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.

New Business Margin, which is the Value of New Business (VNB) as a percentage of the Present Value of New Business Premiums (PVNBP) is a common measure of profitability of that news business.

But it’s a flawed measure, especially when it comes to comparing product lines and insurers or even to understand the change in profitability from one period to the next. It uses and unequal yardstick to measure business.

New Business Margin on Revenue (NBMR) provides a significantly improved measure of profitability that can be used to compare margins across products, across insurers and across time. Further, it leads easily to a component analysis of the margin, adding additional insights to shareholders, brokers and regulators.

If you haven’t read my introductory post on New Business Margin on Revenue, it would be worthwhile doing so now – this post is going to illustrate the sort of results it provides in a practical, numerical example.

Example 1 considers how NBMR clarifies distortions from a change in mix of business.

Example 2 shows how more complex dynamics can be understood through a component analysis of NBMR. The spreadsheet showing the underlying calcs is attached at the end of this post.

Example 1 – A change in mix of business

AGGREGATE PICTURE

Let’s look at the sort of aggregate information you’ll typically see in an EV report.

What one might take from this analysis is that VNB is constant, but margins are declining to below 2.0%. If this is the only information on which to base our analysis, this company might be a clear “sell” and products and pricing need to be updated by management.

Let’s see how this would look using NBMR

From this table we see again that VNB has been constant, but that the profitability of the business has actually been slightly increasing.  So, although we should consider attending to the zero-growth VNB, the actual margin we’re achieving on our business on this measure has improved slightly from 25.5% to 26.1%.

This is a more accurate picture, because as you can see from the following tables, all that has changed is our mix of business – and the investment business that we’re writing more of now actually has a higher NBMR than the risk business we’re selling less of.  The traditional New Business Margin measure is distorted because it treats the entire premium paid by the policyholder as “revenue” when in fact only a small share of it is fees and charges and the rest is more like a deposit.  Again, banks measure profitability and performance through RoE, Cost to Income Ratios and Net Interest Rate Margin and only very much behind those the return on total assets.

Analysis of NBMR and components via product line

So the New Business Margin is constant on a product view, but when compared it appears as if there is a declining trend.  Also, at 26.7% of revenue taken as profit for investment business, this is profitable business, a fact not obvious from the superficially low New Business Margin of 1.3% (which is actually a perfectly good profit margin on that measure, just difficult to understand and compare).

The Revenue Per Premium (RPP) is 100% for risk business and 5% for investment business.  Depending on policy size, a 5% deduction from every premium might be a little on the high side and from a Treating Customers Fairly and sustainability perspective, this area may require some attention.  It’s also fair to ask “why are we losing market share in risk products and what can be done about it”, but at least we see this as a mix of business and market share issue and not a business margin issue.

Example 2 – Complex changes in volume, profitability and other components

Aggregate picture

Example 2 is more complex.  Let’s look at the aggregate information on a traditional presentation first.

In this case it looks like we have a severe margin squeeze problem in spite of increased business volumes and increased VNB. By now it should be clear that it’s dangerous drawing conclusions from this information.

A more coherent aggregate view can be obtained using NBMR:

Here we see a strong 2011 increase in all of VNB, Business Volumes and New Business Margin on Revenue after a poor year in 2010.  On the whole, we are hanging to customers longer than before (Discounted Premium Term or DPT up form 5.4 in 2010 to 5.6 in 2011, but still not at the levels of 2009. This is worth investigating.

The share of each premium we get as revenue has dropped sharply – clearly suggesting a change in mix of business as this sort of change wouldn’t typically be seen otherwise. Clearly we need to dig further, but the previously bleak picture is already looking better – and as we’ll see this is a more accurate reflection of business reality.

ANALYSIS OF NBMR AND COMPONENTS VIA PRODUCT LINE

Immediately we see a huge amount of new information.  Risk business has been declining in profitability significantly and has also had a dramatic increase in lapse rates (since the Discounted Premium Term has dropped to 3.2, suggesting major problems with persistency).

At the same time, although 2010 was a step backwards in terms of DPT for Investment business, the increase in volumes of business (API), allied with a restoration of the DPT to close to 2009 levels, a reduction in RPP (suggesting better value for policyholders, which should give rise to better future sales, lower persistency and less regulatory intervention) and a strong growth in NBMR, driven off efficiencies, expense reductions and economies of scale through greater sales.

