Insurance carriers must constantly strive to reduce losses and optimise pricing to sustain and grow the business. With the availability of diverse data sets and the development of tech stacks to derive personal and commercial risk profiles from this data, underwriters now have the tools to meet both these objectives.
The tech stacks include the insurer’s cloud-based core systems integrated with advanced artificial intelligence (AI) and machine learning (ML) models. These models can crunch both structured and unstructured data to give underwriters some combination of descriptive, predictive, and prescriptive analytics that help them better evaluate risk, accelerate the underwriting process, and deliver a low-friction underwriting experience to policy shoppers.
This blog highlights how an integrated predictive analytics model can help insurers to deliver underwriting excellence for different lines of business in different ways.
• Data replaces doubt.
• What a robust integrated predictive analytics model must offer small commercial underwriters.
• Data sources.
• Benefits of personalising the underwriting process.