By Sean G. King, JD, CPA, MAcc
Principal & In-House Counsel, CIC Services, LLC
Does a low claims history necessarily mean that future premium rates should be lowered?
Last week, I began a series on identifying legitimate and sham captive insurance company arrangements. This series of articles is important because there is much misinformation and urban legend surrounding the notion of sham captive insurance companies. As noted last week, the IRS and some industry pundits have offered a broad set of poorly-chosen characteristics for sham captives that are, frankly, wrong-headed and misidentify far more legitimate captives as shams than identifying true transgressors.
Last week, we covered low claims rates and demonstrated that the occurrence of few claims does not constitute a sham insurance arrangement, as suggested by the IRS and some industry pundits. Insurance legitimacy is a function of achieving real risk shifting and real risk distribution. We demonstrated that common commercial insurance policies, like fire insurance for a dwelling, have low claims rates. In fact, only one in every three hundred homes experiences a fire loss each year. Last week, we did call out two evidences of a sham captive arrangement related to claims, and they are:
–Prearranged written or verbal understandings that no or very few claims (even legitimate ones) will be filed
–Prearranged understandings that insulate one or more insureds from bearing a meaningful portion of the losses associated with claims filed by other insureds
This brings us to another false identifier of sham captive arrangements… that a period of low claims must necessarily result in reduced insurance policy premiums. In the long term low claims could certainly result in reduced premiums, and an actuary can determine when a insured or risk pool arrangement can statistically and reliably contend that their claims history is indeed a trend and not an anomaly. However, in the short term, a few years with low claims experience would rarely justify reducing insurance premiums to acquire the same amount of coverage.
Once again, a mathematical illustration is in order. If you are a homeowner, and you don’t suffer a fire loss for fifteen years, does your insurance premium go down? Obviously not. Your claims rate of zero claims in fifteen years fits well within the expected norm of one fire loss per three hundred dwellings per year. Now, let’s consider a captive reinsurance pool with fifty captives. If all of them insured for fire loss, the pool could go at least six years with no claims before reasonably considering that its loss history might be outside of U.S. norms, thereby justifying a reduction in future policy premiums.
Because they do not benefit from the law of large numbers, small captive insurance companies and their risk pools may appear to have low claims that would justify lowering premium costs. And, of course, large commercial insurers with thousands, and even millions of insureds, will have far more predictable claims rates as a natural by-product of the law of large numbers. This situation, however, can cut both ways. The risk pool with fifty captives referenced earlier could experience five fire losses in one year, making the cost of claims much higher than would have been actuarially predicted for each member of the pool. In fact, the captives in question and their reinsurance pool may be unable to pay out all five claims in the very unlikely event that five of fifty dwellings had a fire loss in one year.
The point is simply this: professional actuaries, using sound statistical models, determine when an insured or group of insureds claims history warrants lowering or raising premium costs.
Tangentially related, it’s worth noting that the U.S. Tax Court does not expect captive insurance companies to operate like commercial insurance companies. In the recent Rent-A-Center case, in the opinion of the majority, it was noted that commercial insurers often lose money on purpose to gain market share. The court pointed out that captive insurance companies are not in competition and would not be expected to lose money when issuing insurance policies. The court has routinely recognized what the IRS and some industry pundits struggle to grasp… that captive insurance arrangements should not be expected to mirror typical commercial insurance to be legitimate. This is true as it relates to being in competition. It is also true as it relates to being subject to the law of large numbers.
As can be seen, low claims rates should not inevitably drive down captive premiums. This supposed standard of a sham captive misses the mark. With that said, the following is a list of characteristics of sham captives when considering claims rates and the pricing of policies:
–Premium pricing is not actuarially determined
–An actuary ignores sound modelling and knowingly (fraudulently) overprices policies