Category Archives: Actuarial and Risk

Insurers dealing with regulatory change

Posted on by
Reply

Insurers around the world are dealing with increased regulations and increasingly nervous regulators, just waiting for the next crisis to see how insurers will cope. In South Africa, SAM presents opportunities and challenges and the potential for a great deal of expense with limited direct business benefits.

Of course, the regulations in some form or other are coming and are likely to stay. The Actuary magazine has an article on some of the lessons for insurers and regulators about how to actually get some control and understanding of macro and systematic risks within the new regulatory models.

NBMR – still relevant

Posted on by
Reply

With several life insurers reporting financial results, including horribly broken measures of new business profitability such as VNB margin or VNB / PVFNBP, it feels like time to roll out New Business Margin on Revenue again and describe why it is a much better measure.

It is a good time, but I don’t currently have the time. I’m going to try to prepare a basic spreadsheet example to make it clearer. I’ve also decided on a provisional treatment of pure financial instruments that I hope will give useful results.

Watch this space.

What is best practice for matching annuities in Greece in 2012?

Posted on by
Reply

Best practice for matching non-profit annuities in most countries, certainly from a risk perspective, is still to cash flow match (or at the very least, match key durations) using government bonds.

The theory is that the insurer isn’t then exposed to changes in the term structure on interest rates, only exposed to illiqudity/reinvestment risk to the extent of mortality fluctuations, isn’t exposed to currency risk and certainly isn’t exposed to credit risk. Without complex margining requirements like some swaps and without the need to roll cash investments over, government bonds should allow ALM teams to sleep well.

Now, Solvency II is likely to adopt a swap yield curve rather than bond yield curve. There are some good reasons here, including arguably fewer distortions from temporary supply and demand imbalances, improved liquidity and so on. The same yield curve is used for liquid liabilities so the allowance for an illiquidity premium over and above the swap curve at some times, in some ways and for some products is still under debate.

But what should Greek insurers do in the meantime?

Frankly, Greek government bonds don’t remove credit risk and the huge credit spreads on these instruments will create huge funding gaps and variability in earnings unless a Greek govi yield curve is used to value liabilities as well. It’s not clear at all that Greece will stay part of the Euro, so German government bonds don’t remove currency risk. German government bonds in any case are show signs of nervousness as yields creep up.

The swap market is exposed to the same Euro break-up risks as bonds. Which banks will survive, what happens to currencies in the meantime and what does that do to long-term Euro swaps? What about Euro-Sterling swaps issued by Greek banks (I’m not sure if these even exist though).

All in all, it’s good to be involved in ALM in South Africa, and even the Middle East just at the moment.

Nearer the edge than ever before

Posted on by
Reply

Great piece outlining the very real, very possible and very very awful possibilities and implications of Italian default.

I wouldn’t want anything to do with any bank that has much at all to do with European banks or European sovereign debt. The old South African Rand is seeming like a safer relative bet than at pretty much any other time in the last decade.

JPBIBNR – Just Plain Bad Incurred But Not Reported

Posted on by
Reply

Nigerian GAAP, soon to be replaced by IFRS at least in the financial services sector, requires IBNR liabilities to be set equal to 10% of the Outstanding Claims Reserve. This is a terrible estimate of IBNR and there really are other, also very simple, better measures available.

As an aside, the use of IFRS balance sheet figures for regulatory reporting is also an unusual idea. There is no particular reason to believe that a shareholder financial reporting basis is appropriate as a regulatory measure. It can be, with specific capital rules perhaps, but it’s not automatically so.

Why the 10% of OCR rule for IBNR liabilities is so bad:

  1. For very long-tailed business with no or low claims reported in the first year, the IBNR will be massively understated
  2. as claims are reported (and before they are paid), the OCR will increase. The IBNR should decrease as the claims have now been reported, but given the 10% rule it will actually increase.
  3. The reconciliation of opening to closing IBNR and the comparison of actual vs expected IBNR claims over time is not useful since there are no explicit expectations built into the methodology
  4. Clearly the method is not sensitive to risks and delays of product lines or processes.

So what’s better? Well aside from the range of standard but fairly complex techniques (including Ultimate Loss methods, Basic Chain Ladder, Bornhuetter-Fergusson, Average Cost Per Claim and a whole range of stochastic methods) there are better simpler measures.

A starting point, although also very far from ideal, is the current (soon to be changed) South African statutory requirement of 7% of net written premiums. It also isn’t sensitive to different delay patterns and will give poor results if net written premium is growing or shrinking rapidly.

Really, the ideal simplification requires a little more complexity, but as a reward for this effort is a far more robust, more accurate measure that behaves sensibly in a far wider set of scenarios.

For each line of business for each delay year, we use a specified percentage of gross earned premium for the gross IBNR. Reinsurers’ share can be calculated similarly. The information relating to earned premium per line of business going back several years should be trivial to obtain and ensures we get a sensible pattern taking into account the growth in the business, the mix of business as well as change in mix of business. The method works well for start-up, mature or declining books.