Our risk business is in trouble and requires attention, but we are building a solid, profitable and sustainable investment business that should provide good returns to shareholders.

Conclusion

These are stylised examples filled with hidden good news. The reality is that many insurers are struggling in several business units.  The analysis and tools outlined here can help make better informed decisions around product strategy and pricing, and for analysts wanting to better understand the current and potential future financial performance of these stocks.

For short-term business (group risk, health insurance, health administration, general insurance etc.) it is something different since these lines don’t have long-term prudent provisions. In these cases it reflects the present value of future profits expected to be earned out of the existing business.

The inclusion of these short term types of business within EV is widespread. It seemingly increases consistency between different types of contracts since we are considering the long-term expected profitability in all cases. More on this apparent consistency in a moment.

What do we include in the EV and VIF?

EV is not a complete economic measure of the value of an insurer, since it ignores future profits arising from future new business. This is by design. An Appraisal Value incorporates the Value of Future New Business (VFNB) as well, although there is always subjectivity over how many years of future new business should be included. (More on this in a separate post.)

Existing Business vs Future Business

The idea of “existing business” and “future new business” is clear in the individual life context. It’s existing business if you have a contract, and future new business if not. Premium increases and slight benefit modifications can usually be accommodated within the existing contract and so should ideally be included in the Value of In Force (VIF) based on the expected probabilities of these changes.

As such, the expected future premium increases should also be factored into the Value of New Business (VNB) when the business is originally sold. (Don’t confuse VNB with VFNB.  VNB is the value of business written over some past historical period, typically the last month, 6 months or year. VFNB is the expected value to owners of the business from business that will be sold at some point in the future.)

What counts as In Force for short term contracts?

The position is less clear for Group Risk or Motor policies. These are typically annual contracts, but with high expectations of renewal. In this case the renewals are typically included in the VIF at some assumed level of premium inflation reflecting wage growth rather than new business. Premium inflation is an important consideration in countries with non-negligible inflation. New employees on an existing Group Risk policy are also usually not considered new business since no new sales activity was performed or purchasing decision was made.

The rules applied then are quite well understood. However, we are valuing two different things between short term and long term contracts, and also a little bit of something we shouldn’t.

The source of value for long-term and short-term contracts in the EV

For long term contracts, we are valuing expected future surpluses arising out of a long-term contractual right and prudent regulatory provisions.

For short term contracts we are valuing the existing contract (a small portion of the total value) and the customer relationship that will give rise to future renewals.

There is also a component of customer relationship in the long-term contractual rights since poicyholders can lapse the contract, incur some penalties possibly, but ultimately not be required by law to continue paying premiums. It’s difficult to separate these components though.

Unintended inclusion of brand value

Now the interesting part: I maintain that by using a best estimate future renewal rate for short term contracts, we are actually valuing a portion of the brand over and above the customer relationship. This is best demonstrated by an example.

Example of confounding of customer relationships and brand value

Take a company with a 20pc market share in the group risk market in which it operates. Let’s also say that best estimate future renewal rate is 80pc. If we assume a constant market share percentage (arising because of the value of the brand, but may be also broker networks etc.) then 1 in 5 employer groups looking for group risk cover will choose our hypothetical company – ignoring customer relationships.

Some of our customers will be very pleased with our service and will renew for that reason. The good customer relationship is a significant source of value. However, some of our customer won’t particularly value our service or relationship. Some of these will leave, but others will stay anyway – because of the value of our brand.

In fact, we should expect 20pc of our existing customers to renew even if there is no customer relationship at all. Why should existing customers be less likely to choose us again even if there is no customer relationship than a brand new customer?

Some of our customers may be so put out by an unfortunate incident, poor service or a repudiated claim that they may deliberately not renew. A customer relationship doesn’t have to have positive value.

So of our 80pc renewals, 20pc renew for reasons independent of our customer relationship. So the correct renewal rate to apply when measuring customer relationships is actually 60pc.

The impact can be significant

This makes a significant difference to the VIF. For a 20 year projection and 20pc market share, the difference is a reduction in VIF of 46pc. For a 10 year projection with a 5pc market share, the difference is still 14pc.

You can test the impact using this Renewal Test model under Example Models.

What does this mean practically?

Now we haven’t changed the true value of the business; we’ve changed how much of it we recognise as a customer relationship. With a lower VIF, we would expect to see positive renewal experience variances (if we compare actual renewal rates to modelled) or higher volumes of new business (if we treat the portion of renewals related to overall market share as new business) athough the new business margin on revenue will be lower since we are modelling a lower Discounted Premium Term (DPT).

