DataRobot can do claim frequency, severity, and pure premium (loss cost) modeling, helping to avoid being adversely selected against.
Problem / Pain
Many P&C insurance companies are seeing deteriorating underwriting results. With the advent of comparative raters in the P&C insurance market, prospects can price compare many companies instantly, often simply choosing the lowest price. Less sophisticated insurance carriers become exposed in the areas where they mispriced to make a sale. The lowest cost may win the business, but may be underpriced relative to the risk. This results in costing a company potentially exorbitant amounts of money in the end.
With DataRobot's wealth of algorithms, you can be confident in the prices you charge. By automating the process of building and comparing models that explore cost versus risk, you can determine whether any risk you consider taking on is priced appropriately. This competitive advantage pushes adverse selection on to competitors, which, over time will increase your growth and profitability.
Accuracy in pricing models can save an insurance company a significant amount of money. DataRobot automatically builds models from a wide class of algorithms—from Generalized Linear Models to Random Forests to Deep Learning—assuring that the final model is the best model.