Large-scale data collection is nothing new for the risk management and insurance industry. After all, insurers have been collecting vast amounts of data about policyholders for a long time. The industry has traditionally gathered a variety of data, including personal information, loss data, credit score and much more in order to understand and price risk.
However, in recent years, the sheer amount and variety of useful data available have increased dramatically, largely because of advances in technology and smart products that allow for much broader data collection. These huge sets of data, which are too large to be gathered and analyzed by traditional methods, are generally referred to as big data.
In addition, recent advances in sophisticated analytical techniques are enabling insurers to use this data to glean useful information about risk that was not previously available. The combination of big data, new technologies and advanced analytics is revolutionizing our industrys operations, affecting everything from underwriting and claims to customer acquisition and new product development.
The Internet of Things (IOT) has spurred a revolution in terms of the volume and kinds of data that are now available to insurers. The IOT allows for real-time monitoring and capture of data pertaining to risk. It is facilitated by devices (cameras, sensors, drones and so on) that are always collecting data and transmitting it to a data center for analysis. Examples are telematics devices for cars, connected thermostats for buildings and wireless sensor networks for supply chains.
To analyze data you collect, you must first have it stored in an accessible way. Blockchain can accomplish the storage phase in a trusted and common way and can also allow for action to be taken using a predetermined set of rules based on threshold triggers in the data. This is revolutionary for our industry. It has the potential to change our conceptions of cost and time, significantly influencing various parts of the insurance value chain.
Capitalizing on the vast amounts of data now at hand, recent advances in analytical techniques can help insurers gain deep insight into data patterns and trends. Crucial to the successful execution of many complex analytical techniques is the enhanced capability offered by advances in computer technologyspecifically, machine learning. The combination of this technology and big data analytics can be used to construct automated underwriting systems, for example. Many organizations, including insurers, employ data scientists, who spend a lot of time analyzing data and making the results available to decision makers.
Opportunities for Innovation in the Insurance Industry
Although our industry has been making strides to incorporate these new capabilities, a perception still exists that insurance tends to lag behind some other industries, such as retail and finance, regarding the integration of emerging technologies. For instance, the insurance business is doing far less than the retail sector when it comes to using technology for marketing and customer acquisition purposes.
In recent years, the retail industry has been much more willing to buy data and use technology to gather detailed information about individual customers for purposes of highly targeted marketing and increased sales. One example is the emerging use of video surveillance and facial recognition tools to monitor behaviors of in-store customers. While such technology can be used for security purposes, it can also be used to monitor individuals shopping behaviors, allowing retailers to create personalized customer profiles and specifically tailor their marketing and sales approach in a way more likely to increase sales.
Part of the reason for our industrys slower adoption of some emerging technologies is the nature of the industry and the unique regulatory requirements we face, and part may also be the natural inclination of risk management professionals to avoid or limit risk. While such characteristics may limit the speed with which we employ technology and analytics relative to other industries, our approach also has virtues. For instance, we tend to be a bit more deliberative and careful in the way we handle privacy and the impact that new technologies might have on customers. When it comes to the use of technologies such as facial recognition software, customer privacy is a legitimate concern.
However, the insurance industry could definitely improve in our approach to technology. Here are a couple of ways:
Digitization and Centralized Storage of Data
Not all insurance organizations realize or put enough emphasis on the fact that all of the data they have available to them, taken from a variety of sources, represents a tremendous strategic asset. They may store all of their various data in disparate places, complicated by inflexible legacy data systems. This can make comprehensive analysis very difficult. Insurance companies should work to digitize as much of their data as possible and store it in a centralized data warehouse or networked data marts. These types of systems help facilitate advanced analytics, including the discovery of trends and data interactions that might not otherwise have been noticed.
Innovation Through Cooperation
To fully realize the potential of big data, emerging technologies and advanced analytics, insurers need to innovate and develop new practices that may, at first, be resisted by many staff members. Furthermore, sharing of data among insurers through intermediaries is an important part of facilitating this innovation. This can be difficult, as the industry has traditionally been a bit fragmented in this regard. Here is where organizations like The Institutes and The Institutes CPCU Society come into play, providing industry-wide education on data management, emerging technologies and advanced analytics and helping to bring together professionals across the insurance business to ensure the successful future of our industry and its ability to serve society.
Ours is a great industry that provides a tremendous service. Insurance is a vehicle for helping people when they are in need. Big changes in data and technology bring great opportunities for improvements in the way society receives this service. It is our responsibility as an industry to continue learning as much as we can and to do our best to innovate in a way that provides for our customers and the general public in the most effective way possible.