Predictive Modeling for Equine Risk

Overview

The racehorse insurance industry sought to move beyond broad, community-based pricing by using a large standardized dataset of equine health and safety information.

The Challenge

Traditional underwriting approaches offered limited differentiation between individual horses. Critical information was also fragmented across veterinary, racing, registration, and operational systems, making predictive analysis difficult at scale.

The Solution & Benefits

Simatree integrated millions of records covering veterinary history, injuries, workouts, race performance, restrictions, trainer profiles, and track conditions. The team then developed predictive mortality models and risk-scoring methodologies to identify preferred risks and improve portfolio forecasting.

The work established a foundation for more precise pricing, improved underwriting decisions, and future actuarial analysis.

Measuring Success

Success is measured through improved risk differentiation, stronger portfolio forecasting, and closer alignment between premiums and measurable mortality indicators.

The Results

The solution is enabling a transition toward individualized horse-level underwriting while reducing adverse-selection risk and supporting future safety initiatives.