Within 6 months of implementation, this insurer writing an admitted line of business achieved a 14-point improvement in ultimate new business loss ratio, along with double-digit percentage reductions in claim frequency and property damage losses. By supplementing static underwriting rules with real-time, data-driven risk intelligence, the organization transformed how it evaluates and selects risk in a dynamic P&C market.

With a 14 pt loss ratio improvement, the insurer gained the flexibility and control to actively manage its book—empowering underwriting and pricing teams to make informed trade-offs, optimize risk selection, and dynamically calibrate toward their desired profitability targets.

Impact:

• Ultimate new business loss ratio improved by 14 points

• Total claim frequency decreased by 18%

• Property damage claims per earned exposure decreased by 29%

The Client: An Admitted Insurer

Founded in 2018, this insurer develops and administers custom insurance programs designed for distinct market opportunities. The organization focuses on niche and underserved segments that do not align well with traditional carriers’ broad market strategies, applying tailored approaches to better manage complex risks.

In this case, the insurer specializes in non-standard auto insurance. While often misunderstood, this segment does not necessarily consist of high-risk drivers. Many insureds have clean driving records but face barriers such as no prior insurance history, foreign identification, or limited credit history. Traditional insurers frequently exclude or overprice these drivers, creating a gap in the market. The insurer’s program is designed to serve individuals who need basic auto insurance but struggle to find affordable and accessible coverage.

The Challenge: Non-Standard, But Not Inadequately Rated

The insurer needed a more efficient way to select drivers in a highly dynamic non-standard auto segment. While existing underwriting methods had been successful, leadership believed there was room for improvement.

In late 2022, the team became aware of Soteris’ precise risk intelligence solution. Because the business depends on informed predictions in a rapidly evolving market, the insurer needed a way to accelerate growth with confidence, without introducing unexpected underwriting losses.

Auto insurance presents a critical challenge: the true cost of a risk is unknown at the point of sale. Balancing growth and profitability requires precision, adaptability, and continuous feedback.

Enter Soteris: A Collaborative Partner

After evaluating the solution, the insurer proceeded with a proof of concept in Q1 2023. The Soteris team worked closely with the insurer’s technology, product, and actuarial teams throughout the process. The proof of concept was delivered ahead of schedule, and based on its success, the insurer moved forward with a full implementation.

The solution was soft-launched in late summer 2023 and fully live shortly thereafter. The insurer described the experience as highly collaborative, noting that Soteris operated as an extension of the internal team—transparent, responsive, and receptive to feedback.

“Soteris was intriguing because our business is based on informed predictions. Auto insurance is an unusual business because the cost of goods sold for any individual risk isn’t known at the point of sale. Our objective in all our programs is to deliver a stable, competitive market for our partners.” – Insurer’s Chief Actuary 

How Soteris Designed An Implementation Plan Tailored For This Insurer’s Unique Needs:

• Before the first, second or both rate calls, the Soteris solution dynamically assigns a risk score to each incoming quote.

• This risk score is based on a custom algorithm derived from the company’s own historical loss data. It is calculated for each individual quote in under 250ms.

• The insurer sets their risk score threshold based on rate adequacy and applies it to expedite underwriting decisions. For instance, an insurer can allow straight-through processing for risks with scores of less than 70.

The Results: Faster Feedback, Greater Agility

Beyond improved risk selection, the insurer discovered an unexpected benefit: rapid feedback on pricing changes. Instead of waiting months to assess the impact of a rate adjustment, the team could see results within days.

Following a rate change, the percentage of inadequately rated opportunities dropped dramatically, immediately revealing where pricing gaps had been closed. This faster feedback loop allowed the insurer to adjust more quickly, increase risk appetite confidently, and remain agile in a competitive market.

Unlike traditional approaches that rely on third-party data purchased by many insurers, Soteris builds models using the insurer’s own historical loss data—creating a solution that is fully customized to each program.

The Results: Compelling Loss Ratio Impact

Within six months, the insurer realized the following business performance through its use of Soteris:

Loss Ratio Impact

• Ultimate new business loss ratio improved by 14 points 

• Total claims per earned car year in the first 90 days dropped by 10%

• Total claims features per earned car year over the full policy period dropped by 18%

• Property damage claims per earned exposure dropped by 29%

“We now have a tool that considers thousands of attributes and dynamically makes judgments on things we couldn’t even comprehend. It’s a dynamic, automatic scalpel. It’s game changing.” – Insurer’s Chief Actuary

By moving from static underwriting rules to dynamic, data-driven decisioning, the insurer transformed its approach to non-standard auto insurance. The organization was able to balance growth and profitability with greater confidence using a solution that adapts as quickly as the market itself.