Considerations for sports and entertainment insurance

Individual sport and entertainment attractions have distinct insurance needs that make traditional actuarial and underwriting approaches insufficient. Insurers needs to customize policies according to the unique risks present at different events.

In the article “Insuring a lazy Saturday afternoon: Insurance for entertainment,” Milliman’s Will Carbone uses a hypothetical family outing to frame the distinct insurance needs associated with a county carnival and a baseball game. Here is an excerpt:

On Long Island, traveling carnivals pop up in parking lots all summer long, attracting kids of all ages and fans of Americana. On this sunny Saturday, I packed up the family and we headed down to the train station, the site of this weekend’s festival. My oldest son let us know definitively that our first stop would be the bouncy houses he loves so dearly. Much to our dismay, this particular carnival had all sorts of rides, games, and food, but did not have a single inflatable attraction. “Where is the bouncy house?!”

“Well, not all carnivals have the same rides,” I tried to explain.

This example highlights the difference between providing coverage for traveling carnivals, theme parks, and other one-off facilities compared with a franchised location. With few exceptions, each of these entertainment spaces was tailored to maximize profit.

For small, mobile operations, this means selecting the rides and games that will make them attractive to the host facility. For the insurer providing cover for the carnival, this means that the pricing needs to be done on a more granular level. Typically, the approach is to price the coverage for each attraction rather than for the collective carnival. A premium is determined for each attraction, and the cost of coverage is based on the sum of the premiums for the attractions at the carnival. This simplifies the underwriting efforts as a unique quote is only needed once for each attraction and does not need to be tailored to each insured.

Pricing individual rides becomes difficult when the ride itself is a unique risk. Larger scale operations seek to provide the big thrill that will draw in crowds. Those big thrills are coming not from tried-and-true roller coasters but from the cutting-edge rides that are considered a “one-of-a-kind” experience. By definition, these rides don’t have a credible history on which underwriters can gather data and price the risk, increasing the challenge of pricing these facilities.

Issues in brief spring 2016: UK life insurance

The Spring 2016 edition of Milliman’s Issues in Brief features articles about the dynamic reporting of management information (MI), valuing lifetime mortgages, the Own Risk and Solvency Assessment (ORSA) process, and embedded value reporting.

Agent Orange is the new black lung

Carbone-WilliamLatent occupational diseases began to emerge in the 1970s as complex risks that could result in future, unknown costs. While asbestos comes to most people’s minds, asbestos claims have generally been handled in tort outside the workers’ compensation systems. Compensation for exposure to coal dust (black lung) generally predated asbestosis and has been handled under workers’ compensation since 1973, under both state workers’ compensation systems and the Federal Coal Mine Health and Safety Act of 1969. So what other latest occupational diseases are potentially of interest to workers’ compensation insurers?

Agent Orange coverage and benefits are still being shaped and molded today. Claims started coming to the Department of Veterans Affairs shortly after the Vietnam War, but were mostly denied until the 1990s when a list of presumptive diseases was created, making it easier for veterans to receive benefits. Similar to black lung, the rules guiding who receives benefits have been changing over time. Under the Agent Orange Act, the Department of Veterans Affairs has expanded the list of “presumptive” conditions. However, the area where less progress has been made is deciding who is covered. Just last year coverage was expanded from “boots on the ground” soldiers to include Air Force personnel who served on the aircraft used to spray Agent Orange. “Blue Water” veterans of the Navy are still fighting to get coverage today.

The effects of black lung and Agent Orange exposure have a potentially obvious link back to their source; however, other occupational hazards are harder to track. The link between coffee roasting and lung cancer is being investigated, with diacetyl exposure being the possible connection. A lack of accurate occupational information in the workplace-illness records or death certificates makes the connection harder to identify. The debate is likely to rage on, even as the number of small, artisanal coffee shops—not to mention the number of potentially exposed employees—continues to grow.

