How Cachet Helped RW Rent Control Costs With Usage-Based Insurance

RW Rent is a fast-growing automotive platform supporting professional taxi and ride-hailing drivers. As demand for ride hailing increased, so did their fleet. But with expansion came a growing line item: insurance.

“The market is getting more competitive every year,” said Tauno Liiv, Owner and Manager of RW Rent. “We needed an insurance model that could adapt around our fleet.”

Standard fleet insurance treats every vehicle as equally risky. That logic made sense when insurers had no access to real-time data. But today, usage data presents opportunities to price better.

Traditional insurance prices every vehicle the same, regardless of how it was used. For RW Rent, that meant full-time premiums for part-time exposure. 

RW Rent’s vehicles vary in use. Some are out daily, others weekly. Drivers range from seasoned professionals to newer operators. 

Under a flat policy, none of that mattered. Every vehicle carried the same premium, regardless of usage, downtime, or behaviour. 

“We were being charged based on assumptions, not data,” Liiv added. 

For an automotive fleet in growth mode, this lack of control over costs creates a lot of pressure. Insurance ranks second only to fuel as the biggest costs of automotive fleets. RW Rent needed insurance that was fair, responsive, and reliable.

Cachet delivered a scoring-based pricing model for RW Rent better rewarded safe driving with fair rates over the long run. 

In the background the Cachet Score analyses real-world indicators: driver patterns, operating hours, incident history, and vehicle downtime. It translates this into a single, transparent risk profile that underwriters can get behind. The end result is a better premium logic that passes back savings to RW Rent via fairer rates for cars within their fleet.

The Score also opened up a clearer line of trust with the insurer. No longer a black box, the fleet’s performance was visible and verifiable. That alignment gave RW Rent something they’d never had with insurance before: stability.

Cachet’s model didn’t just lower premiums. It replaced volatility with structure, and guesswork with logic.

Since adopting the Cachet Score, RW Rent has gained a more stable, transparent insurance model that flexes with their fleet’s performance. Pricing now reflects their unit economics and how their fleet actually performs. Generic averages are gone as insurers better understand the risk and reward of a platform business like theirs. 

The result is better premiums, easier planning and reduced time spent managing insurance questions. The shift to score based pricing has changed their relationship with insurance for the better. RW Rent can approach renewals and operational decisions with greater confidence in the stability of their cost base.