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Tinder owner Match is suing Bumble over patents

17 March, by Katie Roof[ —]

Drama is heating up between the dating apps.

Tinder, which is owned by Match Group, is suing rival Bumble, alleging patent infringement and misuse of intellectual property.

The suit alleges that Bumble “copied Tinder’s world-changing, card-swipe-based, mutual opt-in premise.” The lawsuit also accuses Tinder-turned-Bumble employees Chris Gulczynski and Sarah Mick of copying elements of the design. “Bumble has released at least two features that its co-founders learned of and developed confidentially while at Tinder in violation of confidentiality agreements.”

It’s complicated because Bumble was founded by CEO Whitney Wolfe, who was also a co-founder at Tinder. She wound up suing Tinder for sexual harassment. 

Yet Match hasn’t let the history stop it from trying to buy hotter-than-hot Bumble anyway. As Axios’s Dan Primack pointed out, this lawsuit may actually try to force the hand for a deal. Bumble is majority-owned by Badoo, a dating company based in London and Moscow.

(It wouldn’t be the first time a dating site sued another and then bought it. JDate did this with JSwipe.)

Match provided the following statement:

Match Group has invested significant resources and creative expertise in the development of our industry-leading suite of products. We are committed to protecting the intellectual property and proprietary data that defines our business. Accordingly, we are prepared when necessary to enforce our patents and other intellectual property rights against any operator in the dating space who infringes upon those rights.

I have, um, tested out both Tinder and Bumble and they are similar. Both let you swipe on nearby users with limited information like photos, age, school and employer. And users can only chat if both opt-in.

However, Tinder has developed more of the reputation as a “hookup” app and Bumble doesn’t seem to have quite the same image, largely because it requires women to initiate the conversation, thus setting the tone.

As TechCrunch’s Sarah Perez pointed out recently, “according to App Annie, Tinder is more than 10x bigger in terms of monthly users and 7x bigger in terms of downloads in the last 12 months, versus Bumble.”

We’ve reached out to Bumble for comment.

Facebook suspends Cambridge Analytica, the data analysis firm that worked on the Trump campaign

17 March, by Jonathan Shieber[ —]

Facebook announced late Friday that it had suspended the account of Strategic Communication Laboratories, and its political data analytics firm Cambridge Analytica — which used Facebook data to target voters for President Donald Trump’s campaign in the 2016 election. In a statement released by Paul Grewal, the company’s vice president and deputy general counsel, Facebook explained that the suspension was the result of a violation of its platform policies. The company noted that the very unusual step of a public blog post explaining the decision to act against Cambridge Analytica was due to “the public prominence of this organization.”

Facebook claims that back in 2015 Cambridge Analytica obtained Facebook user information without approval from the social network through work the company did with a University of Cambridge psychology professor named Dr. Aleksandr Kogan. Kogan developed an app called “thisisyourdigitallife” that purported to offer a personality prediction in the form of “a research app used by psychologists.”

Apparently around 270,000 people downloaded the app, which used Facebook Login and granted Kogan access to users’ geographic information, content they had liked, and limited information about users’ friends. While Kogan’s method of obtaining personal information aligned with Facebook’s policies, “he did not subsequently abide by our rules,” Grewal stated in the Facebook post.

“By passing information on to a third party, including SCL/Cambridge Analytica and Christopher Wylie of Eunoia Technologies, he violated our platform policies. When we learned of this violation in 2015, we removed his app from Facebook and demanded certifications from Kogan and all parties he had given data to that the information had been destroyed. Cambridge Analytica, Kogan and Wylie all certified to us that they destroyed the data.”

Facebook said it first identified the violation in 2015 and took action — apparently without informing users of the violation. The company demanded that Kogan, Cambridge Analytica and Wylie certify that they had destroyed the information.

Over the past few days, Facebook said it received reports (from sources it would not identify) that not all of the data Cambridge Analytica, Kogan, and Wylie collected had been deleted. While Facebook investigates the matter further, the company said it had taken the step to suspend the Cambridge Analytica account as well as the accounts of Kogan and Wylie.

Depending on who you ask, UK-based Cambridge Analytica either played a pivotal role in the U.S. presidential election or cooked up an effective marketing myth to spin into future business. Last year, a handful of former Trump aides and Republican consultants dismissed the potency of Cambridge Analytica’s so-called secret sauce as “exaggerated” in a profile by the New York Times. A May 2017 profile in the Guardian that painted the Robert Mercer-funded data company as shadowy and all-powerful resulted in legal action on behalf of Cambridge Analytica. Last October, the Daily Beast reported that Cambridge Analytica’s chief executive Alexander Nix contacted Wikileaks’ Julian Assange with an offer to help disseminate Hillary Clinton’s controversial missing emails.

In an interview with TechCrunch late last year, Nix said that his company had detailed hundreds of thousands of profiles of Americans throughout 2014 and 2015 (the time when the company was working with Sen. Ted Cruz on his presidential campaign).