Neither of these results is very satisfactory. Perhaps the answer lies in separating renewal into a change in market share impact and the remaining renewal variance so that the VNB is still objectively measured as new sales, but the persistency profits are separately allocated between the known adjustment for brand and the actual deviations from renewals being further different than expected.

Merger and Acquisition pricing and accounting

Specifically though, this has important implications for accounting for insurance mergers and acquisitions and the types of intangibles created. It also feeds into the purchase price decision and valuation adopted for an acquisition. Ultimately, views of the Appraisal Value of annually renewable business must incorporate these important differences when compared to individual life businesses.

Bahrain has a population of around 1.2 million but has a well developed insurance sector. Economies of scale limit domestic growth and regional expansion faces tough competition and increased complexity. Will be interesting to see more.

Richard Thaler presents some of the common perception problems with annuities in this article in the NY Times. The basic message is still as it has been for decades. Individuals are reluctant to pay a large portion (often the majority) of their life savings to an insurer with the risk that they will die in a few years and “not have got their money back”. The peace of mind that should come to the policyholder turns into a matter of stress.

The bequeath motive is strong – and amplified by a lack of understanding of exactly how long we’re likely to live in retirement these days and how much money will be required. Those to whom many plan to bequeath may ultimately become the source of support when the income draw-down products are depleted with no longevity guarantee to boost the funds available.

It’s a good explanation although he doesn’t break much new ground. He also doesn’t talk about the concerns some potential policyholders have, in some countries at least, of whether the insurance company who sells the annuity will definitely be around over the next 40 years come what may.  This is more common in developing markets with weaker regulation (probably a good reason to have concerns) and less history of annuities (a cultural bias that will probably disappear over time).

Mr Thaler doesn’t propose any solutions for the insurers in boosting sales – a common “fix” is to combine a traditional pay-until-death annuity with a guaranteed minimum period or a death benefit (either for a limited term or at any point).  These adjustments reduce the “risk” of “making the wrong decision but purchasing an annuity but only living for a short period”.

There’s no free lunch.  In the same way that cash-back bonuses on short-term insurance products actually increase the average cost of insurance and reduce the risk-transfer from insured to insurer, these guarantee periods increase the cost of annuities.

What is New Business Margin?

Many life insurers currently calculate a measure of the profitability of new business sold over a period called “new business margin”. As defined by the CFO Forum’s MCEV Principles and confirmed in South Africa’s PGN107 covering embedded values, this is the Value of New Business (VNB) divided by the Present Value of New Business Premiums (PFNBP) calculated on a consistent basis.

This is a useful measure since it shows, on average, how much of each premium goes to shareholders as profit, after deducting operating costs, benefits paid to policyholders and a cost of the capital required to support the business.

It’s far more useful than a common previous metric of VNB / API where API is Annual Premium Income or APE Annual Premium Equivalent, since the numerator reflects a multi-year stream of profits and the denominator just a single year. It’s a more difficult number to interpret intuitively.

Of course, New Business Margin is also fatally flawed.

The underlying problem with New Business Margin

The premium for a risk-type product (term assurance, credit life, funeral insurance etc.) can be thought of as the cost of obtaining the service, which in this case is insurance against death or disability. The profit margin is the share of this premium that the insurer takes as profit for providing the service. So far so good. VNB / PVNBP is present value of profit over present value of revenue to the insurer.

The premium for investment or savings business – well frankly it’s a pity it’s also called a “premium”. It’s money handed over by a policyholder to an insurer for the insurer to manage on the policyholder’s behalf, generate an investment return, and return to the policyholder at a later point. The “premium” is not the cost of the service.

You don’t pay a “premium” to your bank when you deposit your salary. You don’t pay a “premium” when you invest in unit trusts.

Policyholders also expect to get the vast major if their premium straight back, and hopefully with some investment return. The cost of service is actually the charges or fees deducted from the investment account balance by the insurer to pay for operating expenses, cost of capital, risk benefits (if the policy also has death or disability cover, for example) and shareholder profit.

The correct stream of revenue for the insurer is not “premium” but rather the fees and income deducted from the policyholder’s account. New Business Margin as it is currently defined shows a miniscule margin because it’s not comparing profit to revenue, but rather profit to the money entrusted to the insurer to look after.

