Thursday, December 20, 2018

Fair.com gets $385M led by Softbank to grow its flexible car ownership model globally

California startup Fair.com is aiming to turn the car market on its head by providing price-friendly, easy options for people to lease vehicles instead of buying them, and today it’s taking the latest, big step in that ambition.

It has raised a huge Series B funding round of $385 million led by Softbank, with participation from Exponential Ventures, Munich Re Venture’s ERGO Fund, G Squared, and CreditEase, to take its business global. Requiring just a drivers license and a credit card (or bank details), Fair provides flexible leasing plans both to everyday users, and to people who use cars for work purposes. In the last year, it has worked closely with Uber, which sold Fair its $400 million leasing business earlier this year, to equip its drivers with vehicles, and that will be a pattern it hopes to repeat with other ride-sharing providers in other markets.

“The plan is to scale the business ten-fold,” CEO and co-founder Scott Painter said in an interview. Fair is already in 15 states (26 markets) in the US and is adding a new city every week, he continued, leasing cars to more than 20,000 users to date. “Growth has been dramatic over the last year.”

This is the latest in a series of outsized investments Softbank has made across the tech world out of its Vision Fund, and it is a very strategic one.

Softbank is already one of the biggest investors in the world in ride-sharing businesses, backing not just Uber but Didi in China, Grab in Southeast Asia, Ola in India, Getaround in the US. (It’s also involved in a number of other automotive and transportation plays such as the food delivery startup Doordash, the car dealer platform Auto1 in Germany, the self-driving company Cruise, mapping startup Mapbox, and many more.)

One long-term plan is to use Fair to help scale those ridesharing businesses by helping connect more drivers with vehicles, as Fair has already done with Uber, by providing a quick way for would-be drivers to get vehicles.

“We think Fair could help unlock ridesharing on a global scale,” said Lydia Jett, an investor with the Softbank Vision Fund. “We’re excited to see how this can add to Softbank’s portfolio and vice versa.”

Painter said Fair had been talking to Softbank for the last year leading up to today. One of the reasons Softbank decided to invest was because of Fair’s ability to turn around Uber’s leasing business.

“Uber became a case to prove out the team,” Jett said. “As an investor, you rarely get to see a singular asset operated by two different teams, and the Fair team was about to do something that Uber was not doing well. They have turned that asset around and proven that this is a tremendous value add.”

Painter would not comment directly on his company’s valuation, but he pointed out that this round puts the total raised in equity so far in Fair.com at around $500 million. And from what I understand, Fair’s valuation is now definitely over $1 billion as collectively those equity investors do not control the business.

Alongside the equity investments, Fair has up to now been able to secure up to $1 billion in debt, used to build up its fleet of vehicles. Painter noted to me that this latest equity round will help it grow that debt pot as and when it’s needed to meet demand. “In simple terms, for every dollar in equity we unlock $10 in debt, and we borrow that cash to buy cars.”

Painter said that while the equity funding will mainly be used to scale the business into more markets — and not just to ridesharing, but “anyone working in the gig economy” — there will continue to be some investments made into the company’s tech platform.

That platform has something in common with other financial services that have sprouted up over the years: using big data analytics and intelligent algorithms, Fair’s aim is to improve the process of converting a merely interested consumer into bona-fide transaction by reducing as much friction in the process as possible.

In its case, it requires just two pieces of documentation from would-be leasers of its new or (more commonly) nearly-new vehicles: proof of a driver’s license, and either a credit card or bank account details. From that, Fair is able to build up a financial profile of the user in the backend, to determine quickly whether the person is eligible to rent. (That in itself is a sizeable achievement: leasing or buying a car can be a very time-consuming process, which will put off a lot of people from doing it very often, if at all.)

At the car end, Fair is also crunching numbers, figuring out which cars are in demand and negotiating deals to buy those in. Working with dealers — it has some 3,000 on its books already — it then works out pricing and an essentially guaranteed funnel of business to get those vehicles.

No aspect of the business’ data funnel goes to waste, it seems.

“We have almost two million app installs, a remarkable base of people looking for a used car,” Panter said. “Through that, we can get so much information about you and shopping behavior, and that can let us focus on which cars and products are a good fit. It’s a data-driven, deep learning exercise.”

Painter’s business is predicated on a vision of an automotive marketplace where no one owns cars anymore but just leases them, and conveniently, this fits with how many others believe the automotive industry is already evolving.

The thinking goes like this: as cars become more sophisticated, they also become more costly, and so it’s getting less likely that people will be able to afford these, or want to drive these themselves (indeed, that is a future that carmakers have already been preparing for).

People will either opt to use car services, or if they want to continue driving themselves, they will no longer own these cars. Combing that trend with the wider economic swing we’ve seen to on-demand services, you can see how the concept of an efficient, price-competitive leasing model might persuade people to give that a try.



from TechCrunch https://ift.tt/2QHd94f

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