P&C Insurance Analytics – What Drives Your Priorities?
April 12, 2018| Von Upendra Belhe | P/C General Industry | English
When we say the business environment for P&C insurance is changing at a rapid pace, no one seems surprised. But how are carriers responding to it? Data Analytics is the most accepted transformative force; there seems to be no doubt about that at all. With the advent of artificial intelligence (AI) and machine learning, and multiple viewpoints about the use of predictive analytics within an organization, there is often confusion about the direction/strategy the organization should follow with respect to its data and analytics efforts.
Even though all stakeholders understand the importance of prioritization, especially due to the limited availability of resources, oftentimes the P&C organization is likely to get trapped into one of the limited ways of thinking about analytics priorities. It may fail to recognize that analytics is central to the business, and is almost proprietary in nature. It is about adjusting management style based on data and insights, which a consultant cannot come in and quickly implement.
Actuarial use of analytics has been heavy on pricing applications. The moment analytics is mentioned, the tendency is to think that it refers to predictive analytics and is mostly intended for pricing. The organization’s ability to better price risks in the marketplace and fine tune its algorithms by hunting down all possible data/variables is perceived as a natural priority. Only a few carriers have graduated beyond pricing applications, and only after they exploited its scope. Many fail to realize that business intelligence and analytics are vital to every part of the insurance business. But of those that do realize their importance, very few have challenged their own thinking before taking such a detour in their journey.
Some carriers like to describe themselves as active followers of successful trends in the use of analytics. Their position comes from thinking that they are balanced in their view by being neither enthusiasts nor laggards. In many such instances, the prevailing thought is to grow an understanding of their direct competition in order to gain a business advantage. Consulting organizations thrive on selling ideas and pictures about the competitive landscape. Unfortunately, carriers may not realize that analytics relates to the core makeup of the organization and its appetite can never be compared with competitors' appetites regardless of how “similar” they appear.
Technology is playing a huge role in shaping fears about external forces. Every carrier wants to improve its use of technology within its own limitations of resource availability. The advanced and elegant ways of handling data and analytics initiatives are posing a lucrative opportunity and an obvious next step for many carriers. Rational thinkers within the organization are finding it difficult to object to such prioritizations as they are afraid of being branded as regressive. Asking the core question “So what?” is taking a back seat. These carriers are lured by technological innovations to such a large extent that their purpose - to impact business results - is not emphasized enough. As a result, carriers may not derive the benefits they are hoping for because they are lacking a strong focus on their business objectives in such endeavors.
Some carriers strongly believe their investment in analytics initiatives should be driven by return on investment (ROI). They think they should prioritize analytics initiatives based on how these initiatives directly support their strategic objectives and the size of a measurable ROI. On the surface, this seems to be a very sound position. But if you examine the majority of such situations, you may find that they either failed to measure, or agree on, an ROI measurement that is acceptable to all stakeholders. Interestingly enough, situations where analytics has made great strides for business pursuits has been based on “rapid experimentation,” resulting in the formation of a business benefit case rather than a scientific measurement approach.
Our Remedy – The Gen Re Approach
At Gen Re, we have carefully adopted an extremist business objective-driven position when it comes to the role of analytics. We recommend and follow the path, not of having analytics initiatives that are business-oriented, but of having standalone business objectives that may be impacted by actionable insights. Carriers should strongly consider generating an insights economy rather than thinking of models that can be operationalized for potential business benefit. Sophistication in terms of tools and technology is encouraged only as warranted by business initiatives, rather than the enthusiasm to adopt something new. The prioritization of business initiatives should be led by the CEO and owned by business segment leaders, with analytics as a strong catalyst to make it happen. This sounds simple, but may not be easy, as it may require a change of attitude at all levels, including sponsorship and direct involvement at the CEO level.
Gen Re's Mutual Practice is uniquely structured to specifically focus on helping Mutual companies improve gross underwriting results. Our Direct Model provides unfiltered insights and observations through our exclusive ability to have direct underwriter-to-underwriter dialogue.