It may seem the insurance industry is more cautious and moves more slowly than other industries when it comes to improvements in technology. How insurers are leveraging advanced analytics is no exception. However, that isn’t to say that the industry is standing on the sidelines. Most insurers are making progress that promises to position data, business intelligence, and analytics as a function area of the enterprise much like finance and human resources.
Industry observers and surveys have confirmed that insurers have made slow but steady progress in advanced analytics adoption. Insurers realize that evolving past traditional methods into advanced capabilities that help them gain insight into future likelihoods and forward-looking opportunities have become imperative. And, they are using emerging technology and access to big data to improve customer service, streamline processes, and transform claims management.
Increased spending for advanced analytics
The evolution towards the adoption of advanced analytics requires increased investment. In 2017 personal line insurers spent, on average, 8.6 percent of their total IT budget on data and analytics. The important point here is that this spending is increasing. Forty-one percent of insurers are increasing their spending year over year by 6 to 10 percent. And, an additional 41 percent are increasing spending by 1 to 5 percent. This increase in spending indicates that insurers recognize the value of data and analytics and want to continue to optimize their investments and business outcomes.
Improved customer service
According to a survey conducted by Willis Towers Watson, the majority of insurers have big plans to increase their use of advanced analytics and new technology over the next two years. One of the primary areas of focus is on improving the customer experience. A full 67 percent of insurers promise faster service, 65 percent foresee faster and easier access to information, 61 percent plan to offer a more personalized experience, and 53 percent will deliver more mobile-friendly interactions.
Other customer-oriented efforts include improving agent performance, generating new business, customer relationship management, customer segmentation, and gaining a single view of the customer. These areas focus on using data to improve customer relationships, marketing, and distribution. This makes sense because investment in these areas is historically higher than other categories.
Streamlined processes through artificial intelligence and machine learning
Streamlining processes through artificial intelligence (AI) and machine learning results in lower cost while freeing up time for humans to apply the knowledge gained through advanced analytics. The top applications that insurers plan to use for AI and machine learning are:
Reduce time spent by humans
Identify high-risk cases
Build risk models for better decision making
Help humans identify appropriate risk attributes
Better understand risk drivers
Identify patterns of fraudulent claims
Augment human-performed underwriting
Claims management transformation
With so many claims to manage, adjusters don’t have as much time as they need to sift through the claim data to evaluate each claim. Consequently, they may not make the best decision if they miss a piece of important information. This means that many of their decisions are based on gut feelings. This will soon change as data analytics begins to play a more important role in the claims management process.
The impact of advanced analytics on claims management by 2020 is predicted to be extremely dramatic. The use of advanced analytics for the evaluation of claims for fraud potential will jump from 26 percent to 82 percent. The use for evaluation of claims for litigation potential will jump from 15 percent to 74%. The use for claim triage will jump from 26 percent to 80 percent. And, the use for evaluation of claims for subrogation potential will jump from 13 percent to 62 percent.
Future data sources
Where is the data coming from that will fuel these advancements? The Willis Towers Watson survey reports that the top-growing new data sources for insurers offering personal lines include:
Smart home data
Telematics – Usage-based insurance information
Unstructured internal claim information
Unstructured internal underwriting information
Preferences for obtaining new and emerging data sources
Options for collecting and managing new data are growing to accommodate the needs of insurers. When surveyed, 51 percent of insurers prefer to collect and manage their own data in their own systems. While this may be a preference, there are significant technical and operational barriers when it comes to using legacy systems to manage big data. Until this internal problem is solved, access to insights and opportunities will be limited.
Another 49 percent of respondents reported that industry consortiums and exchanges are their preference. For smaller insurers, these sources are an excellent choice for securing data they may not be able to gather by themselves. Finally, 40 percent of insurers believe that working with insurtech companies is an excellent way to mitigate the barriers discussed above.
What success looks like
Many carriers have made, and will continue to make, progress in building capability. However, they have only scratched the surface in realizing the impact of data analytics. True success means achieving scale in bringing science to insurance. Achieving scale means having analytics initiatives that fully support pricing and underwriting, claims, distribution, and operations. When this happens, insurance organizations will be in the position of capturing an unrivalled competitive advantage.