Issues & Answers Special Advertising Section:
 August 2021

Issues & Answers: Determining Risk Distribution

“EAD is an excellent actuarial tool because it can be applied objectively and can be easily understood by captive owners and other stakeholders.”

Risk distribution in insurance is the aggregation of risks to reduce the potential volatility of loss. It is also one of the requirements to be an insurance company. To determine whether or not an agreement qualifies as insurance, it is common to consider a four-prong test: 1) the agreement needs to meet the commonly accepted notions of insurance; 2) it must involve insurance risk; 3) it must transfer risk from the insured to the insurance company; and 4) there must be risk distribution within the insurance company. This makes risk distribution vital to captive insurance companies. Insurance companies rely on their ability to distribute risk across a critical mass of exposures to withstand significant losses.

Although there is some helpful IRS guidance, there is no single, objective way to determine risk distribution. Historical tax court decisions have been at times inconsistent and ambiguous. IRS guidance to date has been more focused on corporate structures rather than measuring the amount of risk distributed. That said, there have been more recent tax court decisions that recognize that any measure of risk distribution should consider the amount of exposures being covered as well as the reduction in the variability based on aggregating these exposures.

Are there any good objective measures of risk distribution?

At Pinnacle, we felt that the measure of how much risk is distributed based on an insurance company’s risk exposures was an actuarial question. We have worked to develop a straightforward approach to measure it. We considered a number of different potential measures but weren’t satisfied with the initial options available. We felt that any measurement we settled on needed to be transparent, acceptable to regular users and not easily manipulated. Ultimately, we wanted to be able to measure how well an insurance company reduced the volatility of their losses by distributing their risk. And, we wanted to do it in such a way that we could easily explain to key stakeholders. What we devised was Expected Adverse Deviation, or EAD. We think EAD effectively answers the question, “How much risk distribution qualifies as insurance?” But we also think EAD is the most robust risk distribution measure for other key reasons.

What is the EAD calculation?

EAD represents the average amount of loss that the insurance company incurs in excess of the expected losses, or the expected amount of adverse deviation an insurer is exposed to. It is most clearly expressed as the EAD ratio, and to test for risk distribution, we need to normalize the EAD value by dividing by the expected losses. This EAD ratio measures how much volatility or risk an insurance company is taking on relative to its expected losses. The higher the EAD ratio is, the riskier the insurance company. As an insurance company diversifies its risk we should expect to see the EAD ratio decrease. And, the EAD ratio has a maximum value of 100% and a minimum value of 0%, which makes it easier to compare different types of insurance and exposures.