fortune 500 companies, hedge funds, private equity firms and other entities rely on individuals from these groups for their insights and expertise. The biggest company in the expert network industry, Gerson Lerman Group (GLG), has nearly 50 percent market share and was on track to reach $400 million in revenue in 2016.

But GLG has had its share of troubles. The company played an integral role in providing the expert that passed confidential information to an SAC Capital trader, which was used as evidence in an insider trading case against the firm and its owner, Steven A. Cohen. The hedge fund ended up paying a record $1.8 billion in fines to the SEC (they did not admit wrongdoing in the case).

There is a significant opportunity to disrupt the expert networking space. As more experienced workers retire, some may want to continue putting their skills to use, albeit in a reduced capacity. Being a part of an expert network allows them to be available for clients who request their expertise in a flexible, convenient capacity. Facilitating this specialized knowledge sharing is a billion-dollar market for the taking.

Aside from established players like GLG and its European competitors, AlphaSights and Third Bridge, other startups like Clarity, Slingshot Insights, Catalant (formerly known as HourlyNerd) and Dūcō are also looking to transform the way expert networking is done. GLG is known to charge a group of four within a firm $100,000 for basic access to their network for a year. In comparison, these startups have different approaches and business models to improving the way clients access the expertise they need. Their efforts reflect two main segments within the expert network market: expert calls and project-based work.

DeepBench and Slingshot Industries are focusing their efforts on expert calls. DeepBench launched its current service in March 2017, which uses its “technology-driven, human-assisted” platform to connect individual clients with available experts for a 30 to 60-minute conversation at an agreed-upon rate. In addition, the startup does not require “learners” to sign long-term contracts or prepay, unlike other firms, allowing for greater client flexibility. Slingshot Industries matches groups of clients with similar interests to an expert to answer their questions. The group would crowdfund the cost for chatting with the expert.

Catalant and Dūcō have aimed for matching clients that need long-term projects completed with the relevant experienced contractor. These clients are looking for experts who are interested in extended-duration work. Catalant leverages its algorithms to quickly match prospective clients with the experts they are looking for based on the former’s search criteria.

Their goal is to make this process seamless, so more experts and clients will feel enabled to collaborate outside of a conventional consulting framework or contracting arrangement. Dūcō appears to take a more conventional approach to connecting clients and experts. The D.C.-based startup vets its pool of experts before offering them up to potential clients. Like Catalant, Dūcō uses matching algorithms to match clients with project work needs to experts ready to assist them.

As investors seek information to keep their competitive edge, and firms need outside help in solving internal problems, on-demand access to expert networks will become necessary. DeepBench currently has more than 1,000 registered experts for their closed beta platform. Currently, more than 20 clients are using the service. Most are top consulting companies, investors and product designers.

“We are focused on finding quality high-fit advisors right now instead of increasing the volume we can have available for clients,” Basinger said.

With a shift in E.U. financial regulations, expert networks are using their momentum in the Asian and U.S. markets to establish themselves in Europe. This specialized knowledge sharing can be shaped by startups like DeepBench as competition between firms continues to intensify.

24 Apr 2018

Four MIT students have launched DeepBench to democratize access to expert networks

New European financial regulations requiring fund managers at investment firms to pay banks for research and trading services separately could open the door for new entrants in the professional advisory services marketplace.

The rules, which were approved in 2014, but only took effect in January, are proving to be a boon for four MIT students who launched a company last year to try to grab some of the market.

DeepBench, founded by Devin Basinger, Yishi Zuo, Derek Hans and Nikhil Punwaney, is proposing some novel business model solutions to address what the MIT students see as flaws in the existing market — particularly around the use of expert networks in financial advisory services.

DeepBench co-founders Devin Basinger, Nikhil Punwaney, Derek Hans and Yishi Zuo

Expert networks are communities of experienced professionals in a given field. Fortune 500 companies, hedge funds, private equity firms and other entities rely on individuals from these groups for their insights and expertise. The biggest company in the expert network industry, Gerson Lerman Group (GLG), has nearly 50 percent market share and was on track to reach $400 million in revenue in 2016.

But GLG has had its share of troubles. The company played an integral role in providing the expert that passed confidential information to an SAC Capital trader, which was used as evidence in an insider trading case against the firm and its owner, Steven A. Cohen. The hedge fund ended up paying a record $1.8 billion in fines to the SEC (they did not admit wrongdoing in the case).