…We used psychographics all through the 2014 midterms. We used psychographics all through the Cruz and Carson primaries. But when we got to Trump’s campaign in June 2016, whenever it was, there it was there was five and a half months till the elections. We just didn’t have the time to rollout that survey. I mean, Christ, we had to build all the IT, all the infrastructure. There was nothing. There was 30 people on his campaign. Thirty. Even Walker it had 160 (it’s probably why he went bust). And he was the first to crash out. So as I’ve said to other of your [journalist] colleagues, clearly there’s psychographic data that’s baked-in to legacy models that we built before, because we’re not reinventing the wheel. [We’ve been] using models that are based on models, that are based on models, and we’ve been building these models for nearly four years. And all of those models had psychographics in them. But did we go out and rollout a long form quantitive psychographics survey specifically for Trump supporters? No. We just didn’t have time. We just couldn’t do that.

The key implication here is that data leveraged in the Trump campaign could have originated with Kogan before being shared to Cambridge Analytica in violation of Facebook policy. The other implication is that Cambridge Analytica may not have destroyed that data back in 2015.

The tools that Cambridge Analytica deployed have been at the heart of recent criticism of Facebook’s approach to handling advertising and promoted posts on the social media platform.

Nix credits the fact that advertising was ahead of most political messaging and that traditional political operatives hadn’t figured out that the tools used for creating ad campaigns could be so effective in the political arena.

“There’s no question that the marketing and advertising world is ahead of the political marketing the political communications world,” Nix told TechCrunch last year. “…There are some things which [are] best practice digital advertising, best practice communications which we’re taking from the commercial world and are bringing into politics.”

Responding to the allegations, Cambridge Analytica sent the following statement.

In 2014, SCL Elections contracted Dr. Kogan via his company Global Science Research (GSR) to undertake a large scale research project in the US. GSR was contractually committed to only obtain data in accordance with the UK Data Protection Act and to seek the informed consent of each respondent. GSR were also contractually the Data Controller (as per Section 1(1) of the Data Protection Act) for any collected data. The language in the SCL Elections contract with GSR is explicit on these points. GSR subsequently obtained Facebook data via an API provided by Facebook. When it subsequently became clear that the data had not been obtained by GSR in line with Facebook’s terms of service, SCL Elections deleted all data it had received from GSR. For the avoidance of doubt, no data from GSR was used in the work we did in the 2016 US presidential election.

Under Section 55 of the Data Protection Act (Unlawful obtaining etc. of personal data), a criminal offense has not been committed if a person has acted in the reasonable belief that he had in law the right to obtain data. GSR was a company led by a seemingly reputable academic at an internationally renowned institution who made explicit contractual commitments to us regarding the its legal authority to license data to SCL Elections. It would be entirely incorrect to attempt to claim that SCL Elections

illegally acquired Facebook data. Indeed SCL Elections worked with Facebook over this period to ensure that they were satisfied that SCL Elections had not knowingly breached any of Facebook’s Terms of Service and also provided a signed statement to confirm that all Facebook data and their derivatives had been deleted.

Cambridge Analytica and SCL Elections do not use or hold Facebook data.

VR startup Upload shuts down its offices as funding from Oculus founder Palmer Luckey runs out

17 March, by Lucas Matney[ —]

Upload, the VR startup which was rocked by a sexual harassment suit exactly one year ago, is shutting down both its San Francisco office and its 20,000 sq. foot Los Angeles co-working space as it struggles to secure new funding, multiple sources tell TechCrunch.

All of the company’s LA employees were laid off yesterday. The company’s SF office lease has already been taken over. The startup’s VR-focused trade publication, UploadVR, which operates independently of the company’s other ventures, has not been affected yet, sources tell us.

The layoffs and office shut downs come as the company has had trouble raising new funding and managing its reputation following a bombastic lawsuit from the company’s former social media manager that landed the startup on the front-page of the New York Times and on a CNN special feature talking about the company’s toxic workplace environment.

The sexual harassment and wrongful termination lawsuit, which we first reported, alleged — among other things — that the company had a “kink room” with a bed in its office where male employees had sex. As the company wrestled with the fallout, at least one additional former female employee was also threatening to sue the company’s leadership over sexual harassment claims, a source tells us.

In the aftermath of the lawsuit, the company brought on CircleClick CEO Anne Ward as COO to turn things around at the troubled startup. Ward left the company just six weeks later, and soon sent a cease and desist letter threatening a restraining order against Upload CEO Taylor Freeman and President Will Mason after what she alleged was “repeated harassment.”

Though the initial lawsuit was later settled out of court, the bad behavior didn’t end there for Upload. In a subsequent incident, an employee at the startup was reported to management for having sex with a client in the office. That employee was not fired and the person who reported them later quit, we are told.

Despite few of their company’s previous investors wanting to have anything to do with them, the co-founders have managed to keep things afloat thanks to personal investments from a close friend of theirs, Oculus founder Palmer Luckey.

