(Image credit: Dollar Photo Club.)
The insurance industry consumes massive quantities of data on a regular and ongoing basis. Yet, despite the abundance of this asset and the size and sophistication of the industry as a whole, the majority of insurance companies still don’t know how to adequately quantify and harness the power of this incredibly valuable resource.
Historically, insurance BI initiatives were relegated to the use of spreadsheets, but the introduction of analytics tools brought with it the promise of a whole new world of information and insight. However, the hope for what BI would bring to insurance turned out to be starkly different from today’s reality. Insurers were supposed to have accurate data that would be a) easily accessible and shareable to all, b) very specific, drilling down from summary to individual transactions, c) actionably informative, providing insights on where and how to improve business results, and d) the foundation for data-rich solutions across the enterprise, helping to manage brokers, customers, and operations. That was the dream.
The Early Days of Insurance Data
During the advent and introduction of data platforms to the insurance industry, the message somehow got skewed. For the most part, the industry immediately emphasized these initiatives as mostly technology-driven, not enterprise-driven, spearheaded by disparate department-specific strategies without taking into account enterprise-wide strategic alignment. From the beginning, the two most important, tangible things that these initiatives were designed to produce – actionable insight and information – were lost by not being properly and adequately leveraged by wider groups.
Another shortfall was that these systems were designed to replicate the same segmented, isolated reports, which were already in use by certain designated departments. Instead of being available to the wider enterprise, these lackluster data strategies, along with the systems that originally went along with them, consistently failed to achieve their mandated goals.
Lastly, data strategies were historically viewed as mostly IT initiatives guided and controlled by the IT organization instead of an actual component of an enterprise-wide strategy designed to achieve actionable results and align with corporate direction. From sales channel development to broking, from underwriting to finance, from sales and marketing to reinsurance design and beyond, BI and data analytics should be used throughout the entire insurance value chain–not just by a chosen few–as yet another tool in an insurer’s arsenal to help achieve desired results.
The Possibilities for Company-wide Integrated BI and Data Strategies
Taking a page from the past and learning from what wasn’t done properly in terms of leveraging insurance data to its full capacity, several possibilities come into focus in regards to company-wide integrated BI and data strategies. Here are some of the ways to bring actionable insights to businesses as a whole:
Achieving Better Control–Insurers now have the ability to analyze terabytes of data to identify patterns as to how well (or poorly) the company is performing. Additionally, this empowers businesses to help minimize risk, get a clearer sense for how their product mix is performing relative to the competition’s and to segment their products in order to enable them to tailor product offerings based on defined consumer profile.
Enhancing Risk Avoidance–In today’s environment, relationships tend to be much more decentralized and virtual compared to previous generations, which is all the more reason why insurers must pay particularly close attention to data. Myriad new data sources enable insurers to build statistical models to better understand and quantify risk, much like how insurers employ catastrophe models. Having a better sense of what these models say, insurers can use them to develop–even refine–more insightful underwriting criteria, which reflect risk appetites more closely aligned with organizational objectives.
Enabling Claims Liquidation–Data analytics has played an increasingly significant role in claims management. Today, data analytics routinely works alongside claims adjusters to identify claims for closer inspection, priority handling and more. Since one out of 10 insurance claims is fraudulent, it’s more important than ever that insurers employ more rules-based predictive analytics designed to identify fraudulent claims quicker in the claims cycle. According to industry claims experts, even a 1 percent improvement in an insurer’s loss ratio for a $1 billion insurer is worth more than $7 million on the bottom line.
If utilized correctly, all of these examples–and many more–bring actionable insights to businesses as a whole, rather than just certain departments or individuals. Such insight forms the basis of the development of sound strategy from department to department throughout the entire corporation.
The combination of developing BI and data strategies designed with the enterprise in mind, while taking into account the entire insurance value chain, is a necessity for a new generation of insurers. These tools, and the innovation they offer, help the industry to remain relevant, while at the same time enable a combination of newcomers and established players alike to compete at all levels.