Personalized Rate Management
Customizing Rates based on Individual Data using AI
Determining the rate for an insurance policy has traditionally been driven by simple factors. For example, in auto insurance, the rate was determined by the year, make and model of the vehicle. This method does not consider individualized factors such as driving behavior, location, weather, or time of day, all of which could have a significant impact on individual risk. Assessing individual rates for consumers is difficult using traditional processes because of the volume of data available. Segmenting customers can be helpful, but even these macro groups miss the opportunity presented by the large volumes of data being collected at the individual level.
AI is ideal for anomaly detection, clustering, and creating recommendations, which makes it ideal for finding the issues and developing more individualized insurance policies and rates. For automotive insurance, for example, AI can be used to determine the customer behaviors, such as hard breaking, that lead to more accidents. AI can be used to create granular clusters of customers based on behavior which can be used for segmentation. AI can also be used to evaluate a variety of factors when assessing risk of a serious accident based on the location where most of the driving takes place, city versus highway, daytime or nighttime driving, and other factors. Using more personalized data to make the risk assessment results in an individualized picture of risk and the creation of personalized rates for consumers.
The mission at H2O.ai is to democratize AI for all so that more people across industries can use the power of AI to solve business and social challenges. The insurance industry is a key focus for the company with leading insurance companies including Progressive, TransAmerica, Aegon, Zurich Insurance helping to drive significant product innovation. H2O Driverless AI is an award-winning platform for automatic machine learning that empowers data science teams to scale by dramatically increasing the speed to develop highly accurate predictive models. Driverless AI includes innovative features of particular interest to insurance companies including machine learning interpretability (MLI), reason codes for individual predictions, and automatic time series modeling.
Related Case Studies
The ability to do advanced analytics and do more work across the data is going to be the differentiator for insurance companies going forward.”
Conner Jensen, Analytics Program Director, Zurich Insurance