“Nobody else will touch them but the Nazi sympathizer,” a former Upload executive told TechCrunch.

Multiple sources tell us that Luckey has personally invested as much as $2.5 million in Upload to keep the company running after it spent through the last of a $4.5 million Series A which it had raised in late 2016 from Colopl, General Catalyst and others. The Oculus founder, who left Facebook nearly one year ago following an extended controversy swirling around his personal politics, has maintained a close relationship with the company’s leadership but has been reluctant to invest further.

Luckey did not respond to a request for comment. We’ve reached out to Upload for comment.

Update: Upload has published a blog post responding to this article and confirming the office closures and layoffs.

Qualcomm’s former exec chair will exit after exploring an acquisition bid

17 March, by Matthew Lynley[ —]

There’s a new twist in the BroadQualm saga this afternoon as Qualcomm has said it won’t renominate Paul Jacobs, the former executive chairman of the company, after he notified the board that he decided to explore the possibility of making a proposal to acquire Qualcomm.

The last time we saw such a huge exploration to acquire a company was circa 2013, when Dell initiated a leveraged buyout to take the company private in a deal worth $24.4 billion. This would be of a dramatically larger scale, and there’s a report by the Financial Times that Jacobs approached Softbank as a potential partner in the buyout. Jacobs is the son of Irwin Jacobs, who founded Qualcomm, and rose to run the company as CEO from 2005 to 2014. Successfully completing a buyout of this scale would, as a result, end up keeping the company that his father founded in 1985 in the family.

“I am glad the board is willing to evaluate such a proposal, consistent with its fiduciary duties to shareholders,” Jacobs said in a statement. “It is unfortunate and disappointing they are attempting to remove me from the board at this time.”

All this comes following Broadcom’s decision to drop its plans to try to complete a hostile takeover of Qualcomm, which would consolidate two of the largest semiconductor companies in the world into a single unit. Qualcomm said the board of directors would instead consist of just 10 members.

“Following the withdrawal of Broadcom’s takeover proposal, Qualcomm is focused on executing its business plan and maximizing value for shareholders as an independent company,” the company said in a statement. “There can be no assurance that Dr. Jacobs can or will make a proposal, but, if he does, the Board will of course evaluate it consistent with its fiduciary duties to shareholders.”

Broadcom dropped its attempts after the Trump administration decided to block the deal altogether. The BroadQualm deal fell into purgatory following an investigation by the Committee on Foreign Investment in the United States, or CFIUS, and then eventually led to the administration putting a stop to the deal — and potentially any of that scale — while Broadcom was still based in Singapore. Broadcom had intended to move to the United States, but the timing was such that Qualcomm would end up avoiding Broadcom’s attempts at a hostile takeover.

BroadQualm has been filled with a number of twists and turns, coming to a chaotic head this week with the end of the deal. Qualcomm removed Jacobs from his role as executive chairman and installed an independent director, and then delayed the shareholder meeting that would give Broadcom an opportunity to pick up the votes to take over control of part of Qualcomm’s board of directors. The administration then handed down its judgment, and Qualcomm pushed up its shareholder meeting as a result to ten days following the decision.

“There are real opportunities to accelerate Qualcomm’s innovation success and strengthen its position in the global marketplace,” Jacobs said in the statement. “These opportunities are challenging as a standalone public company, and there are clear merits to exploring a path to take the company private in order to maximize the company’s long-term performance, deliver superior value to all stockholders, and bolster a critical contributor to American technology.”

It’s not clear if Jacobs would be able to piece together the partnerships necessary to complete a buyout of this scale. But it’s easy to read between the lines of Qualcomm’s statement — which, as always, has to say it will fulfill its fiduciary duty to its shareholders. The former CEO and executive chairman has quietly been a curious figure to this whole process, and it looks like the BroadQualm saga is nowhere near done.

Education quiz app Kahoot raises another $17M at a $100M valuation

16 March, by Ingrid Lunden[ —]

When we wrote about gaming startup Kahoot passing significant milestones of 70 million users on 51 million educational quizzes in January, we mentioned that the Oslo, Norway-based startup was closing another round of funding. Now, that has come to pass: Kahoot has announced that it has raised $17 million, at a valuation that sources close to the company confirm to us is $100 million.

The funding comes after a change in leadership and strategic direction for the company: its American CEO Erik Harrell has stepped away from the role while remaining on the board of the company, and has been replaced by Asmund Furuseth, one of the original co-founders, after Harrell and the board disagreed on the strategic direction for the company.

Harrell was keen to expand Kahoot’s business lines — in an interview with TechCrunch he described ambitions to partner with big media brands like Disney and educational publishers to create quizzes complementary to their textbooks and learning plans. The board, however, was more focused on getting the company to being cash-flow positive faster through paid tiers on the products they are already offering today, on the back of already establishing paying customers in 100 countries.

