US CPAs to start speaking French

Until very recently, multinationals listed in the US but not resident in the US were required to show a reconciliaton of their local GAAP financial statements to the US GAAP equivalent. Many of these large companies (based in Europe and the Far East) incurred high costs in time, energy and hard cash in preparing US GAAP accounts for this purpose only.

As a result, listing on a US exchange started to appear less attractive to these and other new potential listings. The SEC had been mulling over how to deal with this for a while, and fairly suddenly has now announced that these companies do not need to provide the reconciliaton to US GAAP. As a result, many large companies have already opted not to produce the US GAAP figures.

The next major step would be if the SEC decides that US companies who decide to report under IFRS do not need to provide US GAAP figures. As IFRS gains traction around the rest of the world, nobody wants to be left behind as the special case. This is still a way off, and their is also plenty of trouble brewing with IFRS (Phase 2 Insurance Project particularly) but it does look like many US accountants will need to polish their European language skills.

Solvency II makes another milestone – QIS3 out

Apparently the results for QIS3 are now available.  QIS3 (“Quiz 3”) is the third Quantitative Impact Study along the path to rolling out Sovlency II for insurance companies between 2010 and 2012. It provides further light on what capital requirements will actually be when Sovlency II comes into effect.

Perhaps a warning is required for the overally optimistic. Basel II required 5 QISs before maturing to be ready for roll-out. Many acknowledge that Solvency II is more complicated, with a greater number of complex risks to consider so it could arguably take much longer. Also, Basel II had the framework of Basel I to start with, where many European insurers have had very simplistic capital requirements to date. Watch this space!

I’ll provide some more feedback on the actual results of Solvency II when I’ve had a look through the material.

Retirement age inequality

Iafrica has a story about a court battle against different state retirement ages.

Can’t imagine this will go far in the short-term, but might be the beginning of a serious relook at normal retirement age, for men and women, and in in light of trends of extended retirement periods through “mortality improvements”. Mortality improvement is the lowering of mortality over time as a result of several causes, including better medical care, awareness of the dangers of smoking etc.

A two-day hearing of a case brought by a group of men challenging the unequal provision of the state old age pension to men at 65 and to women at 60 will begin on Tuesday.

Fooled by the Black Swan

Is your organisation one black swan away from disaster? Are you taking hidden risks in the quest for success, and using hope as your only risk management tool?

Nassim Taleb’s books should be required reading for life

Nassim Taleb is one of my new favourite authors. I’m actually a little slow on the uptake here since I am currently reading his 2005 book “Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets.? meanwhile the New York Times has his current book “The Black Swan: The Impact of the Highly Improbable? on their best-seller list. I wholeheartedly recommend “Fooled by Randomness?, and fully expect that once I have read his current book I will be able to do the same for that.

Dumb luck is a large contributor to success in an uncertain world

Do you want the success of your organisation to be at the mercy of dumb luck?

Nassim Taleb’s writings resonate with me, because I agree with them. He just has an infinitely more entertaining (let alone more convincing) way of explaining his viewpoints. One of his major themes is how poor our understanding is of randomness. And he’s not talking about the “average joe? in the street. If anything, he is more scathing of those so-called experts of the financial markets who are made or broken largely by luck. The unlucky fall be the wayside not be heard from, whereas the lucky shout their own praises from the rooftops.

I am not going to go further into his arguments in this post – the book is worthwhile reading if you are interested. However, I do want to touch a theme introduced in Fooled, and further expounded upon (I assume) in “The Black Swan?.

At some stage, the sun is going to stop rising

In the not so distant past, it was assumed that all swans must be white. Every swan ever seen had been white. All the classical statistical inference would have attributed a 100% probability to all swans being white. Until the rather unfortunate discovery of a little place called Australia. Enter the Black Swan.

Don’t trust past experience blindly, and trust your intuition even less

In risk management terms (and when I talk about risk management I include managing an organisation in the face of uncertainty, which includes every organisation I have ever known), events that may seem extremely unlikely based on past information and experience may still happen. If the occurrence of a black swan for your organisation would be catastrophic, are you really prepared to just hope that the past experience to date accurately reflects the future?

Actuaries and risk management

“Actuaries only look at the past so they are Fooled by Randomness.” This is a superficial description of actuarial work. Without a doubt, actuaries look to the past to infer certain parameters about the future. I’m not convinced this is necessarily bad as long as one realises that the past is not all there is to the future. The impact of HIV/AIDS and annuitant mortality improvements are typical of areas where actuaries have recognised that the past does not reflect the future and attempt to adjust for this in their calculations. Actuaries have the unfortunate job of trying to accurately estimate what this unknown future scenario will look like, rather than recognising that the risks exists and managing it.

