Driving $20M growth with predictive models

To uncover the best opportunities, we first focused on discovery—working closely with two business units to explore data-driven possibilities. Using value identification analytics, we tested several hypotheses with the client’s data and presented a strong business case for three high-impact predictive models. Each model was built with a focus on maximizing profitability and efficiency, ensuring the business could make smarter decisions around claims, dealer onboarding, and market targeting. This thorough discovery process ensured the models would deliver measurable financial impact.

Collaboration was at the core of this project. Our multidisciplinary team of insurance experts, product designers, and data engineers partnered closely with the client, using Azure and Databricks to implement the models. Together, we integrated solutions directly into their systems, ensuring ease of use and scalability. The new dealer onboarding model, for instance, will potentially add $3 million to annual EBITDA by helping onboard dealers more strategically. Our hands-on approach ensured the solutions would not only perform well today but adapt to future needs.

The three predictive models quickly showed their worth. A claims adjudication model improved decision-making for claims processing, reducing costs and adding an expected $7 million to annual EBITDA. The new dealer onboarding model helped avoid $3 million in annual risks. Meanwhile, the segmentation and underwriting model identified new revenue streams, adding $500,000 in profit and contributing to a $10 million revenue program. These results demonstrate how our co-created solutions directly contributed to the client’s bottom line, unlocking new avenues for growth and future success.