And that is what the company is doing. Led by Datum Invest AS, Northzone, Creandum, Microsoft Ventures and Kahoot! Chairman Eilert Hanoa, the company said it will be using this latest round of funding — which brings the total raised to $43 million — to further develop its premium subscription services with the aim to getting cash-flow positive by 2019. 

“We are thrilled to secure additional funding from new and existing investors, so that we can accelerate development of the Kahoot! platform and extend premium subscription services to all our users,” said Åsmund Furuseth, CEO of Kahoot, in a statement.

The company plans to continue to offer the basic Kahoot app free to students and teachers in the K-12 range, while generating income from a few areas. These include a premium tier that lets companies build and offer games to their users — a service that has already picked up business from Facebook, Uber and PwC, with companies using it for things like HR and sales training.

Kahoot has also described interest in developing sponsorships related to extra content for the K-12 sector. “There are corprorate sponsors we are in dialogue with now, many who want to support education, and sponsoring content on Kahoot is a great way to do that,” Harrell had said in January.

And there is also a subscription service for regular users. “We also believe in a subscription service. We have already found that there are many who are willing to pay subscribe, school districts that want to enable teachers and also parents,” Harrell said earlier this year. 

You can see why Kahoot may have decided to put the brakes on building too much, too fast: there have been a number of examples of gaming companies waxing and waning all too fast. Looking at another Nordic game sensation, Rovio, the company also found itself growing rapidly after finding wild success with Angry Birds. It used that boost to expand aggressively into a number of adjacent areas (it regularly described an ambition to become the next Disney). But when the popularity of Angry Birds waned, the bottom fell out of its bigger business. Even through a big restructuring and an IPO, the company has continued to search for a sustained return to significant growth.

That’s not to compare Kahoot to Rovio, but to give some context to why the former might be interested in pursuing a slightly more conservative path for the more immediate future.

Suspicious likes lead to researcher lighting up a 22,000-strong botnet on Twitter

16 March, by Devin Coldewey[ —]

Botnets are fascinating to me. Who creates them? What are they for? And why doesn’t someone delete them? The answers are probably less interesting than I hope, but in the meantime I like to cheer when large populations of bots are exposed. That’s what security outfit F-Secure’s Andy Patel did this week after having his curiosity piqued by a handful of strange likes on Twitter .

Curious about the origin of this little cluster of random likes, which he just happened to see roll in one after another, he noticed that the accounts in question all looked… pretty fake. Cute girl avatar, weird truncated bio (“Waiting you”; “You love it harshly”), and a shortened URL which, on inspection, led to “adult dating” sites.

So it was a couple bots designed to lure users to scammy sites. Simple enough. But after seeing that there were a few more of the same type of bot among the followers and likes of these accounts, Patel decided to go a little further down the rabbit hole.

He made a script to scan through the sketchy accounts and find ones with similarly suspicious traits. It did so for a couple days, and… behold!

This fabulous visualization shows the 22,000 accounts the script had scraped when Patel stopped it. Each of those little dots is an account, and they exhibit an interesting pattern. Here’s a close-up:

As you can see, they’re organized in a sort of hierarchical fashion, a hub-and-spoke design where they all follow one central node, which is itself connected to other central nodes.

I picked a few at random to check and they all turned out to be exactly as expected. Racy profile pic, random retweets, a couple strange original ones, and the obligatory come-hither bio link (“Do you like it gently? Come in! &&&”). Warning, they’re NSFW.

Patel continued his analysis and found that far from being some botnet-come-lately, some of these accounts — and by some I mean thousands and thousands! — are years old. A handful are about to hit a decade!

The most likely explanation is a slowly growing botnet owned and operated by a single entity that, in aggregate, drives enough traffic to justify itself — yet doesn’t attract enough attention to get rolled up.

But on that account I’m troubled. Why is it that a single savvy security guy can uncover a giant botnet with, essentially, the work of an afternoon, but Twitter has failed to detect it for going on ten years? Considering how obvious bot spam like this is, and how easily a tool or script can be made that walks the connections and finds near-identical spurious accounts, one wonders how hard Twitter can actually be looking.

That said, I don’t want to be ungenerous. It’s a hard problem, and the company is also dealing with the thousands and thousands (maybe millions) that get created every day. And technically bots aren’t against the terms of service, although at some point they probably tip over into nuisance territory. I suppose we should be happy that the problem isn’t any worse than it is.

Enterprise subscription services provider Zuora has filed for an IPO

16 March, by Matthew Lynley[ —]

Zuora, which helps businesses handle subscription billing and forecasting, filed for an initial public offering this afternoon following on the heels of Dropbox’s filing earlier this month.

Zuora’s IPO may signal that Dropbox going public, and seeing a price range that while under its previous valuation seems relatively reasonable, may open the door for coming enterprise initial public offerings. Cloud security company Zscaler also made its debut earlier this week, with the stock doubling once it began trading on the Nasdaq. Zuora will list on the New York Stock Exchange under the ticker “ZUO.” Zuora CEO Tien Tzuo told The Information in October last year that it expected to go public this year.

