Category Archives: Actuaries

Actuaries in the crosshairs

A more diligent blogger than I would have posted about the Society of Actuaries study that predicted a 32% increase in claims costs on individual health policies, thanks to Obamacare. But I never found time to read the report, so I really had nothing to add.

Today, the pushback comes from Politico and Kaiser Health News and a funnyman-turned-Senator:

“Most actuaries in this country — what percentage are employed by insurance companies?” Sen. Al Franken, a Minnesota Democrat, asked an actuary last week at a hearing of the Committee on Health, Education, Labor and Pensions.

The upshot – actuaries work for insurance companies, or consult for insurers, so they can’t be trusted. Moreover,

… Actuaries are self-regulated, which some say makes them unaccountable.

Their associations set conduct standards and investigate malpractice in confidential proceedings. During the previous two decades the Actuarial Board for Counseling and Discipline, which works with the Society of Actuaries, has recommended public disciplinary measures for fewer than two people a year, according to its annual report.

Yet actuaries play many public roles. By calculating the adequacy of employer pension contributions they affect the retirement of millions. And they’ll act as virtual referees for important aspects of implementing the health act.

“I have a great deal of respect for actuaries,” said Timothy Jost, a law professor at Washington and Lee University and health law expert. “But I do think they often end up in … situations where the interests of the public and of their employers might be in conflict.”

Now, I still haven’t read the SOA study, so I still can’t comment on it. I suspect its estimate is too high, but without reading it, I’m not going to impugn the study or its authors.

That’s where I differ from Franken, et al. Maybe they’ve read the study, maybe they haven’t. But they aren’t criticizing the study. They are criticizing the messengers. Theirs is a classic ad hominem attack and should be condemned.



SOA’s international outreach

I’m a little slow noting this, but SOA President Bradley Smith blogged about the proposal to add a property-casualty track this week.

He asserts fairly clearly that the move is pointed at international concerns:

For us to meet the needs of our growing member and candidate base outside the U.S. and Canada, we must offer this educational option. After all, it’s our job to ensure that our education system is equipping actuaries with the skills to address the full spectrum of risk management issues.

It’s a good point. In the U.S. there aren’t many insurers with both life and p/c operations. (And one of the last – The Hartford – wants to split theirs.) But it’s a common business model in the rest of the world, as a glance through this list of the top 25 shows.

There’s some logic that an actuary in, say, Europe, might want both life and general insurance backgrounds. But despite the hubbub, I’ve seen nothing from either the CAS or the SOA that explicitly denies they are now in competition.

But Smith did post this:

Currently the SOA is the only actuarial education organization with a significant international presence that does not offer education in the full range of practice areas.

The word choice isn’t accidental. It also appears in this Q&A.

But I can think of an actuarial organization that doesn’t offer a credential for life or health practices, but according to this list does administer exams in 24 countries.

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More on the SOA’s P/C track

With the Society of Actuaries planning to launch a casualty track, the CAS responds:

The CAS Board affirms that it is the intention of the CAS to remain independent while at the same time cooperating with other actuarial organizations to meet challenges to the profession.

There’s more at the link, noting that the CAS:

  • is “uniquely positioned to provide the most comprehensive and rigorous education in actuarial science and risk management for general insurance actuaries.”
  • has a singular focus on property/casualty insurance issues.
  • will maintain its singular focus on property/casualty insurance.

Meanwhile, the actuary blogging at Feed on my Links yawns:

These organizations already collborate on exams, so it’s not like the SOA is going to weaken the examination gates and let all the ‘rif-raff’ in. . . .

So it’s all about passing hard exams. Pedants will no doubt quibble about curriculum minutiae or “which one is harder”, but the bottom line is that nobody cares enough about this to spend the time wondering which designation to puruse. My prediction is that the SOA’s initiative will either merge with the ACAS or fizzle out.

I see a different path:

  • SOA offers a general insurance specialty track.
  • The new track gets recognized by international actuarial organizations, like the FSA. And why wouldn’t they recognize it? The mix of life/pension/health/property-casualty looks more like a European fellow than an FCAS does.
  • The SOA tries to get its track recognized for signing U.S. p/c opinions. There could be two paths:
    • It applies through the AAA’s Casualty Practice Council.
    • It seeks recognition from the CAS.
    • Either way, I think the SOA designation gets recognized. I doubt it would get turned down. If it did, the SOA can accuse either counterparty with restraint of trade. And look at the evidence it would have. The CAS recognizes, say, the FSA. And the FSA recognizes the casualty track of the SOA. What possible reason could the CAS have for not recognizing the SOA, except restraint of trade?
  • Once SOA actuaries can sign p/c opinions, the SOA is in a much stronger position to call for a merger.

Mind you, I’m not commenting on whether the SOA should do this. I just think it’s likely once the chain of events begins. And I think Wednesday’s announcement starts the chain.

The goal: merger with the SOA. The CAS rejected a recent offer, but this SOA release Wednesday reiterates that the society’s Consolidation Task Force “remains in place to continue its efforts as needed.”

