Insurate’s Safe-Tier™ Index was developed around the theory that human underwriting alone lacks the ability to acquire and analyze sufficient levels of information to process high hazard policy quotes in a scalable fashion, while also maintaining underwriting discipline. Insurate was founded on the hypothesis that the same macro trend of greater and more granular data science and predictive modeling taking place in many consumer insurance segments should be applied in the evolution of work comp to augment current underwriting methodologies, particularly in industrial markets with premiums set by human beings based on the emotional perception of danger vs detailed information and statistical analysis.

STI scores are calculated through a proprietary data capture and analysis process. We start with the traditional insurance rating information which includes standard industry sources like a company’s experience mod and industry job codes. We then complement this information with data and AI that captures hundreds of additional data points to identify correlations and predictive indicators for work comp.

The result is an objective lens that sees correlations among hundreds of variables to provide a fair and transparent rating of future work comp claims exposure. While the details of Insurate’s rating algorithms and use of AI are confidential, many businesses are surprised to learn how influential novel factors may be in predicting future risk – items like stability of employee base, the availability of supplemental insurance, on-line sentiment, etc – the platform has identified important inter-related factors that have been proven to influence future work comp performance.