Zuora’s numbers show some revenue growth, with its subscriptions services continue to grow. But its losses are a bit all over the place. While the costs for its subscription revenues is trending up, the costs for its professional services are also increasing dramatically, going from $6.2 million in Q4 2016 to $15.6 million in Q4 2017. The company had nearly $50 million in overall revenue in the fourth quarter last year, up from $30 million in Q4 2016.

But, as we can see, Zuora’s “professional services” revenue is an increasing share of the pie. In Q1 2016, professional services only amounted to 22% of Zuora’s revenue, and it’s up to 31% in the fourth quarter last year. It also accounts for a bigger share of Zuora’s costs of revenue, but it’s an area that it appears to be investing more.

Zuora’s core business revolves around helping companies with subscription businesses — like, say, Dropbox — better track their metrics like recurring revenue and retention rates. Zuora is riding a wave of enterprise companies finding traction within smaller teams as a free product and then graduating them into a subscription product as more and more people get on board. Eventually those companies hope to have a formal relationship with the company at a CIO level, and Zuora would hopefully grow up along with them.

Snap effectively opened the so-called “IPO window” in March last year, but both high-profile consumer IPOs — Blue Apron and Snap — have had significant issues since going public. While both consumer companies, it did spark a wave of enterprise IPOs looking to get out the door like Okta, Cardlytics, SailPoint and Aquantia. There have been other consumer IPOs like Stitch Fix, but for many firms, enterprise IPOs serve as the kinds of consistent returns with predictable revenue growth as they eventually march toward an IPO.

The filing says it will raise up to $100 million, but you can usually ignore that as it’s a placeholder. Zuora last raised $115 million in 2015, and was PitchBook data pegged the valuation at around $740 million, according to the Silicon Valley Business Journal. Benchmark Capital and Shasta Ventures are two big investors in the company, with Benchmark still owning around 11.1% of the company and Shasta Ventures owning 6.5%. CEO Tien Tzuo owns 10.2% of the company.

Zscaler soars 106% on first day of trading

16 March, by Katie Roof[ —]

It was a big debut for enterprise cloud security company Zscaler, which saw its shares skyrocket 106% on its first day of trading. After pricing at $16, shares opened at $27.50, and closed at $34.

This was also well above the original expected price range for its IPO of $10 to $12. The company ultimately raised $192 million. In other words, there was significantly better-than-expected demand for Zscaler.

But not everyone likes a big pop. This means the company could have technically sold shares for more and raised more money.

Zscaler works with enterprises and says it counts 200 of the Forbes Global 2000 companies as customers. In an interview with TechCrunch, CEO Jay Chaudhry described the business as “the platform which was built in the cloud for the cloud.”

He went on to explain that his business was designed to help companies stay secure with a transient workforce. “We want to work from a hotel, airplane, coffee shop,” said Chaudhry. “The data center is no longer the center of the universe.”

But Zscaler is not yet profitable. For its fiscal 2015, revenue was $53.7 million, 2016 grew to $80.3 million and 2017 saw $125.7 million. Net losses were $12.8 million, $27.4 million and $35.5 million in 2015, 2016 and 2017, respectively.
Zscaler listed on the Nasdaq, under the ticker, “ZS.”

TechCrunch broke the news that Zscaler filed for IPO last fall.

In just the second venture-backed tech IPO of the year, eyes are on Zscaler, which raised $148 million in capital from Lightspeed Venture Partners and TPG ahead of its IPO.

This was the fifth company founded by Chaudhry. His other four were acquired. He said that TPG was instrumental and helping the company get to this point.

The next venture-backed tech debuts will be Dropbox and Spotify, which are expected to list in the coming weeks.

Tingles is an app devoted to ASMR videos

16 March, by Brian Heater[ —]

The Tingles team has not done much in the way of promotion, but the app has already built a fairly sizable following in its community. That’s one of the nice things about a targeted product — it spreads fast.

In the year since Slovenian co-founders Gasper Kolenc and Miha Mlakar launched, the service has focused almost exclusively on ASMR — autonomous sensory meridian response — those whispered, pleasant-sounding videos that give listeners a sense of low-level euphoria. The service is about to get a big push, with help from Y Combinator.

“We were just trying to figure the best way to build it for artists and the community,” Mlakar, who also serves as the company’s CPO, tells TechCrunch. “We established all of these relationships. All of the features came from the community. We needed time to work on the product.”

In spite of a lack of promotion, the company says it’s pulled in 60,000 monthly active users, bout a third of whom use the product every day. The site’s content is created by more than 200 “artists” (a term taken from the ASMR community’s almost-too-clever “ASMRtist”), many of whom were poached from YouTube.

Google’s video service has, of course, been ground zero for the rise of the ASMR online phenomenon. And while Mlakar admits that it’s proven a valuable resource for the community (it was where he first learned of the concept), the co-founder believes there were still issues unserved by YouTube’s catch-all approach to online video.