Every beer drinker in America knows about the recent growth in the craft brewery business. Like a genie popping out of a bottle, a new tap seems to show up in your local watering hole every week. Similar to coffee roasting, the milling part of the beer brewing process releases dust into the air. This dust poses two problems; it’s potentially combustible and it can be irritating to the respiratory system. Air handling at breweries is very important and proper dust management guidelines are in place, but it is not clear how effectively these guidelines are followed or the number of people working in the industry. The exposure may continue to grow and, as with coffee roasters, should be tracked.

Readying itself for the potential cascade of occupational hazard claims on the horizon is in the best interest of the insurance industry. One way to do this is to push for improvement in occupational definitions, especially in medical records accompanying workers’ compensation claims. Developing a sterling database to help identify the connections between occupational exposure and conditions would also be helpful. In the end, no insurer wants to see their centennial celebration at the local Knights of Columbus ruined by a magnum cluster of latent injury claims.

Nuclear waste issues

An actuary can evaluate the current financial implications of future contingent events, and this enables them to consider actuarial approaches outside the financial industry, as in the nuclear waste sector. In Belgium, Milliman assisted the governmental institute NIRAS, which is responsible for the collection of highly radioactive waste from nuclear power plants. Milliman applied existing life insurance software to project planned cash flows and their security margins and performed market-consistent, risk-neutral valuations as well as real-world projections. Milliman consultant Kurt Lambrechts offers perspective in the April 2016 issue of The European Actuary.

Milliman sponsoring data science competition

Milliman is a sponsor of the 2016 Data Science Game, a two-phase competition showcasing teams of data science students from universities around the world. After an online eliminatory challenge, the best 20 teams will be invited to a two-day competition in Paris.

Last year, teams competed to solve a machine learning challenge created by Google. Students from the Moscow State University won the competition. Who will win this year?

Teams can register at The deadline to register is May 31. The online challenge will take place in June while the two-day competition is scheduled for September.

Discussing ERM with the board and CEOs

Mark GreisigerFounded in 2011, the Milliman Risk Institute provides scientific-based thought leadership on all facets of enterprise risk management (ERM). Composed of senior risk executives, actuaries, and university professors, the Milliman Risk Institute Advisory Board meets semiannually to discuss ERM trends, research, and key topics.

In this blog series, members of the Milliman Risk Institute Advisory Board share their views on ERM research and development and how it can support business insight.

One of the ongoing issues in enterprise risk management (ERM) is the role of a board of directors and chief executive officer (CEO). What risk-related decisions should rise to the level that requires their participation? This year, NetDiligence is rolling out a new service called CEOcyberA!ert. This service allows us to build and host a data breach incident response plan based on a company’s unique requirements. The company can then access its plan on the fly from an iPhone as a crisis is unfolding on a Saturday night (including direct access to the company’s cyber liability insurance carrier’s breach response experts, thus maximizing coverage benefits). This is another step in rationalizing specific approaches to specific risks.

One response we include each fiscal period is notifying the board and/or CEO of certain key events. In researching assumptions for CEOcyberA!ert, NetDiligence found that, in many cases, boards and CEOs are careful to avoid being overwhelmed. They want to be hands-on, but not too hands-on—they want balance—and many of them know they don’t have the necessary technical understanding. Still, they want to know enough to feel they have taken reasonable due care, having paid attention to all significant issues.

The Wyndham Hotels case is a good example. There was a series of incidents involving the hotel chain in which it was attacked by hackers three times between 2008 and 2011. The Federal Trade Commission looked closely at Wyndham’s potential corporate culpability. Wyndham’s board was able to demonstrate that it had been doing enough on a quarterly basis for the court to find its cyber security efforts reasonable. That’s essentially what we’re hoping to do—give boards and CEOs enough tools to exercise effective due diligence and defend themselves against any charges of security negligence. They’ll be able to demonstrate the steps they’ve taken. As a service, it’s actually as easy as an annual subscription.