The fundamental drawback of not reflecting a particular insurer’s patterns remains, but aside from using actual delay data this is about as good as one can hope for.

Frankly, why more regulators don’t prescribe this method is a mystery. The information is available, it’s trivial to calculate and verify and the results are robust.

Somehow, somewhere

Posted on by
Reply

National Treasury is mulling Deposit Insurance with an explicit charge on the banks.

This is not a new idea, and has historically been resisted by the major banks since they feel, generally rightly, that they are less likely to have a problem of confidence and therefore less likely to benefit from deposit insurance. Smaller banks, on the other hand, are certainly more at risk of a run on the bank arising due to perceptions thus causing a liquidity problem when a solvency problem doesn’t exist.

Determining the appropriate mechanism to charge for deposit insurance is not straightforward. Clearly the charge can’t be the same fixed amount for all banks as the exposure will be very different between banks. The large banks would lobby hard to pay a lower rate (even if a higher overall amount) for the insurance given that they should be less subject to those confidence issues.

But how to determine that difference? One could take cue from the market by looking at credit ratings and, even more market-oriented, the spreads on debt issued by the banks. Three immediate problems come to mind:

  1. Credit quality of long-term debt isn’t the same as protection for depositors
  2. Probability of default is an input into confidence issues but certainly isn’t the entire story
  3. Does anybody seriously still believe in the Efficient Market Hypothesis and trust that we can believe what the market offers as an impartial, objective and balanced view of reality?

So there are some fascinating technical problems to solve when implementing deposit insurance, not least of which is deciding how much gets protected.

What caught my eye was Moneyweb columnist, Phakamisa Ndzamela, demonstrating his disbelief at how deposit insurance could create a moral hazard and ultimately increase risk within the banking system.

some senior bank executives have cautioned that this could push the cost of banking higher and somehow encourage risky lending. [emphasis added]

Obviously Ndzamela hasn’t heard of the Savings and Loan crisis in the US in the 1980s, or, I don’t know, the Global Financial Crisis that we are still in, which was massively exacerbated (if perhaps not quite caused) through risk being accepted without due care because it was being passed off immediately to someone else.

Why S&P downgraded

Posted on by
Reply

I don’t think many serious investors care that S&P downgraded US debt. Bond yields are down (more on this in my next post), which means prices are up. US stocks are down, but that’s more about concerns about US and global economic prospects than the credit of the US government.

Nevertheless, S&P did downgrade. Why? I don’t think it is primarily to do with a materially increased estimated probability of default. It has more to do with a change in the payoffs in a ‘game’ (as in game theory) S&P is playíng.

Consider the quadrant of options. S&P downgrades or doesn’t and the US defaults or doesn’t. I’ve constructed totally hypothetically, but perhaps plausible scenarios below, for the S&P’s potential assessment of losses under each possibility given their views and external perceptions of them before and after 2008.

Before 2008, the fallout that would come from downgrading the US and the US not defaulting would be significant and cries of “un-American” might be heard again. Even if the US were downgraded, default would still be a blow for S&P since anything above a BBB rating really shouldn’t ever default if there models are “correct”. I’ve thrown in another hypothetical, a 0.01% probability of default – in other words very low, and as you’ll see in the next scenario, not necessarily higher now for S&P to change their view.

Now, either on a traditional minimax (minimizing the maximum cost) or an expected value basis, before 20008 S&P wouldn’t downgrade the US. This is an important calibration, since S&P didn’t downgrade the US.

After 2008, even if we leave the assessed probability of default unchanged, the world is different and therefore we have different costs.  If S&P doesn’t downgrade the US – even if the US doesn’t default, there will be a cost to S&P since might share the view that the US could default now. The dent in credibility since 2008 means that S&P has to try harder to convince the skeptics that they don’t rate risky instruments as AAA. Along with this goes a massive hit if the US does default and S&P hasn’t downgraded the US. The good news is that at least now a downgrade is viewed more with more understanding even if the US doesn’t default (although be sure Obama’s White House is not happy at the moment).

After 2008, even if the assessed probability of default is unchanged, the minimax and expected value rules both suggested a downgrade is the better option for S&P.

Before 2008

 Don’t downgrade

 Downgrade

 PD

0.0001
Default

-500.0

-50.0
No Default

0.0

-1,000.0
Expected

-0.1

-999.9
After 2008

 Don’t downgrade

 Downgrade

 PD

0.0001
Default

-10,000.0

-50.0
No Default

-10.0

-10.0
Expected

-11.0

-10.0

Now the example is contrived – I chose a set of parameters that demonstrates the point I’m trying to make. This isn’t a problem since I’m not saying this is what happened. I‘m saying it is plausible that S&P made a perfectly rationale (for them) decision to downgrade even if they didn’t think the US was more likely to default now than before.

In truth, the US might be more likely to default now than before, although the change is probability not sufficient on its own to merit a downgrade at this point. Especially since S&P have their maths wrong.