What is success? Are you a successful actuary?

Simple questions, easy to answer you would think. Right?

Wrong!

To illustrate the deeper  meaning and the nuance of success, let's take a look at the next 'Best Practice of Success'. A real life story from Joshua Maggid.....


Moral of the story
From the above example it's clear that 'short term success' is not the same as 'long term success'.

To prevent ending up only in the reality of our own believes, constructive peer reviewing each other's performances is key to keep delivering long term top quality.

So don't forget to discuss your 'actuarial eggs' with one of your actuarial colleagues.....
Finally....
It takes 'new ethics' actuaries (and quants) to make pension fund business successful again.
Are you that actuary?

Related links:
- Making Decisions in the Pension Fund Board Room (PDF,2010)
- Investmentmentor:
   expectation, a force that will release either success or failure

What is simplicity? What's the power of simplicity?

Goethe
It was Johann Wolfgang von Goethe ( listen), a German writer (poet), but also a polymath (!), who
stated:


And indeed Goethe was right, in (actuarial) science and  practice it's the challenge of overcoming (transcending) this paradox of simplicity and complexity.

The art of actuarial mastership
As models become more and more complex, it takes the art of actuarial mastership to condense this complexity into an outlined, understandable and (for the audience) applicable outcome.

A 'best practice example' of condensing complexity into a powerful inspiring statement, is Einseins famous equation E=MC² :

Like Paulo Coelho states in his blog about Einstein:
A man (actuary) should look for what is, and not for what he thinks should be. Any intelligent fool can make things bigger and more complex… 

It takes a touch of genius – and a lot of courage to move in the opposite direction.

Or, to quote Einstein:



Just three simple examples on how to cut through the complex actuarial cake. Examples that might help you to simplify complexity:


A perfect example of 'thinking more simple' is finding the solution of the next math problem (on the left), grabbed from an old high school math test.

Can you solve this problem within 10 seconds?

Found it? Now move your mouse over the picture or click it, to find the refreshing simple answer.....


Remember however not to oversimplify things. Sometimes problems need the eye of the actuarial master to identify important details...



Second example is to visualize the outcome of your models instead of power-point bullet conclusions or explaining how complex your model really is.

A nice example is the online dollar-bill-tracking project "Where's George?" from Research on Complex Systems, that measures the flow of dollars within the U.S. (over 11 millions bills, 3109 counties).
About 17 million passengers travel each week across long distances. However, including all means of transportation, 80% of all traffic occurs across distances less than 50 km.
One picture says it all and 'hides' the complex algorithms used, to get  stunning results.

On top of, George collects relevant data about 'human travel' that could be used for developing models of the spread of infectious diseases.

Just take look at the video presentation of George called Follow the Money to find out how to extract simple outcomes from complex models.

One of the simple results (by Brockmann) of this project is that the probability P(r) of traveling a distance (r, in km)  in a short period of time in days (max 14 days) can be expressed as a power law, i.e.:

Every (actuarial) project outcome fails if there's no well defined goal at first.

Main problem is often, that the client isn't really capable of defining his goal (or problem) very precise and we - actuaries - start 'helping' the client.  In this 'helping' we are imposing our thoughts, beliefs and experiences onto others, by what we think 'is best' for the client. The outcome might often be an actuarial solution that fits the problem in our own actuarial head, but fails to meet the clients problem.

Main point is that we - as advisors - don't really listen well.
Of course that doesn't apply to you as an actuary personally, but it does apply to all other qualified actuaries, doesn't it?

Just to test if you're part of that small elite troop of 'well listening qualified actuaries' (WLQAs), just answer the next simple Client Problem:


O.K. Now think for a moment.....

Have you got the answer to this complex client problem?

Hope you safely (without any mental damage) passed the above WLQA-test......

A nice demonstration of actuarial simplicity is the well known 'compound interest doubling rule' that states that an investment with compound interest rate R, doubles itself in N≈72/R years.

So it'll take (p.e.) approximately N≈ 12 (=72/6) years to double your investment of $100 to $200 at an compound interest rate of 6% p.a.

While the precise equation of the doubling time is quite complex to handle, it's approximating equivalent, N≈72/R, is simple applicable and will do fine for small size compound interest rates.


It's our actuarial duty and challenge to develop simple rules of thumbs for board members we advice. We actuaries have to master the power of simplicity. Let's keep doing so!

Related links:
- The Complexity of Simplicity
- Where's George?: Wikipedia
- The scaling laws of human travel (2006)

To snap things in the right perspective, now and then it's good practice to consider how actuarial science really started:


Yes, like Laplace stated in his masterwork 'Théorie Analytique des Probabilités', it all began with 'games of chance'... and - today -  perhaps it still is.....

From 'gaming', probability theory developed to 'actuarial science' and finally to 'risk management'.

Today we distinguish three main types of risk levels:

Risk Level 1
In fact what we are modeling mostly, are the risks we know, the 'known risks'... These risks are the familiar operational, financial and compliance risks

Risk Level 2
These are the strategic risks. Risks related to new markets, mergers and acquisitions, investments, but also business development, brand and reputation risks.

Risk Level 3
These are the unpredictable, the so called 'unknown, unknown risks'.


A similar more humorous, but also interesting definition of risk levels, has been given by the United States Secretary of Defense  Donald Rumsfeld  during the Iraq War:

1. Known Knowns
   There are known knowns; there are things we know that we know
   
2. Known Unknowns
   There are known unknowns; that is to say, there are things that we now know we don’t know
   
3. Unknown Unknowns
   But there are also unknown unknowns; there are things we do not know we don’t know."
   

If we're honest, we'll have to admit that even our 'known known' and 'known unknown' risks in our models in reality have a high 'unknown unknown' origin.

Or, as Barry du Toit at Riskworx shows in an excellent paper called 'Risk, theory, reflection: Limitations of the stochastic model of uncertainty in financial risk analysis' : our stochastic model of uncertainty is powerful but limited.



It's (p.e.) an illusion to use 'standard deviation' as a stand alone measure for risk. We must be aware to apply our models without a healthy portion of 'common sense'. Or, to put it in air-plane words:


God’s definition of risk
There is no ultimate "God’s definition of risk", we'll have to manage with our limited models as a help to our Risk Insight. Success!


Sources and related links:
- Limitations of the stochastic model of uncertainty in financial risk analysis
- Laplace: analytic theory of probabilities (English)
- Strategic Management of Three Critical Levels of Risk
- Managing Projects in the Presence of Unknown Unknowns