I am an avid reader of Doug’s research at McKinsey on pricing and underwriting, but I only had the opportunity to meet him in person at the ITC in September 2022.
We have spoken several times since, but this is the first time I had the honor of hearing Doug discuss his views on the convergence of today’s global trends and the insurance industry’s trajectory, and what is required from insurers to adapt to this brave new world. The discussion was inspiring.
Doug discusses some of the volatile trends we are all experiencing (from climate to inflation), ties these into the required changes for insurers’ business and operational model, and summarizes with the question, “In 3-5 years, will insurers be able to run their business without adopting a new model?”
A Quote from Doug McElhaney
“In today’s environment, basic trends that have been consistent for decades have become volatile and unpredictable… we need a wider view of the world that includes much more information. We cannot continue to rely on what was historically a relatively set number of data sources, even if they have been used and vetted for years or decades.”
David Schapiro (DS): Could you please tell us about yourself and how you found your way into insurance?
Doug McElhaney (DM): After close to 15 years in corporate IT operations and completing grad school, I joined McKinsey. My first assignments were in insurance operations. Following that, I joined the leadership team developing a partnership between McKinsey and an advanced analytics big data company—all the while keeping in contact with the insurance execs I met in my initial assignments.
I was then asked by McKinsey to establish a service line of data scientists and analytics professionals focused on delivering distinctive and innovative advanced analytics solutions to our insurance clients. As the insurance knowledge required from this position was far more than my initial assignments, I did my own insurance crash-course. It took me close to a year to get the basic understanding to lead the service line, and I have continued to learn about and be a student of insurance ever since.
As a statistician by training (and at heart), I found insurance to be structurally poised for transformation from an analytics perspective. And I decided that insurance is the place to be. Now, I spend all my time helping clients take full advantage of advanced analytics across the insurance value chain—with a particular focus on pricing and underwriting.
DS: What are some of the key dynamics you see in today’s world that are relevant for insurers?
DM: In today’s environment, basic trends that have been consistent for decades have become volatile and unpredictable. Examples include inflation and climate change, both of which require extensive analysis and effort from carriers to keep up with this continued volatility.
In some cases, inflation is now changing quicker than a carrier has time to react—which requires analyzing the data, making decisions based on the analysis, filing changes in rates and/or forms, and then there is the time required for a pricing change to earn in which is anywhere from 9-18 months.
With climate change we are experiencing one in 100- or 200-year weather events on a much more rapid cycle of every 10-15 years (or less). It appears that our stochastic models have lost their stationarity; that we can no longer assume a reversion to the mean over time.
DS: How would you recommend insurers react to this loss of stationarity?
DM: In this environment it is important for insurers to rethink, test, and challenge their approach to pricing. This “rethinking” should include the entire cycle—from the data through analytics and execution of actions—what we call the “data to insight to action” process.
Today, we need a wider view of the world that includes much more information. We cannot continue to rely on what was historically a relatively set number of data sources, even if they have been used and vetted for years or decades. This expansion of data provides additional insight, but also creates a downstream challenge as current analysis and decisioning processes were not necessarily designed to quickly incorporate a broad set of new data. And it’s coming in at an accelerated pace.
There are multiple dependencies across factors that affect the cost of claims, including supply chain delays, raw material prices, weather, inflation, etc. We need to take all of this into consideration at the time we price and underwrite the product, as these factors are volatile and will change between the policy bind and time of claim—impacting loss ratios. Pricing teams should aim to be much more connected to the claims team, their data, and any emerging insights. Claims is often the “canary in the coal mine,” but their raw data doesn’t necessarily lend itself to pricing-oriented analyses.
In parallel, we need to evolve our data and technological capabilities to continuously run preemptive “what-if” scenarios that can help mitigate dramatic shifts in claims costs.
DS: How do you see this impacting insurers’ modus operandi?
DM: Insurers need to change their assumptions and pricing ops model. The cycle of reviewing and interpreting information must become much quicker, dynamic, and nimble—and much more connected across the organization. Carriers must look at data, convert it to insights, make decisions based on these insights, and execute actions based on these decisions—by an order of magnitude faster than it’s done today.
This requires the capability to make decisions and take actions based on partial data, that might achieve “only” good-but-not-perfect results. As the cycle is quick and continuous, in subsequent cycles the results are improved. This is a must in today’s volatile/dynamic world. No longer can we wait for complete data (which could become outdated before it is complete) before taking action (or the action could be taken too late). This agility does not exist in most carriers today, but it needs to be adapted.
Building this new agile pricing capability requires a learning mindset. This will take a bit of time to develop, and it won’t be exactly right in its first incarnation. Carriers need to be open to this and recognize that pricing needs to become a living, evolving system.
DS: This appears to require a material change in the way insurers work—how critical is it?
DM: This is critical for a carrier’s business. In several insurance lines, it’s increasingly becoming a winner-take-all situation, and accelerating in that direction with winners increasing the strategic distance between themselves and their competitors.
