Data Is the New Oil. When’s the Last Time You Got Paid for Yours?

Elan Nyer spent his career on the supply side of automotive and insurance data before deciding the entire model was backwards.

He started in public policy, working with large datasets, then moved into automotive at Mobileye — his introduction to the industry, convincing insurers that early ADAS features like automatic emergency braking and lane-keep assist actually reduced crashes and deserved to affect pricing. From there he became the first business hire at Nexar, whose mission was to index the physical world visually the way Google indexes the web. Nexar’s insurance partnerships focused on first notice of loss: adding visual context to a claim so fault and injury likelihood were established immediately, keeping simple claims out of the hands of lawyers entirely.

Across both roles, he kept hitting the same wall. Every insurance buyer wanted more data than aggregate, anonymized sources could provide — and being locked into aggregate data was itself the problem, because two neighbors with identical cars and ZIP codes can have wildly different actual risk. One drives 5,000 miles a year, the other 30,000, and an insurer working from aggregate data prices them the same.

Ownli’s founding insight was to strip the problem to first principles: if the data is genuinely the individual’s, let companies buy it directly from them, with explicit consent and actual payment.

In Episode 128 of InsurTechTalk, Elan and I covered how the platform actually prices and verifies personal data, why insurers were more receptive than he expected, and the moment an insurance partner told him not to build another app.

About Elan Nyer

Elan Nyer is the co-founder and CEO of Ownli, a platform that lets individuals directly and transparently sell their own data to businesses — focused on the automotive and P&C insurance space. Before Ownli, Elan worked at Mobileye building insurer partnerships around ADAS technology, then was the first business hire at Nexar, working on visual claims data and first notice of loss. Ownli started at the tail end of 2020, spending its first year and a half in stealth working with regulators to validate the model before building the product. Investors include Verissimo Ventures, Circa Partners, and Groundup Ventures, along with angel investors including a Fiverr co-founder, former Yelp executives, and the former CEO of Edmunds.

How the Platform Actually Works

The mechanics matter here, because the pitch only works if the incentives are genuinely aligned on both sides.

• Insurers tell Ownli what data point they want, at what frequency, and what they will pay for it — mileage might be weekly or monthly, vehicle condition only at renewal
• Ownli surfaces the request to individuals at the right time, verifies the submission is legitimate and fraud-free, and confirms explicit consent before anything is shared
• Individuals see the payout before they agree, and can decline — the data only moves with clear, informed consent
• Payment is real cash value, redeemable as cash, Amazon gift cards, or dozens of other options — not points or fractions of a cent

Insurers set their own price, and it varies. A given data point might be worth $10 in Louisiana and $2 in Connecticut, entirely at the insurer’s discretion, based on what it is worth to their book in that market.

Elan’s framing of why this differs from the rest of the data economy: most personal data trades for effectively nothing per person — location data harvested by an app might be worth 0.002 cents a month. Ownli instead focuses on data alternative and stale enough elsewhere that a specific point can be worth real dollars, and treats people like adults rather than gamifying it with meaningless point systems.

Solving “Premium Leakage”

One of the sharper insights in the conversation was a problem neither of us had heard framed this way before: leakage that happens on the discount side rather than the claims side.

• Homeowners commonly get discounts for smoke detectors, alarm systems, and leak detectors — checked once, verified never
• Years later the device may be unplugged or disconnected entirely, while the policyholder still collects the discount
• Ownli’s platform enables a positive check-in instead: confirm the device is still active, and pay a small amount for the confirmation, rather than assuming the box checked years ago still reflects reality

We discussed this against Progressive’s Snapshot model as a point of comparison — a personalized rate that can also move upward based on driving conditions, including other drivers’ behavior nearby. The common thread is that most discount and pricing mechanics today are blunt instruments dressed up as personalization; Ownli’s pitch is closing that gap with continuously verified, individually priced data.

The Insurer Aha Moment: Stop Building More Apps

The unlock that actually got insurers to commit wasn’t about data at all — it was about app fatigue.

One partner had just invested heavily in their own app and admitted the only times customers opened it were to pay a bill or file a claim — both of which put the customer in a bad mood. There was no positive reason to engage otherwise.

Ownli’s answer was to stop asking insurers to add another app to the pile. Instead:

• Ownli exposes APIs and SDKs so its functionality — data capture, verification, payout — can be embedded directly inside an insurer’s existing app
• This unlocks recurring, positive engagement instead of twice-a-year touchpoints (renewal, and maybe a claim)
• The insurer keeps the customer relationship and the branding; Ownli provides the infrastructure underneath

That has become Elan’s standing recommendation to any insurer with an existing app: don’t ask customers to download something new — make the data marketplace part of what they already have open.

The Marketplace: Complementary, Never Competitive

Once insurers were engaged, other categories started asking to participate — and the boundary Ownli drew is instructive.

• An oil change company wanted to subscribe to mileage data instead of blindly mailing reminders every six months regardless of actual usage
• A dashcam company wanted first-party vehicle data to replace blind ad spend — knowing a car’s age and value lets them recommend a $30 single-camera unit versus a two-camera front-and-back system, and offer installation
• Tire chains wanted the same kind of targeted, usage-based outreach

The rule Elan enforces, at insurers’ explicit request: never expose or connect a policyholder to a competing insurer, and never connect a business partner (a tire shop, for instance) to their direct competitors. Complementary services that help maintain the insured asset are welcome; anything that erodes an existing relationship is not.

There’s a second-order benefit insurers are only starting to notice: people who proactively maintain their car — regular oil changes, tire rotations — represent a genuinely new, previously invisible risk signal. Insurers are now asking to specifically target and reach that population, which closes the loop from a pure data-selling exercise into an acquisition channel.

Where the Traditional Data Vendors Fit

I pushed on the obvious comparison: LexisNexis, TransUnion, and the broader industry of data aggregators that insurers already buy from, often without asking too many questions about provenance.

Elan’s view is not that Ownli replaces them, and insurers still have legitimate reasons to want prefill — nobody wants to click through 37 questions on a quote flow not knowing when it will end. The issue is that a meaningful share of that existing third-party data is stale or simply wrong. His practical suggestion: pull your own LexisNexis C.L.U.E. report and see how much of it is inaccurate or missing. Ownli’s data is different in kind because it originates directly from the individual it describes, with active consent, not aggregated or scraped from unclear sources.

What’s Next

Elan was candid about the founder’s constant tension between chasing every opportunity and staying focused.

• Today Ownli operates in personal auto and home P&C
• Health is the vertical he’s most excited about — eight years of EKG data sitting on a wrist is exactly the kind of alternative data health insurers would want
• Small commercial is another target — the long tail of laundromats, plumbing services, and similar businesses that behave more like personal lines than traditional commercial risk

Key Takeaways

• Aggregate, anonymized data hides real variance between individuals with identical demographic profiles — two neighbors, same car, wildly different actual risk
• Paying people directly and transparently for specific, meaningful data points beats the ambient, uncompensated data economy most people already distrust
• Insurers set their own price per data point and frequency, which lets the same platform serve wildly different state-by-state economics
• Discount programs leak premium quietly when the qualifying behavior (a connected device, a safety feature) stops holding after the initial discount is granted
• The highest-leverage integration is inside an app the insurer already has, not a new one — engagement problems get solved by embedding, not by asking for more downloads
• A data marketplace works when it strictly protects competitive boundaries: complementary partners are welcome, direct competitors are walled off
• Businesses adjacent to an insured asset (oil change, tire shops, dashcams) are increasingly interested in the same first-party data insurers already value