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Does bootstrapping understate reserve variability?

Over at Guy Carpenter land, actuary Jessica Leong posits that the bootstrapping method of estimating reserve variability understates that variability.

Bootstrapping, of course, is a method of using the company’s own data to drive a random sampling process; said process re-estimates the reserve. Sample enough times, keep track of the results, and you’ve got a distribution of results. (Better descriptions are here.)

But the method doesn’t seem to work as advertised.

Leong uses company Schedule P homeowners data. Schedule P gives a triangle of paid losses and also ultimate losses. And homeowners has a short tail but produces 10 years of results. The result 10 years out is an excellent estimate of ultimate.

So you have an a priori distribution of losses. And you know, 10 years out, what the actual losses turned out to be. So you can pinpoint where in your original distribution the actual losses came in. In her post, Leong walks through an example, which happens to come in at the 91st percentile.

If you did this across a bunch of companies, across a bunch of years, the actual losses should occur uniformly, at least if bootstrapping works as advertised. So 10% of outcomes would fall within the bottom tenth percentile, another 10% would fall within the top tenth percentile, and so on.

The actual results are here:

The chart shows that

.  .  . around 20 percent of the time, the actual reserve is above the 90th percentile of the bootstrapped distribution, and 30 percent of the time the actual reserve is below the 10th percentile of the distribution.

When you tell management the 90th percentile of your reserves, this is a number they expect to be above 10 percent of the time. In reality, we find that companies have exceeded this number  20 percent of the time. The bootstrap model is under-estimating the probability of extreme reserve movements, by a factor that is clearly material for the purposes of capital modelling and therefore Solvency II.

Hers is the first post in a series to play out over the coming days. In the meantime, I’m a bit curious:

  • Do the outliers have much in common with each other? Are they smaller companies or larger ones?
  • The study works from net data. Would you get the same results gross of reinsurance? Schedule P triangles are net of reinsurance, of course, but you can construct a gross triangle from successive annual statements. Net triangles could be skewed by the presence of reinsurance, especially excessive of loss or catastrophe cover.
  • Does the data set include reinsurers? Reinsurers don’t always receive – and rarely record – losses by accident year. Usually everything is recorded on an underwriting year. So the accident year loss payments and ultimates in Schedule P homeowners are estimates arrived at by allocating underwriting results across accident years. And, believe me, the allocation can be shot full of holes.
  • Do other lines of business exhibit the same phenomena? Homeowners is short-tailed, but the presence of catastrophes skews development and results. Would you see the same phenomenon in, say, private passenger auto?
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Actuarial estimate on civil unions

Not often actuaries get involved in the gay marriage debate, but here’s a snip from an editorial in my old hometown’s newspaper:

The more “explanations” we hear about a city committee’s decision to not provide dependent health insurance for employees in civil unions, the more ridiculous this situation becomes.

First the Joint Labor/Management Health Care Committee accepted at face value a laughable actuarial estimate that put the cost of providing insurance to civil union partners somewhere near the cost of providing free daily helicopter valet service to those employees. This despite the fact that not a single city employee at the moment has asked for civil union benefits.

Then the actuary himself explained the reason for estimating it would cost $725,000 for the city to comply with the state civil union law. Offering this benefit, wrote Ray Martin of the St. Louis firm MarAcon LLC, would invite a flood of new claims, as unmarried same- and opposite-sex couples rushed into civil unions to get cheap insurance. He estimated offering the benefit would lead to 65 civil union couples joining the city self-insurance program. (Sangamon County issued 106 civil union licenses in 2011.)

Of course, I haven’t seen Mr. Martin’s work product, so I don’t know if this opinion piece characterizes it accurately.


Fortune favors an actuary

Via Claire Wilkinson at the III blog, a young actuary makes good. Really good:

As I was sitting in the doctor’s waiting room the other day leafing through the latest issue of Fortune magazine, I couldn’t help but notice Fortune’s 40 under 40.

This annual ranking highlights the hottest young stars in business across the globe. Think technology – Facebook’s Mark Zuckerberg tops the list, while Twitter’s Jack Dorsey is ranked eighth – movies, music, athletic wear, oh, and finance.

Coming in at number 10 and leaping off the page to this insurance blogger is 34-year-old Sid Sankaran, chief risk officer at AIG.

Here’s what Fortune has to say:

The financial crisis proved that AIG had no clothes – or at least no controls. Now it’s up to Sankaran, a Canadian math hotshot (his degree from the University of Waterloo was in actuarial sciences) and former partner at consultancy Oliver Wyman, to make sure it doesn’t happen again. Sankaran declined AIG at first; today, as chief risk officer, he oversees the billions flowing among disparate insurance operations and reports to CEO Robert Benmosche if something suspicious rears its head.”

Chief risk officer is the capstone job in enterprise risk management and is perfect for an actuary with strong interpersonal skills.

