Jun 26, 2010

Death by Solvency

Risk Management can be a strange and deathly game. Normally one would expect that the more the demand of Probability of Insolvency (POI) is decreased:
  • the more Prevention- , Risk-reduction- and Damage-control-measures will be taken
  • the less actual Risk and corresponding Loss will actually occur
  • the higher the resulting average yearly profit
  • the lower the resulting yearly profit volatility

This appears to be true in situations where Risk Management is hardly developed and POI-Demands are relatively modest (5%-2.5%).

Increasing POI-Demands
However, depending on the type of risk, beyond certain POI-Demands (smaller than roughly 2.5%) , the costs of Risk management measures, maintenance and capital requirements become higher than the average expected Loss-reduction, resulting in - on average - lower profits.
Of course, these extra risk management investments and capital requirements can financed by raising consumers prices, but - on balance - this will result a smaller market corresponding with a lower profitability level.

The question can be asked if this still is what we, management and consumers, intended to achieve.......?

Next, in our passion to reduce Risk to an even more extreme low level, we can get carried away completely...

Excessive POI-Demands
When POI-Demands get to levels of 1% or less, a remarkable psychological effect enters the Risk management arena.

Management perceives that the Risk-level is now actually so low that they cannot fail anymore.
In their ambitious goal to outperform the profit level of their competitors, management gets overconfident and reckless. What would you attempt to do if you knew you could not fail?

When POI-Demands are set to levels of 0.5% or less (as they are mostly now in 2010) it becomes almost impossible to beat your competitors with an approach of 'taking more risk'. Even if one would try to manage or hedge these extra risks 'best' in the market. In the long-term, the price of this risk would equal or beat the expected loss.

In this situation some managers get desperate and instead of considering things 'right', they see only one option 'left'....

'Working Around (the) Rules"

WAR, Working Around the Rules, comprises actions like:
  • Taking (extra) risks on non-measurable or non-measured financial transactions, or or 'non-obligated-reporting risks'
  • Manipulating, disguising or mitigate risk information, or risk-control reports
  • Misuse legally allowed methods and accounting principles to create legally unintended financial effects or transactions

It's perhaps hard to admit, but as actual developments show, we've entered the final WAR phase. Some Examples: subprime, Madoff accounting, BP-deep horizon oil failure, bank multipliers, etc, etc.

In all these examples, managers (are pushed to) become over-creative by working around the rules to deliver what they've promised: more profit.

However this approach always results in
  1. More short-term profits
  2. Less long-term profits
  3. Sudden bankruptcy in the end

This development, resembles the 2010 situation in the Insurance and Banking industry where, after each financial debacle, POI-Demands where successively decreased to a 0.5% level  and have resulted in marginal profits and a highly volatile Profits or even losses. Pension Funds (NL: 2.5% POI-Demand) appear to be the next patient the operating table.....

The situation is out of control. Nothing really seems to help anymore....

Are there any solution to prevent this solvency meltdown process?
Yes, but that's for another blog as this one is getting too long...

Related links:
- Why excessive capital requirements harm consumers, insurers and...(2010)
- Presentation - Modelling of Long-Term Risk (2010)

Jun 18, 2010

Risk Symptoms Matrix

On INARM (International Network of Actuarial Risk Managers) ERM advisor Dave Ingram raises the simple question:

What must managers who are not modelers know about models?

Perhaps this question is one of the most relevant questions in Risk Management and the Actuarial profession. It's a key question that should be discussed on Board Level in every (financial) area.

Also this question is relevant in setting up and managing complex projects like Solvency II, ERM, Pension Fund Risk Management, ALM and even "In control" projects.

The answer
Now let's try to answer this intriguing question

Managers are experts in 'decision taking'. Modelers are experts in reducing and simplifying complexity to decidable parameters.

Now the Quality (Q) of a management decision (D) is defined by the equation:

[ Q(D)= Q(Manager) x Q(Modeler) ],

where Modelers are responsible for the Quality of the Input (data) of the model [Q(Input Model)] and the Quality of the modeling process itself [Q(Modeling)].

More refined, we may therefore define :

Q(D)= Q(Manager) x Q(Input Model) x Q(Modeling)

Luckily, not all Q's are independent!
Both Managers and Modelers can raise the Quality of the outcome of the Decision process by asking each other "What If" questions.

By asking WI-questions with regard to the 'Input of the Model" [Q(Input) = data, decision parameters] and examining the output, Modelers are able to raise the Quality of their (technical) Modeling by improving their technical Model [Q(Modeling)].

Moreover, decision parameters are not set in stone. So by asking WI-questions, Modelers become more aware of the Management Decision Consequences (MDCs), helping them to develop and simplify decision parameters to the most adequate, understandable and possible simplified form. Or as Albert Einstein quoted it:

"Everything should be made as simple as possible, but not simpler"

On the other hand, by asking WI-questions, Managers can study the effects of various decisions they might take in different (simulated future) circumstances (as roughly described by the Manager).

This process improves the decision taking skills of a Manager and therefore improves the Quality of the Decisions taken by Managers [Q(D)] in general. At the same time, the Modeler may use the given information from the Manager to improve his Model and (future) data as well.

We may conclude that the answer to the question 'What managers, who are not modelers, need to know about models' is:

Nothing, as long as Manager and Modeler intensively communicate with each other, ask WI-questions, are not afraid to admit their weakness or doubts, challenge each other and don't manipulate each other!

Perhaps an ever more tricky question to answer is:

"What must managers who are also modelers know about models?

Possibly Dave Ingram has the answer to this question....