There is a significant opportunity to disrupt the expert networking space. As more experienced workers retire, some may want to continue putting their skills to use, albeit in a reduced capacity. Being a part of an expert network allows them to be available for clients who request their expertise in a flexible, convenient capacity. Facilitating this specialized knowledge sharing is a billion-dollar market for the taking.

Aside from established players like GLG and its European competitors, AlphaSights and Third Bridge, other startups like Clarity, Slingshot Insights, Catalant (formerly known as HourlyNerd) and Dūcō are also looking to transform the way expert networking is done. GLG is known to charge a group of four within a firm $100,000 for basic access to their network for a year. In comparison, these startups have different approaches and business models to improving the way clients access the expertise they need. Their efforts reflect two main segments within the expert network market: expert calls and project-based work.

DeepBench and Slingshot Industries are focusing their efforts on expert calls. DeepBench launched its current service in March 2017, which uses its “technology-driven, human-assisted” platform to connect individual clients with available experts for a 30 to 60-minute conversation at an agreed-upon rate. In addition, the startup does not require “learners” to sign long-term contracts or prepay, unlike other firms, allowing for greater client flexibility. Slingshot Industries matches groups of clients with similar interests to an expert to answer their questions. The group would crowdfund the cost for chatting with the expert.

Catalant and Dūcō have aimed for matching clients that need long-term projects completed with the relevant experienced contractor. These clients are looking for experts who are interested in extended-duration work. Catalant leverages its algorithms to quickly match prospective clients with the experts they are looking for based on the former’s search criteria.

Their goal is to make this process seamless, so more experts and clients will feel enabled to collaborate outside of a conventional consulting framework or contracting arrangement. Dūcō appears to take a more conventional approach to connecting clients and experts. The D.C.-based startup vets its pool of experts before offering them up to potential clients. Like Catalant, Dūcō uses matching algorithms to match clients with project work needs to experts ready to assist them.

As investors seek information to keep their competitive edge, and firms need outside help in solving internal problems, on-demand access to expert networks will become necessary. DeepBench currently has more than 1,000 registered experts for their closed beta platform. Currently, more than 20 clients are using the service. Most are top consulting companies, investors and product designers.

“We are focused on finding quality high-fit advisors right now instead of increasing the volume we can have available for clients,” Basinger said.

With a shift in E.U. financial regulations, expert networks are using their momentum in the Asian and U.S. markets to establish themselves in Europe. This specialized knowledge sharing can be shaped by startups like DeepBench as competition between firms continues to intensify.

24 Apr 2018

Kogan: “I don’t think Facebook has a developer policy that is valid”

A Cambridge University academic at the center of a data misuse scandal involving Facebook user data and political ad targeting faced questions from the UK parliament this morning.

Although the two-hour evidence session in front of the DCMS committee’s fake news enquiry raised rather more questions than it answered — with professor Aleksandr Kogan citing an NDA he said he had signed with Facebook to decline to answer some of the committee’s questions (including why and when exactly the NDA was signed).

TechCrunch understands the NDA relates to standard confidentiality provisions regarding deletion certifications and other commitments made by Kogan to Facebook not to misuse user data — after the company learned he had user passed data to SCL in contravention of its developer terms.

Asked why he had a non disclosure agreement with Facebook Kogan told the committee it would have to ask Facebook. He also declined to say whether any of his company co-directors (one of whom now works for Facebook) had been asked to sign an NDA. Nor would he specify whether the NDA had been signed in the US.

Asked whether he had deleted all the Facebook data and derivatives he had been able to acquire Kogan said yes “to the best of his knowledge”, though he also said he’s currently conducting a review to make sure nothing has been overlooked.

A few times during the session Kogan made a point of arguing that data audits are essentially useless for catching bad actors — claiming that anyone who wants to misuse data can simply put a copy on a hard drive and “store it under the mattress”.

The UK’s data protection watchdog is currently conducting an audit of Cambridge Analytica, after obtaining a warrant to enter its London offices last month — as part of a year-long investigation into social media data use for political ad targeting.

Your company didn’t hide any data in that way did it, a committee member asked Kogan? “We didn’t,” he rejoined.

“This has been a very painful experience because when I entered into all of this Facebook was a close ally. And I was thinking this would be helpful to my academic career. And my relationship with Facebook. It has, very clearly, done the complete opposite,” Kogan continued.  “I had no interest in becoming an enemy or being antagonized by one of the biggest companies in the world that could — even if it’s frivolous — sue me into oblivion. So we acted entirely as they requested.”