Banks focus on interest rate spreads and cost to income ratios, rather than profit compared to total liability base. Because, well, that’s just not that useful.

Why New Business Margin is not useful

Setting aside for the moment the problem that New Business Margin for investment / savings products is not a coherently defined metric, why should we care on a practical level about finding a better measure for new business margin?

1. You can’t compare New Business Margins across companies, products or business units.
   The comparisons will reflect both differences in actual underlying profitability as well as, and in far greater magnitude, differences in product types and the mix of risk vs savings products. A 4% new business margin is either low for risk business or very high for savings business. Or totally indeterminate for a mix of both types.
2. It confuses the required strategic and product decisions to improve shareholder value.
   If New Business Margin is the measure, then most insurers should stop writing investment business altogether, even though this can be a shareholder value-creating business line.
3. It can create distorted sales incentives.
   It is much easier to sell a R2,000 per month savings policy than a R2,000 per month risk policy. Disproportionately skewing incentives towards high margin risk products could end up reducing total VNB generated through smaller average policy sizes.

A better alternative – New Business Margin on Revenue

A more useful and comparable measure of profitability would be the VNB / PVFR, where PVFR is Present Value of Future Revenue, and where Revenue is recognised as income flowing to shareholders, which would exclude the deposit-like components of savings business “premiums”.

• It is a consistent measure across risk and savings business
• It is easy to calculate using existing systems
• It uses familiar terminology, while adding more information
• It supports relevant component analysis to better understand drivers of margins (see below)
• It drives the correct strategic, business mix and sales-target decisions

Simple component analysis of New Business Margin on Revenue

This new definition of new business margin  naturally gives rise to an interesting component analysis:

VNB = (VNB / PVFR) * (PVFR / PVNBP) * (PVNBP)

Which shows that Value of New Business is my proposed New Business Margin * Revenue Per Premium * Present Value of New Business Premiums

Revenue Per Premium is a measure of how much total revenue is deducted from each premium on average for the insurer. Higher numbers reflect more value extraction for shareholders, but a higher Reduction in Yield for policyholders. For risk-only policies, (PVFR / PVNBP) is 100%.

Present Value of New Business Premiums is then the overall volume measure for new business sold over the period.

The preferred approach to New Business Margin on Revenue component analysis

VNB = (VNB / PVFR) * (PVFR / PVNBP) * (PVNBP / API) * (API)

Which expands Present Value of New Business Premiums into the product of API (Annual Premium Income, or the annualised value of premiums on new business sold during the year, which is an important volume measure) and the average discounted term of future premiums reflecting the durability of the book.  Short-duration product or product line with high lapse rates will have a low (PVFP / API) ratio, reflecting value creation for shorter periods.  Long-duration policies with low lapses will generate value over a much longer period.

Increasing VNB can be accomplished by increased any of the four components, but increasing the revenue per premium component is at the direct expense of policyholder value for money.

So VNB = NBMR * RPP * DPT * API

This analysis is of course most useful if it is performed separately for business/product lines to show the drivers of profit for each. I hope some insurers will take the step to disclose this level of detail.

Extensions of this analysis

Several extensions to this analysis are possible. One the most interesting is where we add a component for cost of capital, showing the percentage reduction in VNB as a result of deducting the cost of capital required to support the new business. Another, more complex analysis would be to separate fixed and marginal expenses in order to determine the effective operational gearing of the business to new business.

It is possible to get too carried away so I suggest these measures as additional, optional measures possibly better suited to internal analysis than widely distributed external reporting.

The burden of unbundling

New Business Margin on Revenue is another call for unbundling of insurance contracts into investment and insurance components. This isn’t a popular idea for many insurers because of the expensive system and reporting changes this would require with limited immediate benefit to offset the costs. (Unbundling isn’t actually required to implement New Business Margin on Revenue.)

My view is that unbundling is inevitable. IFRS4 Phase 2 is pushing for it, reviews of life insurance taxation could well end up requiring unbundling and from an internal value- and risk-reporting perspective there are clear advantages. There are known challenges, for example the unbundling of some older whole of life endowments where there isn’t necessarily an explicit risk premium to unbundle. Also, as many contracts are priced and designed without unbundling in mind, the separation of fees and charges is not objective and will involve decisions around allocating cross-subsidies.

While recognising these challenges, I would counter that the improved discipline of understanding more clearly activity based costs for general administration, investment management and risk administration is actually a positive outcome which will come with unbundling.

