#22 | Portfolio Crediting Physics

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Everyone knows that the probability of a life insurance policy performing exactly as illustrated is zero – and rightfully so. A life insurance illustration is meant to show the interaction of policy inputs (premiums and interest credits) against policy charges. Its accuracy is a direct function of the quality of the assumptions used in the model and all three factors are prone to error. Policyholders miss premiums, pay late, take unscheduled distributions or completely forget to even keep an eye on the policy thanks to lax administration from their agent. Policy charges can and will change. But it’s next to impossible to predict with any certainty how an individual policyholder will behave or which policies will experience an increase in charges.

Crediting rates, on the other hand, are a bit more straightforward. I wrote extensively about the mechanics and impact of new money and portfolio crediting methodologies in a previous post. But I’ve realized since then that I left a key question out of my comments – can we take a carrier’s current crediting rate as a reasonable estimation of future returns? Or, put more precisely, what’s the right rate to show on a CAUL/IUL illustration?

Portfolio crediting makes these questions extremely difficult to answer because crediting rates are almost always different than the yield on the carrier’s new money assets. Portfolio crediting creates momentary suspensions in the physics of invested asset returns. If I showed you a picture of a ball at its zenith and then tried to sell you on the idea that I had created a magical levitating ball as evidenced by the picture, you’d probably walk away. But if I showed you a premium estimation hinging on a crediting rate in excess of new money returns and used the illustration as evidence, would you still walk away? Too often, I think, we forget that the physics are similar. What goes up must come down. Portfolio rates can only differ from market rates because old money is blended with new money. Interest rates have been falling for the last thirty years and that’s directly responsible for pushing portfolio rates, whether in the form of dividends or UL crediting rates/IUL options budgets, above market returns. Not approximately responsible – directly responsible.

Carriers would love to tell you otherwise. They’d love to tell you that their prowess as kept their crediting rates above the benchmarks. And some agents would love to believe that story because it allows for life insurance to be sold as a means for performance rather than protection. The evidence, however, is not as neat as the narrative. An agent recently sent me a copy of Northwestern Mutual’s dividend history spanning back to 1872. I matched that data against the best fit I could find, the Moody’s AAA bond index, which only goes back to 1919. Obviously dividends have other components, primarily mortality and expense pricing, but they’re the best long-term historical proxy for crediting rates. And if anything, they overstate returns compared to UL crediting rates for a variety of reasons. The graph is below.

The story this analysis seems to be telling is highly intuitive. When interest rates are falling, portfolio crediting will beat the market rate. Vice versa when interest rates are rising. Over time, the returns are approximately equal. In this respect, I’d probably argue that portfolio crediting serves as away to compensate for unrealized capital gains and losses associated with the general account assets. The story that life insurance companies can generate returns in excess of the correct risk-adjusted benchmark over periods of time that span macro rate cycles is, at best, extremely optimistic. At worst, it’s misleading.

But, of course, it’s quite useful in illustrations. Life insurance is currently being positioned as an escape for low interest rates. That may be true in the short term, but only if you exclude policy charges (which basically require long-term thinking thanks to high early loads). But it’s certainly not true in the long run. Indexed UL products have especially benefited from the market rate/portfolio rate mismatch because the primary pricing component in capped equity options is interest rates. In other words, options are priced to market rates and portfolio crediting creates temporary leverage above the market rate that allows the carrier to buy higher upside than if market rates matched portfolio rates. For example, an options budget of 5% can purchase a 12% cap in a 0.18% short term interest rate environment. In a 5% short term interest rate environment, a budget of 5% could only purchase a 9.25% cap (holding all else constant). So to a large degree, current caps are subsidized by the mismatch between portfolio and market rates. This leverage will obviously invert with the same magnitude when market rates go up and portfolio rates lag. If the options budget is 5% but market rates are 7%, the affordable cap drops to a paltry 8.25%.

So what’s the application for all of this? I’ve definitely changed the way I run and explain illustrations with nonguaranteed elements. I run CAUL illustrations at several crediting rates scaling down from the current rate and always use something less than the current rate to estimate the premium. If rates go up, the client can stop paying early. If rates drop, the policy funding will provide a buffer. On IUL, I assume that caps will settle in the 9-10% range for products with 0% floors and lower for products with floors above 0%. That, of course, leads to lower rates than most carriers are currently allowing regardless of your assumption for equity returns.

I have no doubt that some people will say that I’m being overly conservative and that this approach would stymie sales. That might be true, but any sale that would happen assuming current rates but wouldn’t happen assuming lower rates probably shouldn’t happen at all. Clients have no idea what the “right” premium, crediting rate or cap is. Being conservative is a way to systematically underpromise and overdeliver. Everyone knows that illustrations are wrong. The only question is the direction and magnitude of the error. Being conservative creates many more positive scenarios than negative ones.

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