Despite apparently lamenting the breakdown in his relations with Facebook — telling the committee how he had worked with the company, in an academic capacity, prior to setting up a company to work with SCL/CA — Kogan refused to accept that he had broken Facebook’s terms of service — instead asserting: “I don’t think they have a developer policy that is valid… For you to break a policy it has to exist. And really be their policy, The reality is Facebook’s policy is unlikely to be their policy.”

“I just don’t believe that’s their policy,” he said repeated when pressed again on whether he had broken Facebook’s ToS. “If somebody has a document that isn’t their policy you can’t break something that isn’t really your policy. I would agree my actions were inconsistent with the language of this document — but that’s slightly different from what I think you’re asking.”

“You should be a professor of semantics,” quipped the committee member who had been asking the questions.

A Facebook spokesperson told us it had no public comment to make on Kogan’s testimony. But last month CEO Mark Zuckerberg couched the academic’s actions as a “breach of trust” — describing the behavior of his app as “abusive”.

In evidence to the committee today, Kogan told it he had only become aware of an “inconsistency” between Facebook’s developer terms of service and what his company did in March 2015 — when he said he begun to suspect the veracity of the advice he had received from SCL. At that point Kogan said GSR reached out to an IP lawyer “and got some guidance”.

(More specifically he said he became suspicious because former SCL employee Chris Wylie did not honor a contract between GSR and Eunoia, a company Wylie set up after leaving SLC, to exchange data-sets; Kogan said GSR gave Wylie the full raw Facebook data-set but Wylie did not provide any data to GSR.)

“Up to that point I don’t believe I was even aware or looked at the developer policy. Because prior to that point — and I know that seems shocking and surprising… the experience of a developer in Facebook is very much like the experience of a user in Facebook. When you sign up there’s this small print that’s easy to miss,” he claimed.

“When I made my app initially I was just an academic researcher. There was no company involved yet. And then when we commercialized it — so we changed the app — it was just something I completely missed. I didn’t have any legal resources, I relied on SCL [to provide me with guidance on what was appropriate]. That was my mistake.”

“Why I think this is still not Facebook’s policy is that we were advised [by an IP lawyer] that Facebook’s terms for users and developers are inconsistent. And that it’s not actually a defensible position for Facebook that this is their policy,” Kogan continued. “This is the remarkable thing about the experience of an app developer on Facebook. You can change the name, you can change the description, you can change the terms of service — and you just save changes. There’s no obvious review process.

“We had a terms of service linked to the Facebook platform that said we could transfer and sell data for at least a year and a half — nothing was ever mentioned. It was only in the wake of the Guardian article [in December 2015] that they came knocking.”

He also described the work he and his company had done for SCL Elections as essentially worthless — arguing that using psychometrically modeled Facebook data for political ad targeting in the way SCL/CA had apparently sought to do was “incompetent” because they could have used Facebook’s own ad targeting platform to achieve greater reach and with more granular targeting.

“It’s all about the use-case. I was very surprised to learn that what they wanted to do is run Facebook ads,” he said. “This was not mentioned, they just wanted a way to measure personality for many people. But if the use-case you have is Facebook ads it’s just incompetent to do it this way.

“Taking this data-set you’re going to be able to target 15% of the population. And use a very small segment of the Facebook data — page likes — to try to build personality models. When do this when you could very easily go target 100% and use much more of the data. It just doesn’t make sense.”

Asked what, then, was the value of the project he undertook for SCL, Kogan responded: “Given what we know now, nothing. Literally nothing.”

He also repeated his prior claim that he was not aware that work he was providing for SCL Elections would be used for targeting political ads, though he confirmed he knew the project was focused on the US and related to elections.

He also said he knew the work was being done for the Republican party — but claimed not to know which specific candidates were involved.

Pressed by one committee member on why he didn’t care to know which politicians he was indirectly working for, Kogan responded by saying he doesn’t have strong personal views on US politics or politicians generally — beyond believing that most US politicians are at least reasonable in their policy positions.

“My personal position on life is unless I have a lot of evidence I don’t know. Is the answer. It’s a good lesson to learn from science — where typically we just don’t know. In terms of politics in particular I rarely have a strong position on a candidate,” said Kogan, adding that therefore he “didn’t bother” to make the effort to find out who would ultimately be the beneficiary of his psychometric modeling.

