Defining the rate for an insurance policy has been conventionally based on simple factors. For example, in auto insurance, the rate was determined by the manufacturing year and model of the vehicle, ignoring valuable individualized factors such as driving capacity and behavior, area of permanent residence, vehicle’s color, weather, or time of day, all of which critical factors on individual risk. By using traditional processes is difficult to evaluate individual rates for consumers because of the volume of data available.
Artificial Intelligence is ideal for anomaly detection, clustering, and creating recommendations, which makes it the perfect solution for finding the issues and developing more personalized insurance policies and rates. For example, AI can be used in automotive insurance to determine customer behaviors, such as hard breaking, that lead to more accidents, as well as to create granular clusters of customers based on behavior which can be used for segmentation. Using more personalized data to make the risk assessment results in an individualized picture of risk and the creation of personalized rates for consumers.