New Business Margin on Revenue (NBMR)

NBMR = VNB / PVFR

and the component analysis:VNB = NBMR * RPP * DPT * API

The advantages of New Business Margin on Revenue outweigh the initial work to set up systems to calculate the new, more useful, more comparable and ultimately, more enlightening metric.

Contact me to pre-order the comprehensive New Business Margin on Revenue methodology and understand more complex component analysis for financial reporting, treating customers fairly, due diligence, how NBMR links into IFRS4, Solvency II and SAM and the systems implications of introducing NBMR.

Now there are many people who don’t like Embedded Values, and they certainly have some good reasons for being wary of it. Embedded Values are a measure of shareholder value in a life insurer that adds the shareholder valued embedded in prudent regulatory reserves to the net worth of the company with an adjustment for the cost of holding capital. It is needed because current accounting measurement of insurance liabilities is also typically overly prudent and thus book value on an accounting basis is a really bad measure of shareholder value in a life insurer.

Embedded Values are flawed due to imperfect allowances for risk, lack of comparability across countries and even sometimes companies and a methodology that can make value magically appear out of taking on mismatch risk.  Worst of all, in a practical sense, is that life insurers typically trade at a discount to Embedded Value in the market (Embedded Value is greater than Market Value) even though theory suggests Embedded Value should be less than Market Value since we haven’t included any allowance for future new business/goodwill/franchise value.

None of this was the basis for the preference for Return on Equity over Embedded Value.

You can’t eat Embedded Value.

That was the criticism. You can’t eat Embedded Value. This is true.  Of course, you can’t eat Equity either.  You can’t eat Book Value.  You can’t eat earnings.  While we’re at it, you can’t actually even eat cash, although you are reasonably likely to be able to potatoes directly with the cash (as in a dividend) than with most other measures.

So while you can’t eat Embedded Value, you just as well can’t eat Book Value.  In the life insurance space, it’s really hard to get a handle on “tangible” asset value.  Our liabilities will always be based on an estimate of future cashflows. Embedded Value is in its most basic form just a different value of different future cashflows discounted at a different rate.  It is no less (or more) tangible than Book Value.  Return on Embedded Value is no less tangible than Return on Equity since they both depend on uncertain estimates of future cashflows and experience.

The difference is, we know that Book Value is categorically, definitely undervalued.  The degree of undervaluation is different from one company to another depending on the level of prudence included in the liabilities. In South Africa, it’s also fundamentally undervalued because the liabilities ignore the economic value arising out of optional (but reasonably predictable) future premium increases.

This means that Return on Equity is an overstated measure of return since the measure of Equity is understated because the liabilities are overstated.  Worse, we can’t compare it from one insurer to another since their liability valuations will be different.

So while you can’t eat Embedded Value, you will make more value for your shareholders basing decisions on Embedded Value than on Book Value.

Interestingly, new accounting developments (IFRS4 Phase 2) and regulatory developments (Solvency Assessment and Management, based on Solvency II from Europe) will completely change the way we measure financial performance of insurers. And no, I still won’t be using Return on Equity.

The tail of a distribution includes the very bad and very good possible outcomes, that typically have a very low frequency of occurring. Having your house burn down is a very bad outcome, but fortunately happens very infrequently. Winning the lottery is very good, but unfortunately in this case is also very unlikely for any particular individual.

Managing the nasty tail

A rational person who wants to avoid the unlikely but catastrophic risk of  losing their house to fire will be prepared to pay more than just the average cost of the loss of the house in order to avoid the risk. Typically, we humans are risk averse (a wild generalisation given the research into utility and decision making that has led to behavioural finance and behavioural economics, but probably good enough for now). Insurance provides:

• genuine decrease in risk and indemnification of losses against the loss event happening
• peace of mind even if no loss is ever experienced, which has real value in terms of clearing the mind to think about other more important and more controllable personal and business matters
• reduction in the amount of capital / liquid assets individuals and businesses need to keep against unforeseen events. This capital can be better used and invested elsewhere

Contrary to the popular view, insurance has value even if you never claim.

Gearing to the nice tail

Gambling can be dangerous and addictive. It can also be entirely rational to gamble within certain parameters.