Kogan told the committee his initial intention had not been to set up a business at all but to conduct not-for-profit big data research — via a non-profit, big data institute he wanted to establish — claiming it was Wylie who had advised him to also set up the for-profit entity, GSR, through which he went on to engage with SCL Elections/CA.

“The initial plan was we collect the data, I fulfill my obligations to SCL, and then I would go and use the data for research,” he said.

And while Kogan maintained he had never drawn a salary from the work he did for SCL — saying his reward was “to keep the data”, and get to use it for academic research — he confirmed SCL did pay GSR £230,000 at one point during the project; a portion of which he also said eventually went to pay lawyers Kogan engaged “in the wake” of Facebook becoming aware that data had been passed to SCL/CA by Kogan — when it contacted him to ask him to delete the data (and presumably also to get him to sign an NDA).

In one curious moment, Kogan claimed not to know his own company had been registered at 29 Harley Street — which the committee noted is “used by a lot of shell companies some of which have been used for money laundering by Russian oligarchs”.

Seeming a little flustered he said initially he had registered the company at his apartment in Cambridge, and later “I think we moved it to an innovation center in Cambridge and then later Manchester”.

“I’m actually surprised. I’m totally surprised by this,” he added.

Did you use an agent to set it up, asked one committee member. “We used Formations House,” replied Kogan, referring to a company whose website states it can locate a business’ trading address “in the heart of central London” — in exchange for a small fee.

“I’m legitimately surprised by that,” added Kogan of the Harley Street address. “I’m unfortunately not a Russian oligarch.”

Later in the session another odd moment came when he was being asked about his relationship with Saint Petersburg University in Russia — where he confirmed he had given talks and workshops, after traveling to the country with friends and proactively getting in touch with the university “to say hi” — and specifically about some Russian government-funded research being conducted by researchers there into cyberbullying.

Committee chair Collins implied to Kogan the Russian state could have had a specific malicious interest in such a piece of research, and wondered whether Kogan had thought about that in relation to the interactions he’d had with the university and the researchers.

Kogan described it as a “big leap” to connect the piece of research to Kremlin efforts to use online platforms to interfere in foreign elections — before essentially going on to repeat a Kremlin talking point by saying the US and the UK engage in much the same types of behavior.

“You can make the same argument about the UK government funding anything or the US government funding anything,” he told the committee. “Both countries are very famous for their spies.

“There’s a long history of the US interfering with foreign elections and doing the exact same thing [creating bot networks and using trolls for online intimidation].”

“Are you saying it’s equivalent?” pressed Collins. “That the work of the Russian government is equivalent to the US government and you couldn’t really distinguish between the two?”

“In general I would say the governments that are most high profile I am dubious about the moral scruples of their activities through the long history of UK, US and Russia,” responded Kogan. “Trying to equate them I think is a bit of a silly process. But I think certainly all these countries have engaged in activities that people feel uncomfortable with or are covert. And then to try to link academic work that’s basic science to that — if you’re going to down the Russia line I think we have to go down the UK line and the US line in the same way.

“I understand Russia is a hot-button topic right now but outside of that… Most people in Russia are like most people in the UK. They’re not involved in spycraft, they’re just living lives.”

“I’m not aware of UK government agencies that have been interfering in foreign elections,” added Collins.

“Doesn’t mean it’s not happened,” replied Kogan. “Could be just better at it.”

During Wylie’s evidence last month the former SCL employee had implied there could have been a risk of the Facebook data falling into the hands of the Russian state as a result of Kogan’s back and forth travel to the region. But Kogan rebutted this idea — saying the data had never been in his physical possession when he traveled to Russia, pointing out it was stored in a cloud hosting service in the US.

“If you want to try to hack Amazon Web Services good luck,” he added.

He also claimed not to have read the piece of research in question, even though he said he thought the researcher had emailed the paper to him — claiming he can’t read Russian well.

Kogan seemed most comfortable during the session when he was laying into Facebook’s platform policies — perhaps unsurprisingly, given how the company has sought to paint him as a rogue actor who abused its systems by creating an app that harvested data on up to 87 million Facebook users and then handing information off to third parties.

Asked whether he thought a prior answer given to the committee by Facebook — when it claimed it had not provided any user data to third parties — was correct, Kogan said no given the company provides academics with “macro level” user data (including providing him with this type of data, in 2013).

He was also asked why he thinks Facebook lets its employees collaborate with external researchers — and Kogan suggested this is “tolerated” by management as a strategy to keep employees stimulated.