“I think YouTube is great for discovery,” says Mlakar. “I discovered ASMR on there. But when you become a regular user, it becomes a problem. The main thing is the ads. If you’re listening to ASMR to fall asleep and you’re just about to doze off, then a loud commercial wakes you up, it’s really unpleasant.”

The other benefits of offering such a hyper-focused service include a better monetization model for creators. The service is available ad-free for free, but the company is working with creators to develop exclusive premium content deals, along with other features like tipping. Creators are vetted through a short approval process, and Tingles does police the videos. But while the app — and most ASMR proponents — are quick to point out that the phenomenon itself isn’t a sexual one, there are indeed “more erotic channels,” according to Mlakar.

For Tingles, ASMR is just the beginning. Mlakar describes the Android/iOS app as “basically the best place to find any video content that helps you relax and fall asleep,” and future plans include a larger push into other relaxation categories, like meditation/mindfulness.

The Third Age of credit

https://wallethub.com/edu/average-credit-scores/25578/play episode download
16 March, by David Riggs[ —]

Society is beginning to wake up to a tremendous shift in one of the most fundamental underpinnings to how we live our lives: the credit system. Even though it’s not commonly known, credit infrastructure has existed about as long as civilization itself. In one way or another, credit systems have always formalized the one essential basis for relationships between people: trust.

Over millennia, the way credit looks, feels and is used has changed dramatically. Today, buoyed by a plethora of technologies and a golden age for abundant data, credit is undergoing its most radical change yet. But it is being pulled in many directions by competing forces, each with their own vision for the future.

In the beginning, credit was highly personal and subjective — this persisted for thousands of years. Over the last century, a miracle happened: Driven mostly by statistical modeling, credit became for the first time “objective.” Yet today, the cracks in that system are beginning to show, and we now stand on the brink of another revolution — the “Third Age” of credit.

We are on the verge of an exponential leap. The last year has witnessed a Cambrian explosion in credit innovation, unveiling hundreds of possibilities for the future of credit. Unlike the last two ages, credit of the future will be personal, predictive, self-correcting and universal.

The First Age: credit as trust

Modern anthropologists paint a picture of early agricultural society as a community of unsophisticated barterers, trading goods and services directly. In this picture, there is no room for a credit system: I trade you what I have and you want for what you have and I want. But, as historian David Graeber points out in his excellent etymology of credit, Debt: The First 5,000 Years, this account of early civilization is a myth.

The barter system has one major fault, known as the double coincidence of wants. If I am a chicken farmer, and I want to buy shoes from a cobbler, then my only hope is to find a cobbler who wants some of my chickens. If no cobbler in my town wants chickens, then I have to find out what the cobbler wants and begin bringing third parties into the transaction until all wants are fulfilled.

Today, we have a simple solution to this problem — money. Though it’s not conventionally viewed this way, money is actually a form of credit. The radical innovation of money was to introduce one third-party into every transaction: the government. When the farmer doesn’t have anything that the cobbler wants, he pays the cobbler in dollars; the dollars provide a deferred opportunity for the cobbler to then buy what she wants. All of this is possible because people trust that the value of a dollar will remain the same, and that trust comes from the fact that the government vouches for each dollar’s value. When you accept money as payment, you are giving the government credit for their claim that the money you accept can be redeemed for (about) the same value at a later date.

For the first 10,000 years or so, credit was useful… but imperfect.

People take this feature of money for granted, but even today, it’s not ubiquitous — take the example of the three-tier pricing phenomenon in Zimbabwe: The government released bond notes pegged 1:1 to the U.S. dollar, but shops accepted actual U.S. dollars at a premium to the notes (meaning a purchase would be less expensive in U.S. dollars than bond notes). This is the literal embodiment of Zimbabwe’s citizens not giving its government any credit. (Which also led to weird discrepancies in bitcoin prices in the country.)

Money is an amazing financial instrument for so many reasons. It is a medium of exchange. It is a store of value. It is highly divisible. It is fungible across many uses. It is universally coveted. It is liquid. But early societies didn’t have anything resembling modern money, so instead, they used credit. (See a timeline of payments over the course of civilization here.)

Credit has existed as long as human economies have. Some of the earliest writings discovered by archaeologists are debt records. (Historian John Lanchester profiles the history of credit excellently in When Bitcoin Grows Up.) But credit had a lot of issues: How do you give credit to a stranger or foreigner you don’t trust? Even for those you do trust, how do you guarantee they will pay you back? What is the right amount to charge on a loan?

Early debt systems often answered by formalizing rules such as debtors going into slavery or forfeiting their daughters. These conditions artificially constrained debt, meaning that, for most of human history, economies didn’t grow much, their size being capped by a lack of credit.

So, for the first 10,000 years or so, credit was useful… but imperfect.

The Second Age: credit as algorithm

This all changed in 1956. That year, an engineer and a statistician launched a small tech company from their San Francisco apartment. That company, named Fair, Isaac and Co. after its founders, came to be known as FICO.

