Automated Underwriting

In automated underwriting, the risk perspective of the system and the classification models of the client profiles are so crucial to determine the right assessment and approval path of the related issue. If the model construction of the system doesn’t cover all the issues, there will always be misevaluated cases. Keeping the model always up-to-date is another challenge.

The model of the product should be designed by considering as many variables as possible and feeding with substantial issue data to be updated and aware of most of the possibilities. False-positive or false-negative cases shouldn’t be ranged as exceptions.

Aigoritma improves claims automation by using machine learning models as a fast and accurate solution to help insurance companies. Clients can submit the claim online through the claim automation services by filling in the information about the cause of the loss. This automation can provide accurate optimization with a fast, fair and satisfactory customer experience.