However, we are witnessing a continued rise in the medical component of workers’ compensation, with such trends being greater than indemnity. A significant driver of medical inflation seems to be prescrpiton costs; particularly scripts for opioids which can be perscribed for back pain. These drugs were originally designed to be used for individuals experiencing end-stage cancer pain but are now being prescribed for more common ailments. Excessive opioid use can be addictive, has side effects, and can actually diminish the injured worker’s abillity to recover from an injury and return to work.

For those companies with a significant workers’ compensation exposure, we suggest drilling down to the detail for their medical claims to analyze the cost components. Action steps, including employee education, may need to be taken with claims personnel, insurers and third party providers.

In many respects, the easiest data to work with is a large group of losses of similar size. A large private passenger automobile book is a great example. There are bigger claims and smaller claims, but the bulk are small, and are in a pretty predictable range.

The polar opposite might be a small book of medical malpractice claims. Though such claims can be small, they can also easily range into seven and eight figures. Worker’s comp, especially for higher-risk businesses, can be similar.

Multi-million dollar losses would seem like enough to worry about. But no; there’s another problem here. When one or two large claims occur in a year with just a few smaller claims, the large claims are pushing the numbers around by themselves. Now it can become difficult to tell which claims are typical: the large ones or the small ones? And small claims, which might be settled privately and quickly, play out very differently than large claims, which have to wind slowly through the courts.

For those of us charged with estimating the likely future value of these losses, there are a few approaches available. One is to pull the large losses out of the data altogether. This makes sense when the large losses can be argued to be truly different from the small ones, and when there is good reason to think they will not be repeated. (Though the business side and the audit side often have different opinions about this!)

Another is to choose appropriate caps on the data. If development of losses on large claims is capped at a low level, their influence on the data can be diminished, and more fundamental patterns show up clearly.

Large losses may not jump out in the same way as zero-dollar years or single-digit claim counts. But they can have a huge impact on the bottom line, so it’s essential to keep them in mind.

With insurance losses, credibility problems take a number of forms. One of the most common is having too few years of data. When we can only look back to one or two years of losses, it’s hard to tell good years from bad. More technically, it’s hard to establish a credible estimate of likely future losses.

Standard methodologies might, numerically speaking, produce a result. But the meaning of that result may not be credible. If the business’s operations (and risk-management practices) have been consistent for five or ten years, however, it is easier place some trust in those calculations.

A related problem arises when there are too few losses. Practically speaking, of course, fewer losses is always better, but it makes the numerical work harder. If a typical year has only one or two losses—even if there are many years—it’s hard to say what a typical year would look like. In other words, the data may reflect those individual losses more than they reflect the underlying risk.

Both of these problems arise frequently with captive insurance companies and self-insurance programs, especially those of small or mid-sized firms. These companies may have few losses and a limited number of years of data. Though the captive or self-insurance arrangement may make business sense, it may nonetheless be hard to pin down credible actuarial estimates.

A number of approaches can be used in the face of credibility problems. I’ll take up some of these approaches in coming posts.

Actuaries often develop projections of losses or loss reserves. These amounts are then considered by the corporate client or insurance company. We used to call these projections “expected values” or “estimates”, but in today’s actuarial world they are referred to as the Actuarial Central Estimate. The basic definition of an Actuarial Central Estimate is “…an estimate that represents an expected value over the range of reasonably possible outcomes…Such a range of reasonably possible outcomes may not include all conceivable outcomes, as, for example, it would not include conceivable extreme events where the contribution of such events to an expected value is not reliably estimable.”

I am sure to you non-actuaries out there, the above definition is as clear as mud! So what does the above mean in ordinary language?  Let’s present a simple example:

Actuaries often utilize several methods in the forecasting process.
Suppose the Actuary’s charge is to forecast 2011 worker’s compensation losses for a particular client. He or she uses various methods and comes up with four different results – not unusual. These results are:

Method A = $6,000,000

Method B =   7,000,000

Method C =   8,000,000

Method D =   9,000,000

Assume prior years’ losses after adjusting for inflation and other considerations have largely fallen within the $ 6 – $9 million range. Let us further assume the Actuary believes all methods are equally valid. In this particular instance the Actuarial Central Estimate might be the average of the four numbers or $7,500,000 which is an estimate that represents an expected value over a range of reasonable outcomes. Now, let’s make it a bit more complicated. Suppose Method D results in a value of $12,000,000. The actuary might now say that $12,000,000 seems a bit high, but it is a possible event, so we need to give it some weight, say 10%, with 90% of the weight given to the other Methods. The Central Estimate is still $7,500,000. However, the client may be of the opinion that $12,000,000 is unreasonable and should be excluded from consideration, so the appropriate estimate is the average of $6,000,000 –$8,000,000 or $7,000,000.

The point of the above discussion is to illustrate that Actuaries often need to exercise judgment in their determination of the Actuarial Central Estimate, and clients need to be aware of the underlying assumptions and weights given to the various methodologies.

Feel free to contact AJA ifyou have questions regarding the actuarial methods and processes utilized to arrive at a loss pick or reserve projection.

Over the past several months, we have been receiving more and more industry emails, newsletters and webinar invitations on topics related to Enterprise Risk Management (ERM). For example, I attended Strategic Risk Solutions Inc.’s webinar “ERM for Captives.”

The Casualty Society of Actuaries defines ERM as:
“… the discipline by which an organization in any industry assesses, controls, exploits, finances, and monitors risks from all sources for the purpose of increasing the organization’s short and long-term value to its stakeholders.” Or put more simply, it is the assessment and management of the entirety of an organization’s risks – not just the risks analyzed in a typical loss reserve or loss forecast actuarial analysis.

The focus on ERM has been driven by both external and internal factors. Not only are new regulations and rating agencies driving the push for an organization to develop an ERM plan, but there are internal pushes as well. Boards of both parents and captive companies as well as service providers are suggesting a more enlightened approach to risk management that strives to encompass all risks outside the more readily quantifiable ones.

Developing an ERM plan can seem overwhelming as there is no boilerplate approach that will apply to all organizations. We, as actuaries, can assist management in quantifying and assessing all risks and can tailor the ERM plan to the individual business. We can also work with captive owners to determine which coverages to incorporate into the captive structure to cover more unusual risks and assist in determining the premium level. However, like any analysis, the ERM program will need to be monitored and revised over time.

Are you feeling pressure to implement an ERM plan? Have you already done so? What are your concerns with ERM and your plan going forward?