As Mara Hvistendahl writes, “Before FICO, credit bureaus relied in part on gossip culled from people’s landlords, neighbors, and local grocers. Applicants’ race could be counted against them, as could messiness, poor morals, and ‘effeminate gestures.’ ” Lenders would employ rules such as, “prudence in large transactions with all Jews should be used,” according to Time. “Algorithmic scoring, Fair and Isaac argued, was a more equitable, scientific alternative to this unfair reality.”

It’s hard to overstate how revolutionary FICO really was. Before multivariate credit scoring, a banker couldn’t tell two neighbors apart when pricing a mortgage. The move to statistical underwriting — a movement that had roots as early as the 1800s in the U.S. — had a snowball effect, inspiring lookalike algorithmic credit systems around the world. Credit is all about risk, but until these systems developed in the mid-century, risk-based pricing was almost entirely absent.

Famously, Capital One founder Richard Fairbank launched IBS, his “information-based strategy.” As he noted, “First, the fact that everyone had the same price for credit cards in a risk-based business was strange. […] Secondly, credit cards were a profoundly rich information business because, with the information revolution, there was a huge amount of information that could be acquired about the customers externally.”

Today, algorithmic credit is ubiquitous. Between 90 percent and 95 percent of all financial institutions in the U.S. use FICO. In the last year alone, FICO released new credit scores in Russia, China and India using novel sources of data like utility bills and mobile phone payment records. Banks around the world now implement risk-based pricing for every kind of credit.

What does a new world of credit look like?

Thousands of startups are all finding new ways to apply this same concept of statistical modeling. WeLab in Hong Kong and Kreditech in Germany, for example, use up to 20,000 points of alternative data to process loans (WeLab has provided $28 billion in credit in four years). mPesa and Branch in Kenya provide developing-world credit using mobile data, Lendable does so using psychographic data and Kora does this on blockchain. Young peer-to-peer lending startups like Funding Circle, Lending Club and Lufax have originated more than $100 billion in loans using algorithmic underwriting.

Yet this global credit infrastructure is not without its significant drawbacks, as Americans found out on September 7, 2017, when the credit bureau Equifax announced a hack that exposed the data of 146 million U.S. consumers.

The fallout from the massive breach sparked conversations on credit, forced us to re-evaluate our current credit system and finally inspired the companies to look beyond the Second Age. White House cybersecurity czar Rob Joyce opined that the time has come to get rid of Social Security numbers, so intimately tied to credit scores, which can’t be changed even after identity theft.

Today, we are held hostage by our data. We become vulnerable by being forced to rely on insecure SSNs and PINs that can be stolen. We have no choice how that information is used (more than 100 billion FICO scores have been sold.)

FICO also doesn’t take into account relevant factors such as income or bills, and in some cases only reflects poor payment history and not on-time payments. And on top of that, 50 percent of a person’s score is dependent on their credit history — inherently biasing the system against the younger borrowers who should be leveraging credit the most.

Lastly, as Frank Pasquale writes in The Black Box Society, credit scoring is opaque. This creates disparate impacts on different groups. Algorithms accidentally incorporate human biases, making loans more expensive for minorities. Building credit often requires adherence to unknown rules, such as rewarding “piggybacking” off of others’ credit — a structure that perpetuates economic inequality.

Maybe the Equifax hack was a good thing. It was a jarring reminder that a credit system reliant on historical statistical modeling, opaque algorithms and insecure identifiers is still far from perfect. Were the hackers really Robin Hood in disguise, freeing us from our hostage-like dependence on an outdated scoring system?

The time has come to move beyond the weaknesses of the modern credit regime, and technology is today taking the first step.

The Third Age: credit as liberation

What does a new world of credit look like?

In the last year there has been a Cambrian explosion of new ideas to drive modern credit forward. It is too early to tell which system(s) will win out, but the early indications are truly mind-blowing. Credit is on the precipice of an exponential leap in innovation, which will reshape the world of financial inclusion. It will become more personal, predictive instead of reactive and instantaneous.

One of the most revolutionary aspects of the future of credit is that it will increasingly come to look like cash (and cash, conversely, like credit). Consumers won’t have to request credit; rather it will be automatically allocated to them in advance based off many factors, such as behavior, age, assets and needs. It will be liquid, rather than dispersed in fixed tranches. And as it becomes increasingly commoditized, in many cases it will be close to free.

Customers will have one form of payment for all purchases that automatically decides on the back-end what the best type of funding is, cash or credit, optimizing for efficiency and low fees. Imagine Venmo, credit cards, checks, PayPal and cash, all rolled into one payment method.

People will no longer have multiple credit lines, such as separate credit cards, student loans and mortgages. People will have a guaranteed “credit plan” available to them, all linked into one master identity or profile.

Physical instruments like dollar bills and plastic cards will be phased out and live only in museums. Biometric identifiers like fingerprints will be all you need to make a purchase. Prices will become infinitesimally divisible, optimized in some cases for fractional cent values. Denominations and different currencies will become background features.

