Among other advantages, massive data management helps a core aspect of the industry: risk assessment.

The entire concept of the insurance business is based on risk assessment. Whether it is property and casualty insurance or any other type of life, home, or auto policy, the main task is to assume the potential relevant risks for each client and predict the likelihood that the policyholder will file a claim.

Given the type of industry, data collection and analysis are a fundamental pillar of this business. Basically, the more efficiently you can assess risks, the more accurately you can identify high-risk insured and set appropriate insurance premiums. In this context, the incorporation of Big Data only brings benefits.

Insurance organizations can also use this approach to make data-driven decisions that improve business-related outcomes. Benefits may include more effective marketing, new revenue opportunities, customer personalization, and operational efficiency in an industry that has long been managed by traditional standards.

According to data provided by Statistics and Studies Service of the Insurance Sector in Spain (ICEA), approximately two-thirds of insurers have already applied Big Data or are working on it. In this regard, the most common areas of use are “Customer Segmentation” (92.4%) and “Fraud Risk” (83.3%), but also “Process Efficiency” (74.2%) and “Product Redesign” (45.5%).

As a first point and as with many other industries, Big Data combined with other technologies allows for the automation of certain processes and smarter use of employee efforts, leading to cost reductions.

However, it is worth noting that there are some core aspects of the risk business where the strategic management of large volumes of information can bring fundamental transformation; for example, by examining trends in previous fraudulent cases and analyzing external trends, it is possible to identify fraud more efficiently than in the past.

Thanks to digital data sources such as social media or IoT devices, companies gain a deeper insight into customer characteristics and behavior that will increase or decrease statistical risks and determine the amount of the premium each one should pay. In this sense, the use of large amounts of information provides insurers with more detailed information, which can be used to distinguish more limited demographic groups and personalize offers.

Furthermore, in an industry where paper and errors derived from its management have always predominated, Big Data can help detect dependent and independent variables that help settle claims much more quickly and easily. Automation, in turn, speeds up internal processes and frees employees from manual and repetitive tasks.

On the other hand, there is also a customer experience that improves significantly, for example, by collecting information about customer behavior to detect early signs of dissatisfaction and resolve issues proactively.

There is no doubt about the competitive advantage of data in this industry: improved risk calculation helps avoid excessive risk exposure, which in turn allows insurers to reduce premium costs and provide more personalized service.

New approaches can also be conceived to encourage prudent behavior through Big Data and data intelligence, allowing the industry to transition from mere risk protection to a risk prediction and prevention industry.

By Julio Cesar Blanco – January 16, 2023