Jul
21
2021
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Ethos picks up $100M at a $2.7B+ valuation for a big data platform to improve life insurance accessibility

More than half of the U.S. population has stayed away from considering life insurance because they believe it’s probably too expensive, and the most common way to buy it today is in person. A startup that’s built a platform that aims to break down those conventions and democratize the process by making life insurance (and the benefits of it) more accessible is today announcing significant funding to fuel its rapidly growing business.

Ethos, which uses more than 300,000 data points online to determine a person’s eligibility for life insurance policies, which are offered as either term or whole life packages starting at $8/month, has picked up $100 million from a single investor, SoftBank Vision Fund 2. Peter Colis, Ethos’s CEO and co-founder, said that the funding brings the startup’s valuation to over $2.7 billion.

This is a quick jump for the company: It was only two months ago that Ethos picked up a $200 million equity round at a valuation of just over $2 billion.

It has now raised $400 million to date and has amassed a very illustrious group of backers. In addition to SoftBank they include General Catalyst, Sequoia Capital, Accel, GV, Jay-Z’s Roc Nation, Glade Brook Capital Partners, Will Smith and Robert Downey Jr.

This latest injection of funding — which will be used to hire more people and continue to expand its product set into adjacent areas of insurance like critical illness coverage — was unsolicited, Colis said, but comes on the heels of very rapid growth.

Ethos — which is sold currently only in the U.S. across 49 states — has seen both revenues and user numbers grow by over 500% compared to a year ago, and it’s on track to issue some $20 billion in life insurance coverage this year. And it is approaching $100 million in annualized growth profit. Ethos itself is not yet profitable, Colis said.

There are a couple of trends going on that speak to a wide opportunity for Ethos at the moment.

The first of these is the current market climate: Globally we are still battling the COVID-19 global health pandemic, and one impact of that — in particular given how COVID-19 has not spared any age group or demographic — has been more awareness of our mortality. That inevitably leads at least some part of the population to considering something like life insurance coverage that might not have thought about it previously.

However, Colis is a little skeptical on the lasting impact of that particular trend. “We saw an initial surge of demand in the COVID period, but then it regressed back to normal,” he said in an interview. Those who were more inclined to think about life insurance around COVID-19 might have come around to considering it regardless: It was being driven, he said, by those with pre-existing health conditions going into the pandemic.

That, interestingly, brings up the second trend, which goes beyond our present circumstances, and Colis believes will have the more lasting impact.

While there have been a number of startups, and even incumbent providers, looking to rethink other areas of insurance such as car, health and property coverage, life insurance has been relatively untouched, especially in some markets like the U.S. Traditionally, someone taking out life insurance goes through a long vetting process, which is not all carried out online and can involve medical examinations and more, and yes, it can be expensive: The stereotype you might best know is that only wealthier people take out life insurance policies.

Much like companies in fintech that have rethought how loan applications (and payback terms) can be rethought and evaluated afresh using big data — pulling in a new range of information to form a picture of the applicant and the likelihood of default or not — Ethos is among the companies that is applying that same concept to a different problem. The end result is a much faster turnaround for applications, a considerably cheaper and more flexible offer (term life insurance lasts only as long as a person pays for it), and generally a lot more accessibility for everyone potentially interested. That pool of data is growing all the time.

“Every month, we get more intelligent,” said Colis.

There is also the matter of what Ethos is actually selling. The company itself is not an insurance provider but an “insuretech” — similar to how neobanks use APIs to integrate banking services that have been built by others, which they then wrap with their own customer service, personalization and more — Ethos integrates with third-party insurance underwriters, providing customer service, more efficient onboarding (no in-person medical exams for example) and personalization (both in packages and pricing) around them. Given how staid and hard it is to get more traditional policies, it’s essentially meant completely open water for Ethos in terms of finding and securing new customers.

Ethos’s rise comes at a time when we are seeing other startups approaching and rethinking life insurance also in the U.S. and further afield. Last week, YuLife in the U.K. raised a big round to further build out its own take on life insurance, which is to sell policies that are linked to an individual’s own health and wellness practices — the idea being that this will make you happier and give more reason to pay for a policy that otherwise feels like some dormant investment; but also that it could help you live longer (Sproutt is another also looking at how to emphasize the “life” aspect of life insurance). Others like  DeadHappy and BIMA are, like Ethos, rethinking accessibility of life insurance for a wider set of demographics.

There are some signs that Ethos is catching on with its mission to expand that pool, not just grow business among the kind of users who might have already been considering and would have taken out life insurance policies. The startup said that more than 40% of its new policy holders in the first half of 2021 had incomes of $60,000 or less, and nearly 40% of new policy holders were under the age of 40. The professions of those customers also speak to that democratization: The top five occupations, it said, were homemaker, insurance agent, business owner, teacher and registered nurse.

That traction is likely one reason why SoftBank came knocking.

“Ethos is leveraging data and its vertically integrated tech stack to fundamentally transform life insurance in the U.S.,” said Munish Varma, managing partner at SoftBank Investment Advisers, in a statement. “Through a fast and user-friendly online application process, the company can accurately underwrite and insure a broad segment of customers quickly. We are excited to partner with Peter Colis and the exceptional team at Ethos.”

