Category: Actuarial

Categories
Actuarial

Don’t count your chickens

Take reports of changed pension deficits with large amounts of salt. It’s always important to put news in context, and to think about what’s going on underneath, especially when you read a story based on a survey or report produced by a consultant. And yes, I am a consultant, and that applies to surveys or reports I put out, too.

In yesterday’s FT there was a piece (£) about the pensions funding position. Apparently it hasn’t changed much since December 2010,

partly because the gap between yields on government bonds and those on corporate bonds has widened, which has the effect of reducing liabilities.

No it doesn’t. Absolutely not. The liabilities have not changed an iota because of any change in bond yields. The pension schemes are still on the line for the same payments in the future as they were. The only thing that has changed is one estimate of the present value of the liabilities, in other words how much money should be set aside now to pay the liabilities in the future.

But let’s get this straight. Nobody knows how much the pension schemes will have to pay out in the future. It depends on all sorts of things — including how long the pensioners live, what survivors they leave when they die, what future inflation rates are, whether members of the scheme transfer out before starting to draw their pension, what options they exercise when they do start, and countless others. And that’s without even considering what can happen to active members (those still in employment). So the actual payments out are uncertain.

And the payments in are uncertain too — investment returns, employer contributions, member contributions.

It’s fairly easy, nowadays, to estimate the value of the assets — just use the market value. Which is of course highly volatile, especially in the short to medium term.

It’s much less easy to estimate the value of the liabilities. You project the likely future payments, and then use a discount rate to come up with a present value. Which could be volatile too, as well as uncertain, if the discount rate you use is volatile.

So the deficit (or surplus) is the difference between two large numbers, at least one of which is highly volatile and the other is highly uncertain. No change that occurs over just a few months can be really significant, if nothing else has changed.

Just apply some common sense. If the assets are the same assets (no big changes in investments), and the liabilities are the same liabilities (no big changes in membership or benefits), then the long term position simply can’t have changed significantly. Pensions is a long term business. Transient changes in estimated current values are bound to happen, but in the end what matters is that the benefits are paid out when they fall due.

Categories
Actuarial Data

The new modelling

Data is the new modelling. That is, it’s where all the sexy stuff is going to be over the next few years. Over the last few years, in the insurance industry at least, modelling has been where its at. Driven largely by Solvency II, a huge amount of effort has gone into building and, now, validating, hugely complex financial models.

But now, in the insurance industry as well as others, data is coming to the fore. After all, what is a model without data? And, as we all know, Garbage In, Garbage Out is one of the fundamental tenets of computing. The FSA has pointed out that data is a key area for the successful introduction of Solvency II and has produced a scoping tool that will help them assess a firm’s data management processes.

And it’s not only Solvency II. At GIRO last week there was an interesting debate over whether telematics will be at the heart of personal motor insurance in ten years’ time. The thing about telematics is that it produces large quantities of data. With the Test Achats case meaning that gender won’t be able to be used as a rating factor, insurers are going to be looking for other ways of coming up with premiums, and other factors they can take into account. The thing about gender, of course, is that it doesn’t take much data. It’s just a single bit in the database. Other rating factors may have more predictive power, but it’s harder to get at them.

We’re seeing this everywhere, though. As computers continue to get more powerful, and data storage gets ever cheaper (how big is the disk drive on your laptop? — even my phone has 16GB), doing things the rough and ready way with only limited data has fewer and fewer advantages. Big data is becoming mainstream: look at Google, for instance. And why did HP buy Autonomy?

You mark my words, a change is gonna come.

Categories
Actuarial Uncertainty

Getting rates in a mess

Another good blog post from Understanding Uncertainty: for once not based on a howler from the British press. Instead, it’s based on a howler from the German press – High suicide rate in German forces serving abroad – every fifth soldier takes his own life. They actually meant to say one in five of deaths among soldiers serving abroad.

The post goes on to discuss whether the suicide rate is higher or lower than would be expected, and along the way gives some explanations of the concepts behind exposed to risk (without actually using the term). A great example of how to explain something that can get pretty technical in an uncomplicated way. If only most actuaries could do the same.