If you were to build a graph of growth vs combined ratio, you would see the leaders moving more up and to the right and all others are falling further down and to the left. Non-leading insurers can at best focus on either improving profitability or growth—but not both. Many are currently “shrinking” to profitability.
This is a material challenge for the insurance industry.
DS: Do you see this solely as a leadership-oriented change, or is it more of a cross-level cultural change?
DM: Incorporating this agility requires addressing knowledge from the bottom up. Every employee at every level needs to be looking at what’s happening all the time. For example, if there are preliminary signs of performance deteriorating in some states while the rest of the book appears to be fine, the data should be analyzed immediately and acted upon instead of waiting until the next scheduled pricing cycle.
Although it may seem contrary to the analytical and risk-averse mentality associated with successful insurance strategy, carriers must begin to adopt an agile mentality and execute on much smaller time cycles. To survive in today’s world, insurers need to add the DNA of agility in execution. This requires changing processes and procedures, which can be a significant culture challenge.
Carriers will need to become comfortable with being wrong some of the time, and establish a flexible perspective on how to define “wrong.” Taking action that moves the organization toward a goal but doesn’t necessarily hit the exact target should be viewed as a positive step instead of a failure. That said, this requires a cultural change of being okay with not being right all the time, as long as there is a continuous and rapid improvement cycle that converges to optimal/better results—and recognition that the organization has the ability to address an action that was directionally correct but didn’t have the impact that was expected.
If you build an agile-based system that is nimble and responsive, you can feel confident in your capability to course-correct quickly if you don’t quite hit the mark in the first instance of an action.
There is a fear-factor that must be overcome. For instance, insurers today are concerned that if aggressive rating or pricing actions are implemented there could be substantial reduction to the size or profitability of their book—which could take very long to identify and then fix. This fear will be allayed by a culture of self-confidence that inspires employees to think “I am willing to take this action, as our organization has the capability to adapt and quickly make changes as required to achieve the optimal result.”
DS: Are there additional complicating factors facing insurers today?
DM: Definitely. There are new insurance products embedded in small timeframes that require “pricing on steroids,” like mobility, travel, SMB commercial, UBI/auto, and the gig economy.
Additional complicating factors include commonly used data points that only provide a small part of the information required to make an underwriting/pricing decision. For example, classifying businesses by SIC code is an important but imperfect method to identify the risk class and often doesn’t supply enough information to make an accurate pricing or underwriting decision. And vehicle symbols are important but is today insufficient, as it does not convey which vehicle features have been purchased by the consumer or activated “over the air” by the OEM on this specific vehicle (e.g., semi-autonomous driving capability).
DS: Can technology address these challenges?
DM: Technology can solve major aspects, but just purchasing and implementing the technology is not sufficient. You must be using and putting it into practice to turn your company into an agile organization. This is the culture challenge.
Intrinsically, insurers underwrite and price risks in specific ways. As discussed above, using SIC codes for small businesses classification often doesn’t supply sufficient information to make an accurate pricing or underwriting decision. A more robust description of the company and what types of services and products it provides can be obtained via technology—including probabilistic measures of SIC code alignment. But it is difficult for insurers to adapt to use this new technology.
DS: This could require changes in insurers’ business model—how do you see this playing out in the long run?
DM: On the aggregate, the insurance business model of the past worked—if the combined ratio gets too high (close to 100) you react, i.e., stop marketing, increase prices, and get back to your comfort zone of COR<100. But this does not work in today’s world of volatile changes, like climate, inflation, etc.
Many carriers have become comfortable with waiting until after loss runs materialize before taking actions. But in today’s market, decisions must be made quickly based on a mix of signals—emerging trends, initial indications, ancillary inputs from the sales and claims teams —or it could be too late.
Adopting this model will be difficult for many insurers, as it is a long-term effort that will take a bit of time to yield impact. For carriers that need to hit quarterly targets, this could be quite challenging.
DS: Are there any final thoughts you would like to share?
DM: If insurers do not rebuild their model of business and actions, it could be an existential risk for the industry. A large carrier can absorb a lot, but smaller carriers cannot—especially if they have challenging exposures (e.g., flood-exposed properties). Reinsurers are also requiring primary insurers to improve, as the reinsurers are beginning to be impacted by the primary insurers mode of operations not adapting to the new volatile world.
Insurers should see this as a “bet”: With these volatile trends increasing, in 3-5 years from now will they be able to run their business without adopting this model?
Doug McElhaney – Bio
Doug McElhaney, Partner at McKinsey & Company, serves the insurance industry broadly, working with carriers, brokers, and insurtechs to develop leading edge technical capabilities and fully leverage AI and advanced data capabilities across their organizations. He also has deep experience providing insights and guidance to PE firms as they navigate a variety of insurance-focused transactions.
Doug has presented and participated in panels on the topic of AI in several forums, including the Geneva Association, NAMIC, and LIMRA. Recent publications include, “Connected revolution: The future of US auto insurance” (Sept 2022) and “The post-COVID-19 pricing imperative for P&C insurers” (July 2020). Prior to McKinsey, Doug spent 10 years at General Electric as both a Six Sigma Expert and in various Technology leadership roles.