The nature of the insurance industry is changing quickly, and much of that change is being attributed to big data and analytics. In fact, a Research and Markets report on the global insurtech market highlighted big data discovery and analytics as a key market trend that will drive a projected CAGR of 10.41 percent during the period 2016-2020.
The impact of big data on insurance makes sense. Insurance is based on the principle of risk. Customers take out policies based on their assessment of potential incidents, and insurance providers offer them coverage based on those assessments. With big data analytics, there is now a more accurate way to gauge these risks and gain insight into future events by measuring and understanding what has happened in the past.
Look at the automotive insurance market, for example. Traditionally, car insurance companies would price policies based on several variables, such as the age of the driver, gender, ZIP code and driving record. Today, even more variables are becoming available due to the ability to record, store and analyze data, transmitted through a plug-in device such as Progressive’s Snapshot® or from an app on the driver’s smartphone. More variables and data result in more accurate assessments of a driver’s likelihood to be involved in an accident or have their car stolen, resulting in more targeted premiums based on risk.
The Internet of Things (IoT) is also playing a role in the evolving health insurance landscape as the technology begins to become part of consumers’ lives. Insurtech firms have identified new devices to gather patient information with their permission, such as wearables and smartphone apps, which can provide new sources of data to better understand their healthcare needs and status. Big data solutions can then help insurance companies ensure better insights into patient behaviors, increase preventative measures, and reduce the cost of care while bolstering its effectiveness.
As we’ve seen in the financial and pharmaceutical industries, whenever there are huge volumes of data there are major opportunities to be found using the right technology tools. By leveraging data lakes and semantic graph technology, for instance, insurers can quickly extract and intuitively analyze data to find ways to enhance productivity and efficiencies. Many industry observers believe that big data analytics will eventually lead insurers to create new service products and features with a more precise understanding of their risk to protect profits and better serve their clients.
Cambridge Semantics’ Anzo Smart Data Lake® (ASDL) offers an end to end, fully integrated, highly customizable, and governed big data management and exploratory analytic solution for today’s data-driven insurance companies. ASDL works with any combination of diverse data far more quickly by deploying flexible graph models to deliver superior insights and actionable information.