Many people with a little mathematical, statistical or economic backgrounds view gambling as foolish because on average, those playing against “the house” will lose. Playing the game has a negative “expected value” since on average more money is spent than is one. (Casions regularly pay out approximately 97% of the money they take in, safe in the knowledge that most of the money they pay out will be return straight to the casino. The casino has several bites at your wallet. Playing ten times over reduces the effective payout to below 75%.)

A negative expected value is not sufficient to make it irrational to play the game. Insurance has a negative expected value for the insured but for the reasons mentioned above it is rational to use an appropriate amount of insurance.

The step that comes closer to making gambling irrational is that the gambler is paying to take on risk. Insurance is all about paying a premium to reduce risk. If humans are naturally risk-averse, how can it be rational to pay a premium to take on risk?

This brings into sharper focus the problems around the generalisation that humans are risk averse. I’ll try to explain how it can be rational to gamble under some parameters as an example of how risk-seeking behaviour (paying to take on risk) can be rational.

Entering the national lottery twice a year (you and your spouse’s birthday, for example) will cost around R7 per year. If you start this when you get married, using very rough numbers, it will almost certainly cost you less than R500 over your entire life. That R500 is not going to change your life in any meaningful way, but it does provide the chance of a completely life-changing event. You could pay off your house and cars, stop working, travel the world, donate to your favourite charities and provide for your children’s health and education. You now have upside exposure to that very unlikely, buy very desirable outcome.

Provided you don’t live your life expecting to win the Big One, and provided you don’t buy a hundred tickets every month to improve your chances at the expense of food on the table for your family, this can be an entirely sensible decision.

Other tails

Gold miners can’t control the gold price. In order to plan operations and capital investment, they should be hedging gold production at some level. The downside tail of very low gold prices is an unbearable risk that limits the ability of the organisation to be an efficient gold miner.

Gold exploration companies, on the other hand, are geared to the upside tail. Expenses are relatively fixed, and the chance of success isn’t great, but the payoff is they literally strike gold is fantastic.

Entrepreneurs are putting themselves out into the risky world, hoping to catch a wild ride up a huge positive tail.

Management diversifying a business because all their personal interests are too tightly focused in a single company, in a single industry, in single part of the value chain are hoping to avoid nasty tail events (or trying to diversify away from a dying business, or simply empire building rather than returning cash to shareholders, but that’s several separate posts altogether).

The lesson

The distribution of what can happen is important. Forget about the MBA mean and standard deviation mirage. Those measures conceal more information than they provide. Understood the most likely events and the extremes, understand how they affect your business and understand how the perception of these issues affects the decisions of those around you.

Why was a new OpRisk formula needed?

The original formula for OpRisk proposed in QIS4 was widely condemned. Complaints included being too simplistic, being insensitive to risk (and basely primarily on business size) and the impossibility of calibrating to 99.5% in a meaningful way. CEIOPS accepts most of this criticism, but counters by reminding stakeholders that the aim of the standard formula is partly about being simple.

A more serious problem is that in comparison against companies’ own internal models, the standard formula produced results lower than companies’ own assessment. Median internal model requirements for OpRisk were 133% of the standard formula and 13 out of 16 countries reported higher requirements under their insurers’ internal models.

One of the aims of the standard formula is to be slightly conservative to provide an incentive for insurers to develop their internal models. Clearly this objective is not being achieved.

Current OpRisk recommendation for Solvency II

CEIOPS has issued final (they’re calling it final anyway) level 2 guidance on OpRisk requirements under the standard formula.

CEIOPS-L2-Final-Advice-on-Standard-Formula-operational-risk

Although there are a few detailed differences (around negative components, for example) but the most significant change for most insurers will relate to the change in parameters. In many cases the changes are close to doubling of the parameters. This will significantly increase capital requirements for many insurers.

QIS5 is planned, so presumably the financial implications of the new recommendations will be tested.

It’s still clear to most that OpRisk is particularly poorly suited to Pillar 1 and purely quantitative requirements. While the updated formula wont have won over many of the loudest critics, it does better match capital requirements to those companies were getting from their own models.

Best solution is still a company-tailored internal model combining actual loss data collected, supplemented by subjective frequency/severity assessments mapped to density functions using work-shopping techniques.

Other relevant CEIOPS documents on Operational Risk

Comments and responses paper (pdf)

Earlier suggested OpRisk paper (superseded by November version) (pdf)

Note from the Actuarial Society of South Africa outlining recommendations for use in conjunction with PGN104 (December 2009):

ASSA OpRisk guidelines