Data Visualization:
An Important Tool
for Insurance, Risk Management

By Max Dorfman, Research Writer, Triple-I

Data visualization has become an increasingly important tool for understanding and communicating complex risks and informing plans to address them.

Simply put, data visualization is the depiction of data through static or interactive charts, maps, infographics, and animations. Such displays help clarify multifaceted data relationships and convey data-driven insights.

The origins of data visualization could be considered to go back to the 16th century, during the evolution of cartography. However, modern data visualization is considered to have emerged in the 1960s, when researcher John W. Tukey published his paper The Future of Data Analysis, which advocated for the acknowledgement of data analysis as a branch of statistics separate from mathematical statistics. Tukey helped invent graphic displays, including stem-leaf plots, boxplots, hanging rootograms, and two-way table displays, several of have become part of the statistical vocabulary and software implementation.

Since Tukey’s advancements, data visualization has progressed in extraordinary ways. Matrices, histograms, and scatter plots (both 2D and 3D) can illustrate complex relationships among different pieces of data. And, in an age of big data, machine learning, and artificial intelligence, the possible applications of data science and data analytics has only expanded, helping curate information into easier to understand formats, giving insight into trends and outliers. Indeed, a good visualization possesses a narrative, eliminating the extraneous aspects of the data and emphasizing the valuable information. 

Whether for tracking long-term rainfall trends, monitoring active wildfires, or getting out in front of cyber threats, data visualization has proved itself tremendously beneficial for understanding and managing risk.

The Triple-I uses data visualization in its Resilience Accelerator to better illustrate the risks many communities face with natural disasters, particularly hurricanes, floods, and resilience ratings. Spearheaded by Dr. Michel Leonard, Chief Economist and Data Scientist, Head of the Economics and Analytics Department at the Triple-I, these data visualizations provide an ever-needed way to more effectively communicate these hazards, expanding the knowledge base of insurers, consumers, and policymakers.

To further understand data visualization, we sat down with Dr. Leonard.

Why is data visualization so essential in preparing for and responding to catastrophes? What immediately comes to mind is maps. We can make spreadsheets of policies and claims, but how do you express the relationships between each row in these spreadsheets? We can use data visualization to show how houses closest to a river are most at risk during a flood or show the likely paths of wildfires through a landscape. Before a catastrophe, these tools help us identify at-risk zones to bolster resilience. After a catastrophe, they help us identify areas that need the most to rebuild.

How can data visualization help change the way insurers confront the challenges of catastrophes? The most crucial aspect of data visualization for insurers is the potential to explore “what-if” scenarios with interactive tools. Understanding risk means understanding what range of outcomes are possible and what it most likely to happen. Once we start accounting for joint outcomes and conditional probabilities, spreadsheets turn into mazes. Thus, it’s important to illustrate the relationship between inputs and outputs in a way that is reasonably easy to understand.

With the increasing threat of climate risk, how much more significant do you anticipate data visualization will become? I’m reminded of the writings from the philosopher Timothy Morton, who described climate change as a “hyper-object”: a multifaceted network of interacting forces so complex, and with so many manifestations that it is almost impossible to fully conceptualize it in your head at once.

Climate change is complicated and communicating about the risks it creates is a unique problem. Very few people have time to read through a long technical report on climate risk and how it might affect them. Thus, the question becomes: How do we communicate to people the information they need in a way that is not only easy to understand but also engaging?

Images or infographics have always been compelling tools; however, we prefer interactive data visualization tools for their ability to capture attention and curiosity and make an impression.

How does the Resilience Accelerator fit into the sphere of data visualization? With the Resilience Accelerator, we wanted to explore the interplay between insurance, economics and climate risk, and present our findings in an engaging, insightful way. It was our goal from the beginning to produce a tool that would help policymakers, insurers, and community members could find their counties, see their ratings, compare their ratings with those of neighboring counties, and see what steps they should take to improve their ratings.

What motivated this venture into data visualization – and how can it help change the ways communities, policymakers, and insurers prepare for natural disasters? It’s our job to help our members understand climate-related risks to their business and to their policyholders. Hurricanes and floods are only the first entry in a climate risk series we are working on. We want our data to drive discussion about climate and resilience. We hope the fruits of those discussions are communities that are better protected from the dangers of climate change.

