Driving $20M growth with AI-powered predictive models

To uncover the best opportunities, we first focused on discovery—working closely with two business units to explore AI applications across operations. 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 designed for real impact—applying AI and machine learning to claims, dealer onboarding, and segmentation. This thorough discovery process ensured the models would deliver measurable financial impact.

Collaboration was at the core of this AI initiative. Our multidisciplinary team of insurance experts, product designers, and data engineers worked side by side with the client. Using Azure and Databricks, we built and deployed three AI-powered models into existing systems. The onboarding model, for example, uses AI to score and prioritize dealers—avoiding $3 million in annual risk. Our integrated approach ensured each model not only delivered immediate value but could scale to address evolving business needs.

The three AI-infused 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. AI became a strategic tool for profit, not just prediction—positioning the client to compete smarter and scale faster.