In the future, people will be paid in real time (Walmart is experimenting with this now), instead of waiting for work credit every two weeks. Payday loans as an industry will evaporate. WISH Finance is building an Ethereum-based blockchain for cash flow-based underwriting. It’s easy to see this applied to consumers: get real-time credit based on your regular pay and expenses.

Naturally, talking about the future of credit, we have to talk about blockchains.

In the next phase, credit will revolve around the individual. Right now we live in a world of gatekeepers: Centralized data aggregators, such as credit bureaus, act as intermediaries to credit. This advantage will increasingly be eroded by individually permissioned data (a concept known as self-sovereign identity). This is consistent with trends in cross-border work and globalization: In an atomized world, the individual is the core unit and will need to take her information with her, without reliance on third parties. It could reduce some $15 billion in annual fees paid to access data and make information more secure, eliminating single points of failure.

One-size fits all scores like FICO will become disaggregated. Credit is a relational system: Our credit indicates our standing relative to a wide network. But people shouldn’t be represented by averages. Credit will become more multivariate, using machine learning and breaking apart the contributing factors and weights that make up FICO (the company where I work, Petal, is doing this to democratize credit cards).

It makes little sense to set single credit benchmarks — such as the 350 to 850 score range — irrespective of age, so consumers will be compared to their cohort. Per Experian, youngest people have the lowest credit scores. However, youth is when people should be borrowing the most, both to build credit and because they should be saving cash for their spending later in life.

Credit will become contextual. Your maximum available credit will fluctuate based on ever-changing factors such as payroll and bills. It also will be specific to purchases: You will receive different levels and costs of credit based on the value and type of the asset you’re buying. For instance, credit to buy a crib for your newborn may be cheaper than credit to buy a trip to Vegas. Illiquid assets will be automatically usable to secure credit, as Sweetbridge is doing. (The founders of Kora point out that the problem is not that the poor don’t have wealth, it’s that their capital is locked up.)

Credit will be psychographic and predictive. It won’t be enough to look backwards at your past behavior — your creditworthiness will change dynamically as you move around, make purchases and stay active. It will be dynamically assigned to specific needs (like ink if you buy a printer) before you realize you have them.

Naturally, talking about the future of credit, we have to talk about blockchains. They will have three early uses:

  • Funds dispersal: It will become much cheaper to disperse credit and accept payments using services like Stellar. There will be no latency from banks having to verify transactions against their own accounts.

  • Underwriting: Data will be aggregated into universal profiles (like those being built at uPort and Bloom) from a wide variety of sources, such as credit bureaus, phone bills, academic transcripts and Facebook. As mentioned, these will be self-sovereign, and make it much easier for credit providers to underwrite borrowers.

  • Contract enforcement: Smart contracts will be self-enforcing, automatically collecting debt payments, re-adjusting themselves if someone is credit crunched in the short term and refinancing if customers can consolidate or lower their APRs. The universal ID and contract will keep people from “running to Mexico” with their credit funds.

In the future, credit (and capital) will be automatically allocated to people based off predictive AI. Better risk pricing will continue to drop rates at which consumers can borrow, toward 0 percent. The federal funds rate has been around 1 percent for the last couple of years — in 1980 it was 18 percent! A combination of machine learning and what Bain calls “A world awash in money,” with larger investors hunting for lower returns, will continue to drive these rates down.

At a higher level, blockchain protocols like Dharma will set up smart contracts for the credit economy that allocate capital in the most efficient way. Credit will not rely on active investment managers to lend or borrow: Any capital not currently tied into a contract will be programmed to continuously search for the highest risk-adjusted return — including provision of credit.

Credit providers, at scale, will experience massive network effects. “Network effects” describe the condition in which networks become more valuable to users as more users participate. This doesn’t traditionally apply to credit: Just because other people have the same credit card as you, you don’t accrue any benefits. But in the future it will: More data points within credit networks will provide better underwriting, which will create fairer pricing, creating a virtuous cycle of data. User experiences and pricing will benefit tremendously as a result. Initiatives like the U.K.’s Open Banking will accelerate this trend.

Tom Noyes calls this The Democratization of Data. In a world of smaller, local data sets that collaborate (80-90 percent of all our current behavior is local), bridging disparate data gaps will increase credit participation to 100 percent (currently, only about 71 percent of Americans have credit cards).

And these are just some of the more probable, routine ideas. Futurists like Daniel Jeffries envision currencies with built-in features to incentivize different behaviors — like saving versus spending — and universal basic income tokens, to decentralize financial inclusion. Platforms like Bloom, which now has 100 applications being built on it, are reimagining credit at the protocol level. These systems are tackling first-principles questions, such as can the future be entirely meritocratic, or can people inherently create trust with no data.

We are living in the prologue to the Third Age. It’s hard to tell exactly how the future of credit will play out, but from where we stand, we can see that it will represent the biggest departure from the past in credit’s history, and we’re just today taking the first steps.

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