Apr
13
2021
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SambaNova raises $676M at a $5.1B valuation to double down on cloud-based AI software for enterprises

Artificial intelligence technology holds a huge amount of promise for enterprises — as a tool to process and understand their data more efficiently; as a way to leapfrog into new kinds of services and products; and as a critical stepping stone into whatever the future might hold for their businesses. But the problem for many enterprises is that they are not tech businesses at their core, so bringing on and using AI will typically involve a lot of heavy lifting. Today, one of the startups building AI services is announcing a big round of funding to help bridge that gap.

SambaNova — a startup building AI hardware and integrated systems that run on it that only officially came out of three years in stealth last December — is announcing a huge round of funding today to take its business out into the world. The company has closed on $676 million in financing, a Series D that co-founder and CEO Rodrigo Liang has confirmed values the company at $5.1 billion.

The round is being led by SoftBank, which is making the investment via Vision Fund 2. Temasek and the government of Singapore Investment Corp. (GIC), both new investors, are also participating, along with previous backers BlackRock, Intel Capital, GV (formerly Google Ventures), Walden International and WRVI, among other unnamed investors. (Sidenote: BlackRock and Temasek separately kicked off an investment partnership yesterday, although it’s not clear if this falls into that remit.)

Co-founded by two Stanford professors, Kunle Olukotun and Chris Ré, and Liang, who had been an engineering executive at Oracle, SambaNova has been around since 2017 and has raised more than $1 billion to date — both to build out its AI-focused hardware, which it calls DataScale, and to build out the system that runs on it. (The “Samba” in the name is a reference to Liang’s Brazilian heritage, he said, but also the Latino music and dance that speaks of constant movement and shifting, not unlike the journey AI data regularly needs to take that makes it too complicated and too intensive to run on more traditional systems.)

SambaNova on one level competes for enterprise business against companies like Nvidia, Cerebras Systems and Graphcore — another startup in the space which earlier this year also raised a significant round. However, SambaNova has also taken a slightly different approach to the AI challenge.

In December, the startup launched Dataflow-as-a-Service as an on-demand, subscription-based way for enterprises to tap into SambaNova’s AI system, with the focus just on the applications that run on it, without needing to focus on maintaining those systems themselves. It’s the latter that SambaNova will be focusing on selling and delivering with this latest tranche of funding, Liang said.

SambaNova’s opportunity, Liang believes, lies in selling software-based AI systems to enterprises that are keen to adopt more AI into their business, but might lack the talent and other resources to do so if it requires running and maintaining large systems.

“The market right now has a lot of interest in AI. They are finding they have to transition to this way of competing, and it’s no longer acceptable not to be considering it,” said Liang in an interview.

The problem, he said, is that most AI companies “want to talk chips,” yet many would-be customers will lack the teams and appetite to essentially become technology companies to run those services. “Rather than you coming in and thinking about how to hire scientists and hire and then deploy an AI service, you can now subscribe, and bring in that technology overnight. We’re very proud that our technology is pushing the envelope on cases in the industry.”

To be clear, a company will still need data scientists, just not the same number, and specifically not the same number dedicating their time to maintaining systems, updating code and other more incremental work that comes managing an end-to-end process.

SambaNova has not disclosed many customers so far in the work that it has done — the two reference names it provided to me are both research labs, the Argonne National Laboratory and the Lawrence Livermore National Laboratory — but Liang noted some typical use cases.

One was in imaging, such as in the healthcare industry, where the company’s technology is being used to help train systems based on high-resolution imagery, along with other healthcare-related work. The coincidentally-named Corona supercomputer at the Livermore Lab (it was named after the 2014 lunar eclipse, not the dark cloud of a pandemic that we’re currently living through) is using SambaNova’s technology to help run calculations related to some COVID-19 therapeutic and antiviral compound research, Marshall Choy, the company’s VP of product, told me.

Another set of applications involves building systems around custom language models, for example in specific industries like finance, to process data quicker. And a third is in recommendation algorithms, something that appears in most digital services and frankly could always do to work a little better than it does today. I’m guessing that in the coming months it will release more information about where and who is using its technology.

Liang also would not comment on whether Google and Intel were specifically tapping SambaNova as a partner in their own AI services, but he didn’t rule out the prospect of partnering to go to market. Indeed, both have strong enterprise businesses that span well beyond technology companies, and so working with a third party that is helping to make even their own AI cores more accessible could be an interesting prospect, and SambaNova’s DataScale (and the Dataflow-as-a-Service system) both work using input from frameworks like PyTorch and TensorFlow, so there is a level of integration already there.

“We’re quite comfortable in collaborating with others in this space,” Liang said. “We think the market will be large and will start segmenting. The opportunity for us is in being able to take hold of some of the hardest problems in a much simpler way on their behalf. That is a very valuable proposition.”

The promise of creating a more accessible AI for businesses is one that has eluded quite a few companies to date, so the prospect of finally cracking that nut is one that appeals to investors.

“SambaNova has created a leading systems architecture that is flexible, efficient and scalable. This provides a holistic software and hardware solution for customers and alleviates the additional complexity driven by single technology component solutions,” said Deep Nishar, senior managing partner at SoftBank Investment Advisers, in a statement. “We are excited to partner with Rodrigo and the SambaNova team to support their mission of bringing advanced AI solutions to organizations globally.”

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