Committee chair Collins also asked whether he thought it was odd that Facebook now employs his former co-director at GSR, Joseph Chancellor — who works in its research division — despite Chancellor having worked for a company Facebook has said it regards as having violation its platform policies.

“Honestly I don’t think it’s odd,” said Kogan. “The reason I don’t think it’s odd is because in my view Facebook’s comments are PR crisis mode. I don’t believe they actually think these things — because I think they realize that their platform has been mined, left and right, by thousands of others.

“And I was just the unlucky person that ended up somehow linked to the Trump campaign. And we are where we are. I think they realize all this but PR is PR and they were trying to manage the crisis and it’s convenient to point the finger at a single entity and try to paint the picture this is a rogue agent.

At another moment during the evidence session Kogan was also asked to respond to denials previously given to the committee by former CEO of Cambridge Analytica Alexander Nix — who had claimed that none of the data it used came from GSR and — even more specifically — that GSR had never supplied it with “data-sets or information”.

“Fabrication,” responded Kogan. “Total fabrication.”

“We certainly gave them [SCL/CA] data. That’s indisputable,” he added.

In written testimony to the committee he also explained that he in fact created three apps for gathering Facebook user data. The first one — called the CPW Lab app — was developed after he had begun a collaboration with Facebook in early 2013, as part of his academic studies. Kogan says Facebook provided him with user data at this time for his research — although he said these datasets were “macro-level datasets on friendship connections and emoticon usage” rather than information on individual users.

The CPW Lab app was used to gather individual level data to supplement those datasets, according to Kogan’s account. Although he specifies that data collected via this app was housed at the university; used for academic purposes only; and was “not provided to the SCL Group”.

Later, once Kogan had set up GSR and was intending to work on gathering and modeling data for SCL/Cambridge Analytica, the CPW Lab app was renamed to the GSR App and its terms were changed (with the new terms provided by Wylie).

Thousands of people were then recruited to take this survey via a third company — Qualtrics — with Kogan saying SCL directly paid ~$800,000 to it to recruit survey participants, at a cost of around $3-$4 per head (he says between 200,000 and 300,000 people took the survey as a result in the summer of 2014; NB: Facebook doesn’t appear to be able to break out separate downloads for the different apps Kogan ran on its platform — it told us about 305,000 people downloaded “the app”).

In the final part of that year, after data collection had finished for SCL, Kogan said his company revised the GSR App to become an interactive personality quiz — renaming it “thisisyourdigitallife” and leaving the commercial portions of the terms intact.

“The thisisyourdigitallife App was used by only a few hundred individuals and, like the two prior iterations of the application, collected demographic information and data about “likes” for survey participants and their friends whose Facebook privacy settings gave participants access to “likes” and demographic information. Data collected by the thisisyourdigitallife App was not provided to SCL,” he claims in the written testimony.

During the oral hearing, Kogan was pressed on misleading T&Cs in his two commercial apps. Asked by a committee member about the terms of the GSR App not specifying that the data would be used for political targeting, he said he didn’t write the terms himself but added: “If we had to do it again I think I would have insisted to Mr Wylie that we do add politics as a use-case in that doc.”

“It’s misleading,” argued the committee member. “It’s a misrepresentation.”

“I think it’s broad,” Kogan responded. “I think it’s not specific enough. So you’re asking for why didn’t we go outline specific use-cases — because the politics is a specific use-case. I would argue that the politics does fall under there but it’s a specific use-case. I think we should have.”

The committee member also noted how, “in longer, denser paragraphs” within the app’s T&Cs, the legalese does also state that “whatever that primary purpose is you can sell this data for any purposes whatsoever” — making the point that such sweeping terms are unfair.

“Yes,” responded Kogan. “In terms of speaking the truth, the reality is — as you’ve pointed out — very few if any people have read this, just like very few if any people read terms of service. I think that’s a major flaw we have right now. That people just do not read these things. And these things are written this way.”

“Look — fundamentally I made a mistake by not being critical about this. And trusting the advice of another company [SCL]. As you pointed out GSR is my company and I should have gotten better advice, and better guidance on what is and isn’t appropriate,” he added.

“Quite frankly my understanding was this was business as usual and normal practice for companies to write broad terms of service that didn’t provide specific examples,” he said after being pressed on the point again.

“I doubt in Facebook’s user policy it says that users can be advertised for political purposes — it just has broad language to provide for whatever use cases they want. I agree with you this doesn’t seem right, and those changes need to be made.”

