Take for instance auto insurance, which in some jurisdictions is beginning to use telematics data and analytics to discount policies based on improved driving behaviour. Generated from advanced sensors and GPS-based satellites, details like driving patterns and traffic congestion are transmitted directly to the insurance company. Traditionally, carriers would have created risk models and set premiums based on information from specific group behaviour; like age, driving experience and geographic location. Now, data on existing driving patterns can be collected in real-time and utilized to provide the best premium solution for a driver’s unique needs.
A natural extension of big data and analytics is cognitive computing. Cognitive computing applications can formulate thousands of possible outcomes based on precise data and unique risks for each customer. Currently revolutionizing healthcare, cognitive computing systems can help insurers and brokers evaluate substantial amounts of unstructured data, such as risk assessment, underwriting, loss mitigation and claims management. These systems have the capacity and intelligence to approach each case, formulate hypotheses, test for the best hypotheses and apply reason and judgment to evaluate risks for each customer rather than align risk to a defined product, making for a truly personalized, customer-centric model.
With this information, insurers and brokers can determine the next best action in customer relationships; improve claims operations and fraud detection; perform near-real-time catastrophe risk modeling; gain enterprise insight for actionable decision making; enhance producer effectiveness, and transform contact-center operations.
How to get started
It’s a new era for insurance companies. An industry that was once focused on marketing to a group of many is now integrating customer insights based on big data and analytic technologies to offer a more specific, comprehensive service for an individual.
To successfully compete in this environment, insurers and brokers should acquire the necessary skills to understand real analytic outcomes based on insights that assist customers and provide analytics-driven business outcomes. Enhanced insight will build a smarter insurance industry, where personnel can attract customers rather than selling to them and optimize the business with insight rather than managing it with instinct.