In the past, our services have been far removed from the board, but that’s starting to change now. Federal agencies are looking at corporate behavior in these realms with a more critical eye, holding boards and CEOs to higher standards. Normally, we’re brought in by, and deal with, mid-level information technology professionals or risk managers in the chief financial officer’s chain of command.

A decade ago, the federal government enforcers, such as the Office for Civil Rights, were not really penalizing companies yet. That has changed dramatically over the last few years, and we think it could start happening with other regulatory bodies, too, because they recognize the need to promote good security and privacy and to protect citizens’ data. Penalty dollars fund these departments, so they have incentive to go after board members and CEOs more aggressively. Boards and CEOs are starting to recognize this—and recognize the importance of being in the loop on all key security issues.

A cyber pioneer and thought leader, Mark Greisiger serves as the President of NetDiligence, a cyber risk assessment and data breach services company. In October 2015, Mark presented at the Milliman Risk Institute Advisory Board Meeting as a keynote speaker. His remarks were well-received and followed by a robust Q&A session. As part of this blog series, we invited Mark to provide some additional commentary to his speech and share his views on trending topics in ERM.

Predictive analytics can make playing daily fantasy sports a homerun

While most daily fantasy sports (DFS) players usually swing and miss, big data management and predictive analytics have the capacity to increase a player’s chance of winning more consistently. In this article, Milliman’s Michael Henk and Nicholas Blaubach discuss the monetary success that some advance modelers are having on DFS websites using predictive analytics. The following excerpt highlights the steps necessary to build a DFS predictive model.

There are some basic steps that serve as general “rules of thumb” when we set out to develop our predictive model to make us millions in DFS.

First, we need an objective. We want our model to optimize our roster, giving us the most potential points. In our DFS example, we’d want a predictive model that will help us identify the best players for the cost (in order to stay under the salary caps) for any given contest.

Next, we gather our data… Gathering the data and getting it into a proper format for our predictive model is another story, but historical sports data is easy to find online. One thing to consider here is the traditional actuarial concern of credibility. If the data isn’t credible, it’s highly unlikely that we’ll be able to build a successful model from it….

After we choose the data to use, we need to select and transform the specific variables in the data set. The structure of the predictive (or independent) variables in relation to the target (or dependent) variable determines how well a model works. We can transform variables (by taking logarithms, for example) or bucket variables to see what gives us the best fit. Sports data can have hundreds (or even thousands) of variables….

Next, we process and evaluate our model. The key to good model performance is obviously getting the best fit. If we’ve done the other steps up to this point well, this step should run smoothly. Here we identify the ideal number of variables and use performance metrics to evaluate the model fits….

Once all of that is done, it’s important to not merely implement the model and ignore it. It requires routine maintenance. As time goes by and data continues to emerge, we need to take time to reinvestigate the data, update the models, and challenge some of our initial assumptions. The best models are continually updated and recalibrated, audited on a regular basis, and replaced when they are no longer effective.

Milliman Risk Talks: ERM for retail operations

In this episode of Milliman Risk Talks, Mark Stephens and Vikas Shah explore the evolving role of enterprise risk management (ERM) in the retail industry. They also discuss some of the day-to-day challenges that risk managers face in this sector. From the alignment of risk culture to the quantification of strategic and operational risks, many of the perspectives shared can be applied to industries outside of retail operations.

To watch our Milliman Risk Talks series, click here.

To learn more about the Milliman Risk Institute, click here.

Diversification of longevity and mortality risk

Insurance companies can generate value when pricing, setting deterministic margins, determining economic capital, and determining its optimal mix of business by performing stochastic modeling with volatile mortality assumptions. In this case study, Milliman consultants Dan Theodore and Stuart Silverman explore relevant questions related to margins using a simple combination of life insurance and payout annuity products by applying stochastic projections of future mortality rates. It also compares percentile values from the stochastic projections to results using deterministic projections and margins. In addition, the study demonstrates the relative diversification benefit of the longevity exposure from the annuity product along with the mortality exposure of the life insurance product.