At another point, he was asked about the Cambridge University Psychometrics Centre — which he said had initially been involved in discussions between him and SCL to be part of the project but fell out of the arrangement. According to his version of events the Centre had asked for £500,000 for their piece of proposed work, and specifically for modeling the data — which he said SCL didn’t want to pay. So SCL had asked him to take that work on too and remove the Centre from the negotiations.

As a result of that, Kogan said the Centre had complained about him to the university — and SCL had written a letter to it on his behalf defending his actions.

“The mistake the Psychometrics Centre made in the negotiation is that they believed that models are useful, rather than data,” he said. “And actually just not the same. Data’s far more valuable than models because if you have the data it’s very easy to build models — because models use just a few well understood statistical techniques to make them. I was able to go from not doing machine learning to knowing what I need to know in one week. That’s all it took.”

In another exchange during the session, Kogan denied he had been in contact with Facebook in 2014. Wylie previously told the committee he thought Kogan had run into problems with the rate at which the GSR App was able to pull data off Facebook’s platform — and had contacted engineers at the company at the time (though Wylie also caveated his evidence by saying he did not know whether what he’d been told was true).

“This never happened,” said Kogan, adding that there was no dialogue between him and Facebook at that time.  “I don’t know any engineers at Facebook.”

24 Apr 2018

Voyage open-sources autonomous driving safety practices

Voyage, the self-driving car spinout from Udacity, is open-sourcing its approach to autonomous driving safety. This comes at a time when autonomous driving programs are under intense scrutiny following two fatal crashes — one involving Tesla’s Autopilot and the other one involving one of Uber’s self-driving cars in Tempe, Arizona. Meanwhile, Voyage has already successfully deployed five Level 4 self-driving vehicles in retirement communities in California and Florida.

Dubbed Open Autonomous Safety, the initiative aims to help autonomous driving startups implement better safety testing practices. Companies looking to access the documents, safety procedures and test code can do so via a GitHub repository.

“Each and every autonomous vehicle startup today has to define their own safety programs, and we think that is dangerous,” Voyage CEO Oliver Cameron tweeted earlier today.

Version one includes scenario testing, functional safety, autonomy assessment and a testing toolkit. Later this year, OAS will release driver training material, additional scenarios and fault injection code and tests.

Here’s a quick breakdown of what the above currently entails:

  • Scenario testing: Looks at fundamental questions, like how self-driving cars behave around pedestrians and when cars back out of driveways.
  • Functional safety: Helps to ensure safety without a driver present.
  • Autonomy assessment: Validates whether or not car is moving in the right direction “and how we know that we are solving the right problems,” Cameron wrote in a blog post.
  • Testing toolkit: A library of traffic, roadway and vehicle assets.

“When it comes to safety, we believe open is better. At Voyage, we welcome contributions to improve OAS, like any other open source project,” Cameron wrote in a blog post. “The purpose of this effort is to promote an elevated standard of safety in the autonomous vehicle industry, increasing public trust through transparency.”

24 Apr 2018

Facebook shuts down custom feed sharing prompts and 12 other APIs

Facebook is making good on Mark Zuckerberg’s promise to prioritize user safety and data privacy over its developer platform. Today Facebook and Instagram announced a slew of API shut downs and changes designed to stop developers from being able to pull you or your friends data without express permission, drag in public content, or trick you into sharing. Some changes go into effect today, and others roll out on August 1st so developers have over 90 days to fix their apps. They follow the big changes announced two weeks ago

Most notably, app developers will have to start using the standardized Facebook sharing dialog to request the ability to publish to the News Feed on a user’s behalf. They’ll no longer be  able to use the publish_actions API that let them design a custom sharing prompt. A Facebook spokesperson says this change was planned for the future because the consistency helps users feel in control, but the company moved the deadline up to August 1st as part of today’s updates because it didn’t want to have to make multiple separate announcements of app-breaking changes.

 

Facebook app developers will now have to use this standard Facebook sharing prompt since the publish_action API for creating custom prompts is shutting down

One significant Instagram Graph API change is going into effect today, which removes the ability to pull the name and bio of users who leave comments on your content, though commenters’ usernames and comment text is still available.

Facebook’s willingness to put user safety over platform utility indicates a maturation of the company’s “Hacker Way” that played fast-and-loose with people’s data in order to attract developers to its platform who would in turn create functionality that soaked up more attention.

For more on Facebook’s API changes, check out our breakdown of the major updates: