The evolution of data in the insurance industry

The insurance industry has always relied on historical data to assess potential risks. With the advent of digital technologies, the industry has a lot more touch points with the customer and processes that can be tapped into to gather a lot of data.

Along with historical data, the insurers also have access to a huge amount of real-time data. Both when paired can be used can give them a deeper understanding of risks as well as customer experience and expectations. The insurance industry is taking the help of these insights to personalize its products and services and take faster and more strategic decisions.

This data can be used to improve the consumer experience, be it by selecting new products or solving customer problems.

–   A chatbot fueled by Natural language processing and frequently asked questions can give the customers a more personal experience.

–   Customer queries can also be a good input for fine-tuning various insurance policies/products suggested to the prospective buyer

Marketing efforts are also fueled by data, to identify the prospects and customize the product as per their need.

–   Customer search data is analyzed to understand the buying patterns, identify potential customers, and design focused and personalized campaigns.

Data can also provide the ability to perform a risk assessment for the applications for a policy

– Traditionally, underwriters were relying on predefined guidelines, basic statistical models such as profiling and scoring models, and their intuitions for evaluating the risk of insurance policies. With the availability of predictive analytical models, underwriters can now make.

data-driven predictions about a customer’s risk profile with higher accuracy and apply these insights to premium pricing accordingly.

What is the most applicable use of historical and real-time data for your organization?