Aftermath What happens when communication between Managers and modelers fails, is well illustrated in the Gulf of Mexico Oil Disaster, where BP CEO Tony Hayward stated before congress:
- “I simply wasn’t involved in the decision-making.”
- “Clearly an engineering judgment was taken.”

It's easy to spot failing Management-Modeler relationships by means of the next 'Management-Modeler Symptoms Matrix'.....

If you happen to be a modeler in the upper left quadrant, get out as fast as you can!

Jun 12, 2010

Actuarial Model World Cup 2010 Winner

In 'The Actuary June 2010', Greg Becker (actuary) and Arminder Kainth (annuities pricing analyst) present the outcome of an actuarial model they developed, to  predict the probability of a country winning the Fifa World Cup 2010.

With Brazil as a clear winner, here's the outcome:

Perhaps trading on the World Cup 2010 Bet Market can become a new interesting alternative for traditional investment categories....
Anyhow, let's hope (fingers crossed) that actuaries are right and Brazil, Germany, Italy and England all end in the semi-finals. In this case we'll ask both actuarial whiz kids to develop a new actuarial investment model to settle (for ever!) the everlasting bonds-stocks discussion....

Place your own (free) bet
Meantime if you want to place your World Cup bets for free, join The Actuary World Cup PredictorPro game in association with Star Actuarial. For your chance to win an iPad register at Predictorpro.
Start right away, because betting already started....

Used Sources:
- The Actuary: Article 'World Cup fever' (pdf)
- The Actuary:Who will win the World Cup?
- Free bet at Predictorpro

- Estimating the Real Rate of Return on Stocks Over the Long Term (2001)

- Pension Fund Investments: Stocks or Bonds? (2004)
- Social Insecurity? (2008)

Jun 5, 2010

Pension Fund Coverage Ratio Analogy

Let's compare driving your car with managing a Pension Fund. Are you ready?

You, the Car Driver

Suppose you plan a trip from New York to Washington, about 200 miles, in a tight time schedule of four hours .

You're know your car's average fuel consumption is on average about 25 miles per gallon and your dashboard computer tells you, you've got 10 gallons left in the tank.

Simple mental arithmetic shows you'll finish in Washington without any major 'out of gas'  problem if you keep your average fuel consumption above a rough 20 miles per gallon.

You tell your partner, who's next to you in the car, you're quite sure (97.5%) there's enough gas left for Washington.

Suddenly - your half way climbing a small hill - your Miles Per Gallons (MPG) Meter drops from 25 to 13.

A bit worried you take a look at the Average MPG Trip Meter on your dash board computer that shows an average of 35 miles per gallon on the first 100 miles.

You conclude there's no problem or real gas shortage issue to be expected and decide to keep checking your dashboard every 5 minutes to find out how the Average MPG develops.

Your partner, who's not familiar with driving a car or arithmetic exercises, tells you to stop at a gas station immediately and to end this silly arithmetic game.

You - quietly - explain that there's no need to go to a gas station and if you would go to a gas station, the two of you will be late on your appointment in Washington.

You tell her that you'll take no direct measures and have decided to look for a gas station if your average GPM meter shows a 25 gallons per mile.

Your partner is satisfied and you continue your trip.

Problem solved.
You, Pension Fund CEO

Suppose you run a 30 year old Pension Fund and your target is to keep a save coverage ratio of 125% on the long run.

The outcome of intense and professional Risk Modeling, ALM studies, VaR analyses, FIRM approach and other sound risk techniques, has concluded in an agreed asset mix, implicating that daily coverage ratio's may vary (97.5% CI) between  65% and 185%, corresponding with an average long term coverage ratio of 125%.

Suddenly, exactly at the Pension Funds 30th  birthday, interest rates collapse....

Your Dashboard's Daily 'Pension Fund  Coverage Ratio' (PFCR) meter shows a surprising meltdown to 65%!

All pension board members look worried. They take a look at the '5 years Average Pension Fund Coverage Rate Meter' at their Dashboard. This meter  shows a trustful 132%. You and your board conclude there is no urgent or substantial problem of  shortage on the long run.

Problem solved!, one would think. Unfortunately: No!.

At this point the Supervisor starts interfering. The Supervisor is worried and orders the Pension Board to develop a recovery plan outlining measures on how the pension fund will restore minimum funding requirements within a five-year time frame.

This Recovery Plan (RP) was not included or part of the original  strategic risk management plan as foreseen. The extra costs of executing this RP and the effects of reallocating the assets to a lower risk position, result in a lower return of the pension fund on the long run with a lower coverage ratio than the original 125% objective average.

The pension fund was forced to improve the short term (daily)  coverage ratio a little bit at the cost of substantially lowering the coverage ratio on the long run.


It's clear that ...
  • Pension Funds shouldn't be managed just on daily coverage ratio's, but more on 5 or 10  years average coverage ratios.

  • Demanding recovery plans after a disappointing 'two year coverage ratio' is not wise and damages the long term objectives and financial results of the pension fund.
  • In case of  long term (more than 5 years) failing coverage ratios, there's enough time to take measures to redefine the Pension Fund's strategy and funding policy. The same applies for interest rates, returns and other Dash Board parameters, excluding liquidity scores.
  • Much more than banks, Pension Funds are financial institutions with mainly long term obligations and should therefore mainly be managed, controlled and supervised by "long term" score card parameters.

Therefore, Supervisors should change their Risk Management philosophy as well as their control policy on this subject. Supervisors should redefine dash board parameters and only demand recovery plans in case of more than five year consequently failing coverage ratio's.

Related Links
- GN26: Pension Fund Terminology (pdf)
- Coverage ratio Dutch pension funds.png
- ABP assets up, but funding ratio down
- Fuel Convert
- New York Senate passes gallons per mile bill
- GPM psychology