Insurance agencies must deal with reams and reams of documents and sometimes fairly complex numerical models to maximize coverage while targeting the best pricing. With Machine learning, agencies can aim for an optimized yield and faster operations.
Using Interplay’s regression analysis model, commercial insurers can apply insights to their pricing and otherwise complex risk management models. Interplay can run regression machine learning and AI predictive models to data sets in order to evaluate and predict potential risks of each applicant, including risk of cancellation and fraud, before ever issuing a policy to them, protecting the carrier as much as possible. These applications can run predictive models based on data fields such as transaction history, location, and product mix.
Interplay has easy connections to legacy database applications and large enterprise customer database systems such as Oracle, Postgres, SAP, and any legacy system with an API exposed. Integration can also port the predictive results out to common RPA office applications, communications systems, or even back into the legacy databases according to the available database schema. Interplay can be deployed in edge servers within offices, data centers, or in secure cloud environments.