Where do you see data visualization going in the next five to 10 years?
I’m interested in seeing what comes from the recent addition of GPU acceleration to web browsers and the shift of internet infrastructure to fiber optics. GPU acceleration is the practice of using a graphics processing unit (GPU) in addition to a central processing unit (CPU) to speed up processing-intensive operations. Both of these technologies are necessary for creating a 3-D visualization environment with streaming real-time data.

Triple-I/Milliman See Loss Pressures in P&C Industry Continuing

Triple-I/Milliman See Loss Pressures in P&C Industry Continuing

By Max Dorfman, Research Writer, Triple-I

The latest insurance underwriting projections for property/casualty lines by actuaries at the Triple-I and Milliman – an independent risk-management, benefits, and technology firm – reveal that the industry saw the 2021 combined ratio worsen by 0.8 points from 2020, driven by deterioration in the personal auto and workers compensation lines. The report, Insurance Information Institute (Triple-I) /Milliman Insurance Economics and Underwriting Projections: A Forward View, presented at a members-only event on May 12, also found that homeowners, commercial auto, commercial multi-peril, and general liability all experienced significant improvement year-over-year.

Michel Léonard, PhD, CBE, Chief Economist and Data Scientist, and head of Triple-I’s Economics and Analytics Department, discussed key macroeconomic trends impacting the property/casualty industry results. He noted that the U.S. P&C insurance industry’s performance continues to be constrained by historically high inflation, which affects replacement costs.

“The insurance industry’s performance continues to be severely constrained by macroeconomic fundamentals,” he said “The average replacement costs for P&C lines is 16.3 percent, nearly twice the U.S. average CPI of 8.5 percent.”

Léonard noted that while the Federal Reserve forecasts U.S. inflation slowing to 4.3 percent by yearend, “Triple-I expects the transition to take longer.”

Dale Porfilio, FCAS, MAAA, Chief Insurance Officer at Triple-I, noted that 2021 had the worst full-year catastrophe losses since 2017, though Q4 actuals were materially lower than prior expectation. Kentucky tornadoes and Colorado wildfires in December were part of these losses, with homeowners suffering over 60 percent of the insured losses. Hurricane Ida was the worst single event, although multiple other billion-dollar events also contributed to the 2021 insured catastrophe losses.

“Healthy premium growth observed in 2021 is likely to continue through 2024 due to the hard market,” Porfilio said, adding, “Net expense ratio at 27.0 points was the lowest in more than a decade due to premiums growing at a faster rate than expenses.”

For the P&C industry as a whole, he said to expect loss pressures to continue due to inflation and supply chain disruption.

On the commercial side, Jason B. Kurtz, FCAS, MAAA, a principal and consulting actuary at Milliman, said  the commercial multi-peril 2021 combined ratio improved 3.6 points from 2020, primarily due to strong net earned premium growth, which stood at 6.3 percent year over year, from the economic recovery and a hard market.

“Despite the improvement relative to 2020, the CMP line still experienced an underwriting loss in 2021, and we expect underwriting results in 2022-2024 will continue to be adversely impacted by inflation and CAT loss pressures,” he said.

Workers compensation had another very profitable year, Kurtz said, with the 2021 combined ratio coming in at 91.8 percent, although margins shrank in 2021 and are expected to continue to shrink through 2024.

“The workers comp line has experienced seven straight years of underwriting profitability, a remarkable turn-around after eight straight years of underwriting losses,” Kurtz said.  “Not surprisingly, rate increases have been hard to come by. Coupled with low unemployment, these forces will constrain premium growth for the foreseeable future.”   

For commercial auto, the 2021 combined ratio improved by 3.0 points from 2020 due to lower adverse development and a two point reduction in expense ratio, according to Dave Moore, FCAS, MAAA of Moore Actuarial Consulting.

“The 2021 combined ratio dipped below 100 percent for the first time since 2010 and we’ve had the lowest expense ratio in more than a decade,” he said. “Watch for social inflation loss pressure and prior year adverse loss development in 2022-2024.”

According to projections, both personal auto and homeowners lines produced underwriting losses in 2021. Prices need to reflect the underlying risk, particularly because the economic risk is quickly escalating.

Porfilio said the 2021 combined ratio for personal auto jumped up to 101.4, the worst since 2017 and 8.9 points worse than 2020.

“While miles driven are largely back to 2019 levels, riskier driving behaviors have led to increased insured losses and fatality rates,” he said.

Overall, the loss pressures from inflation, supply-chain disruption, risky driving behavior, and increasing catastrophe losses are leading to the need for rate increases to restore both homeowners and personal auto lines to an underwriting profit, which is projected to take at least two more calendar years.