When it comes to managing potentially catastrophic risks, Mr Taleb’s preferred practice is to limit all risks no matter how unlikely they may seem. The good news here is that if the consensus view is that the risks are extremely unlikely, the costs of mitigating those risks (transferring, hedging, reinsuring, selling etc.) should be relatively low. Mr Taleb prefers to find ways to use past patterns to make a profit, but use a sophisticated paranoia when managing the risks. He goes further and aims to benefit from the occasional black swan that flies his way. Again, more of this in his very worthwhile reading books.

Understanding all these potential risks, and understanding the potential for financial or operational impact on your organisation is not easy. Some of the results can be counter-intuitive, and simply drilling through the analytical steps to get to practical, useful steps requires a combination of common sense, uncommon insight into risk, and a tool-set capable of meeting the problems head-on.

In general, the human mind is a pretty poor tool for understanding a probabilistic world and making good decisions in the face of uncertainty.

What makes a good decision?

As an aside, another element of Mr Taleb’s thinking that I read with a fervently nodding head is that in an uncertain world, decisions should not be evaluated based on the outcome, but rather on whether it was the right decision given the information available at the time the decision was made. This is also not to say that the outcome never provides any information about the quality of the decision, just that it usually doesn’t. For example, take the decision to call “heads? on the toss of a “fair? coin. If the coin dutifully lands heads up, does that make the decision a good decision? I would argue very strongly that it does not. A more difficult example to agree with is that of a fund manager selecting a particular stock. If it the share appreciates in value over some period, is that sufficient evidence to show that the “buy? call was a good one? Again, I would argue that it doesn’t. Especially when there is a large selection of fund managers making calls on all manner of stocks on a regular basis. Some of them have to be right some of the time. And a few of them will be right a great deal of the time just through luck.

Do you have a Black Swan?

Now if your organisation has a currency exposure, perhaps you are importing a component of your production process, or maybe your sales are partly to a foreign country, should you be bullish on the exchange rate? Should you be tring to time the market? Or should you be managing your risk by removing the areas of uncertainty over which you have no control, and where you are likely to be less informed than most professional currency traders, and where those self-same professional currency traders are playing in a massively uncertain world, where those with good “track records? are more likely to be lucky than skillful? What happens if the Black Swan of a sharp exchange rate depreciation (or appreciation) is enough to wipe our your year’s operational earnings?

“We can’t afford risk management”

A common response to the argument for risk management is that hedging (or reinsurance, or put options or credit guarantees or business interruption insurance) is expensive. As I alluded to before, if the risk really is that unlikely, the cost should be relatively low. If the cost is high, it may reflect that others have a more prudent view of the possibilities of those risks than you do, which should start the alarm bells ringing immediately. The other side is that do you really believe than an appropriate way to build and manage your organisation is to continually take a small but very real risk of a catastrophic risk in order to make additional profit? If that is the primary source of profit for your organisation, then the fundamentals of that business may need to be revisited. Selling far out of the money naked call options as an income source may never get you into trouble and yield a modest revenue stream. Very few would agree that this is a good long-term strategy for success. A good number of the few that do have already been burnt in the process.

So what now for understanding and managing risk?

So there are four major points I would like to conclude with:

  1. If you operate an organisation, you operate in an uncertain world and are exposed to risks

  2. Just because you have never seen a Black Swan, doesn’t mean you will never see one.

  3. If there is a risk that could severely damage your business (a Black Swan), you had better have a better risk management strategy than closing your eyes and hoping

  4. Identifying these risks, measuring them and understanding their impact on your business, and then understanding the options available to you in managing those risks is an important and non-trivial exercise.

Why premium size matters (more than you think)

Most people involved with insurance recognise that more premium is better (ceteris paribus of course). This is usually true (and occasionally not) but while some of the reasons are obvious, there are a variety of more subtle factors to take into account. This post will cover many of these factors, and point out a few cautionary tales around seeking large average premium size above all else.

When is value created?

For a particular product-type, it is usual for larger premiums to be more profitable than smaller premiums. By profitability here I mean the increase in shareholder wealth resulting from having sold that additional policy. The value creation at time of sale arises from:

  1. A customer relationship has been confirmed and cemented through an agreement to do business for a few months or many years. The customer relationship was already in the process of being developed in the period up to the sale (from broad advertising campaigns, brand-development, specific distribution channel contact and the quotation process). However, this is also true for any other industry, so we will restrict the analysis in this post to the “point of sale”.
  2. This customer relationship means that for short-term or annually renewable business, there is a non-zero probability of renewal, and this probability is likely to be higher than the probability of a random individual with no previous contact with the insurance company buying a new product under the same conditions.
  3. The costs of renewing an existing policy are usually lower than those of creating a new policy. (Policyholder and risk details are already captured on the system, the sales process is quicker, legal and regulatory compliance (for example, around identifying customers) is already complete and payment details / credit checks have been performed.
  4. For life insurance business, a long-term, legal contract has been entered into. Traditionally, these contracts can be cancelled at the option of the policyholder (usually with a fair and sometimes controversially unfair penalty). In spite of the cancellation option, signing a long-term contract provides some evidence that the policyholder has an intention to enter into a long-term agreement with the insurance company.