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Why health insurance subsidizes the elderly

Over at the Speaking of Actuaries blog, SOA President Brad Miller puzzles over why Obamacare has younger buyers subsidizing older ones:

I discussed this with someone who works on Capitol Hill. I told him I understood the criteria for the first three but was struggling to understand the reason for the young to old age subsidy. Was Congress and the president trying to emulate the group insurance market? Were they making a statement about the appropriateness of age-based pricing? The person just looked at me and smiled. He said, “Brad, you are such an actuary. You try to impute logic where there is none. There is one reason and one reason alone for the 3 to 1 limit that subsidizes the old at the expense of the young.” I said, “OK, what is the reason?” He said, “It is the price that AARP (American Association of Retired Persons) extracted for their support of the bill.”

“It is the price AARP extracted to support the bill.” Totally non-actuarial. Totally political. Old people vote, young people don’t. If you are under age 35 this should make you pay particular attention.

I think Brad and the aide have set up AARP as a straw man here. There are political considerations to any bill (er, that’s politics), but there are sound public policy reasons for the subsidy. Health insurance is unbelievably expensive if you are over 50. $10,000 a year for a healthy couple is not out of the question.

For many people, that makes it unaffordable in the same way it would be unaffordable for a young, poor person. If you require someone to buy insurance, but they can’t afford to, you haven’t solved a problem. You’ve just created a new class of criminal.

Also, they may be focusing on the current concept of health insurance as a one-year policy. However, the individual mandate – assuming it remains in the law – turns health insurance into a lifelong purchase for every consumer. This makes a bit of sense, since health insurance is a lifelong need.

In that circumstance, it’s not inappropriate to charge a customer more in the early years of coverage and less in later years. I’m pretty sure you can buy a term-life policy that works this way.

Another way to look at it: The young person will probably become old, so they will move from subsidizing to receiving the subsidy

Brad’s larger point is on target, though: Actuaries tend to see actuarial considerations when addressing problems. But there are other ways, and they are equally valid.

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Supply and demand in p/c insurance

Always good when someone shores up the ranks of blogging actuaries, so welcome to Todd Bault! I guess he’s been posting awhile, but I seemed to have missed his earlier work.

Todd is well-known in the actuarial community for being one of the leading insurance industry analysts, and he’s posting as part of the lineup at Sector & Sovereign Research’s blog.

Todd’s advancing a controversial idea – that insurance capital is not the ‘supply’ in the industry’s supply/demand equations. Controversial because most people will tell you that the price of insurance varies inversely with the amount of capital in the industry.

When insurers have lots of capital, the thinking goes, they are eager to write lots of business. Hence the price of insurance goes down. When capital is scarce – think of the losses from the World Trade Center paired with a loss of capital from the bursting of the dot-com bubble – prices rise.

But Todd doesn’t subscribe to that theory, and his recent posts – here, here and here – suggest that exposure is actually what drives the insurance industry’s supply curve.

To summarize his thinking: Loss trends would drive accident year loss ratios ever higher, except for rate change (and catastrophes, which he accounts for). So if you back out loss trends, any year-to-year movement in loss ratios will reflect rate changes. Then he notes that premium growth = exposure growth * rate change.

Having estimated rate change and exposure change, he graphs one against the other:

To prove this is difficult. At the macro level, data is thin, so his analysis is driven by the kind of squinting you do when you look out the window of a plane at 30,000 feet – you can’t make out much in detail. But since you are operating at a high level, imperfect information will generally be good enough.

So his key assumption – that change in CPI serves as a good proxy for loss trend – will seem outrageous to most actuaries. Essentially he implies that claim frequency doesn’t change over time (though it has). But given his data limitations, it’s reasonable.

And he has what looks like a nice supply curve mapping data from 1980 to 2010:

As you can see, this graph has the “right” relationship: a downward-sloping line reflecting the negative correlation one would expect for supply & demand.  It’s not a 95% R-squared, but I wouldn’t expect it to be.  It just has the expected relationship, without any other unnecessary assumptions.

It would even slope downward if it were modeled the way most economists do – measuring price vs supply with price on the y-axis (instead of change in price vs. change in supply with price on the x-axis).

But I think the negative correlation is an inevitable result of the formula used to calculate exposure growth

premium growth = price change * exposure growth

The formula, I think, requires price and exposure to be negatively correlated. For example, if premium didn’t grow, premium growth would be a constant of 1.00. If price change was positive, exposure change would necessarily be negative, and vice versa.

Of course, premium growth isn’t zero. It follows GDP over the long term. Nominal annual GDP growth from 1980 to 2010 is about 5%, so absent any data, we’d expect an exhibit like the one above to be a negatively sloped line with a y intercept around 5%, which it is.

I don’t think this means the underlying analysis is wrong, just that the negative correlation isn’t as meaningful as portrayed.


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Insolvency: What was the actuary’s role?

Time Flies Department: The Reliance Insurance insolvency turned 10 this year, and Best’s Review (sub. req., I think) was all over it.

Reliance was one of three big insurers that went under in a 10-month span ending in March 2002, the others being Legion Insurance and Phico. The accompanying chart, which ranks the largest insolvencies by the net amount they drew from state guaranty funds, gives you some idea how big a mess the three left behind. Continue reading

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