This list isn’t exhaustive, but it covers some important bases.

So why are larger premiums better?

Larger premiums are more profitable because:

  • Some marginal costs are fixed per policy
  • Larger policies are usually more persistent
  • Larger policies usually imply greater wealth, which usually means lower morality (check below for caveats!)
Some marginal costs are fixed per policy

Many actual marginal costs really are fixed per policy:

  • Policy form, posting, printing, filing etc.
  • Ongoing reporting and communication with the policyholder
  • Bank charges related to processing premium receipts and claim payments
  • Calls to the call centre
  • Valuation modelling costs (PC / Mainframe running time, purchase costs, electricity, coding, debugging)

Since the costs are fixed per policy, the greater absolute charges are matched against lower costs yielding a higher margin.

Larger policies are usually more persistent

No question this is subjective, but one only needs to consider the 25% – 50% first year lapse rates on low-income products with small sums assured and small premiums. Large policies are likely to be sold to educated consumers who are less likely to be hoodwinked by smooth-talking commission-driven salespersons.

One can understand logically how this could be true, and the data supports these conclusions as well.

Larger policies usually imply greater wealth, which usually means lower mortality

Fairly standard actuarial knowledge this. Higher income means better access to healthcare for current ailments. More importantly, high income now is strongly correlated with high income in the previous years, which implies consistently better access to good healthcare and thus better overall life expectancy. Moreover, higher income is correlated with higher education. Education is correlated with family having money, which is correlated with good healthcare since birth, which is positive for life expectancy. Certain diseases (particularly heart disease) are related to stress and high cholesterol, which are positively correlated with wealth and income and act in the opposite direction.

Lower mortality both means lower claims experience (for non-annuity risk products) but also means, very marginally, that persistency will be higher since dead policyholders don’t pay premiums. Since a portion of all premiums is earmarked for the repayment of initial expenses, the more premiums paid the higher the overall margin will be.

And what about the impact of discounted rates?

Absolutely right. Higher premiums often attract discount rates, including lower asset management fees, higher allocation rates and lower mortality charges. These cost elements shouldn’t be ignored in the analysis, but experience usually shows that the benefits outweigh these costs. Results may vary!

An element that is often forgotten is medical underwriting. Most underwriting manuals have limits below which certain components of the comprehensive underwriting process are omitted because they aren’t cost effective. Thus, for the largest policies, the underwriting cost are often the highest. Analysis of actual experience and the costs involved for this should provide reasonable estimates of this cost.

One final, even more subtle impact is that of statistical variation. Individual policyholders will die (and we are continuing with the focus on non-annuity risk products here) with a certain probability at each age. Thus, the overall distribution of the number of deaths in a year should follow a binomial distribution, ignoring catastrophes and the slight theoretical correlation between deaths of spouses. Since the number of deaths follows a binomial distribution, we can determine likely variation from the expected number of deaths using basic statistical methods. What this also shows us is that as the number of policyholders increases, so the percentage variation from the mean decreases due to the diversification benefit. I’m not going to go into the detail of this for now – those familiar with insurance should be comfortable so far.

So, ideally we want lots of policies. If we also want to hold the premium constant between two comparable companies (S and B) but where S has small premiums per policy and B has big premiums per policy, then S will have a greater number of policyholders than B and will experience less volatility in financial results through better diversification of risks. You can also think of this like every Rand (or Pound or Dollar or Euro) of benefit for a particular policyholder is perfectly correlated with every other unit of currency for that same policyholder. Either the policyholder lives and all units of currency don’t get paid, or the policyholder dies and every single unit of currency is paid out as the total Sum Assured. Thus, larger premiums make larger benefits make more correlation and less diversification. This slightly unusual way of looking at the problem is what most people are familiar with as concentration risk, except here we are considering concentration within individual policyholders. This increase in risk increases the economic capital required (and often the regulatory capital too) which will likely have a cost to be considered.

So large premiums matter

Most people involved in life insurance will intuitively feel that larger premiums are “better” or more profitable – here are some of the reasons why. Most of these reasons are familiar to actuaries, and if you give an actuary a little bit of time he or she will likely come up with these and some others as well. However, this article has focussed on premium size in the absence of other factors and incentives. I’ll post soon on an example of how the external environment can distort this natural operational conclusions.