The Big C is behind every great Risk

Concentration, defined broadly, is the source of all risk.

In an unconcentrated pool of activities, all with potential for positive and negative outcomes, provides the Big D – Diversification.

So it seems simple to avoid C – just do D.

But we have so many ways to concentrate.  And concentration is particularly tempting.

• When things are going well, it makes sense to do more of whatever it is that is working best.  That increases concentration. 
• Once we learn how to do something right, it makes sense to do more.  That increases concentration.
• One supplier is almost always the cheapest, fastest and best quality.  So we give them more business.  That increases concentration. 
• That one product has better margins than the rest and it sells better too.  So we plan to increase our capacity to make that product.  That increases concentration. 
• Our best distributor runs rings around the rest.  We are working on giving her a larger territory.  That increases concentration. 

The alternative, the diversifying alternative just doesn’t sound so smart.

• Hold back when things are going well.
• Do more of the things that you haven’t quite mastered.
• Buy from the second and third best suppliers.
• Keep up capacity for the lower margin lower selling products.
• Restrict your best distributor from selling too much.

Remember Blockbuster?  There were Blockbuster stores everywhere fifteen years ago.  They did that one thing, rent physical videos through physical stores and did it so well that they drove out most of their competition.  But they were totally Concentrated.  When they were faced with a new competitor, Netflix, the CEO proposed changes to their business practices, including diversifying into online rentals.  Their board decided against going into a new lower margin product and fired the CEO.  Five years later, Blockbuster was toast.

Concentration risk is often strategic.

In the financial crisis, we found a new sort of concentration risk.  It was a network risk.  The banks were all highly concentrated in the financial sector – in exposure to other banks.  This network risk is now often called systemic risk.  But this risk is necessary because of the strategic choices of business models of the banks.  They all choose to do business in such a way to take up each other’s slack on a daily basis.  They all think that is much more efficient than operating with an irregular amount of slack resources.  In times running up to the financial crisis, the interdependency changed from just taking up each other’s overnight slack to some banks using that overnight facility from other banks to fund major fraction of their business activity.  (And woe is all that much of that business activity was fundamentally a loser. But that lack of underwriting by the banks of each other is a different story.)

Why is concentration risk so deadly?  The answer to that is pretty simple arithmetic.  If your conglomerate amounts to four similar sized separate divisions that do not interact so much, it is quite possible that if one of those businesses fails, that the conglomerate will be able to continue operating – wounded but fully able to operate the other three divisions.  But if your cousin’s venture has just one highly profitable, highly successful business, then his venture will either live or die with that one business.

In insurance, we see this concentration risk all of the time.  If you are an insurer that only writes business throughout the Pacific islands in the 1700’s, but you find that your best salesperson is on Easter Island and your highest margin product is business interruption insurance for the businesses that do the carving of the massive Moai statues.  So you do more and more business with your best salesperson selling your best product, until you are essentially a one product, one location insurer.  And then the last tree is used (or rats eat the roots).  All of your customers make claims at once.  You thought that you were diversified because you had 300 separate customers.  But those 300 customers all acted like just one when the trees were gone.

So diversification is not just about counting.  It is about understanding the differences or similarities of your risks.  And failure to understand those drivers will often lead to dangerous concentration.  Just ask those banks or that Easter Island insurer.

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Too Much Risk

Risk Management is all about avoiding taking Too Much Risk.

And when it really comes down to it, there are only a few ways to get into the situation of taking too much risk.

1. Misunderstanding the risk involved in the choices made and to be made by the organization
2. Misunderstanding the risk appetite of the organization
3. Misunderstanding the risk taking capacity of the organization
4. Deliberately ignoring the risk, the risk appetite and/or the risk taking capacity

So Risk Management needs to concentrate on preventing these four situations.  Here are some thoughts regarding how Risk Management can provide that.

1. Misunderstanding the risk involved in the choices made and to be made by an organization

This is the most common driver of Too Much Risk.  There are two major forms of misunderstanding:  Misunderstanding the riskiness of individual choices and Misunderstanding the way that risk from each choice aggregates.  Both of these drivers were strongly in evidence in the run up to the financial crisis.  The risk of each individual mortgage backed security was not seriously investigated by most participants in the market.  And the aggregation of the risk from the mortgages was misunderestimated as well.  In both cases, there was some rationalization for the misunderstanding.  The Misunderstanding was apparent to most only in hindsight.  And that is most common for misunderstanding risks.  Those who are later found to have made the wrong decisions about risk were most often acting on their beliefs about the risks at the time.  This problem is particularly common for firms with no history of consistently and rigorously measuring risks.  Those firms usually have very experienced managers who have been selecting their risks for a long time, who may work from rules of thumb.  Those firms suffer this problem most when new risks are encountered, when the environment changes making their experience less valid and when there is turnover of their experienced managers.  Firms that use a consistent and rigorous risk measurement process also suffer from model induced risk blindness.  The best approach is to combine analysis with experienced judgment.

2.  Misunderstanding the risk appetite of the organization

This is common for organizations where the risk appetite has never been spelled out.  All firms have risk appetites, it is just that in many, many cases, no one knows what they are in advance of a significant loss event.  So misunderstanding the unstated risk appetite is fairly common.  But actually, the most common problem with unstated risk appetites is under utilization of risk capacity.  Because the risk appetite is unknown, some ambitious managers will push to take as much risk as possible, but the majority will be over cautious and take less risk to make sure that things are “safe”.

3.  Misunderstanding the risk taking capacity of the organization

 This misunderstanding affects both companies who do state their risk appetites and companies who do not.  For those who do state their risk appetite, this problem comes about when the company assumes that they have contingent capital available but do not fully understand the contingencies.  The most important contingency is the usual one regarding money – no one wants to give money to someone who really, really needs it.  The preference is to give money to someone who has lots of money who is sure to repay.  For those who do not state a risk appetite, each person who has authority to take on risks does their own estimate of the risk appetite based upon their own estimate of the risk taking capacity.  It is likely that some will view the capacity as huge, especially in comparison to their decision.  So most often the problem is not misunderstanding the total risk taking capacity, but instead, mistaking the available risk capacity.

4.  Deliberately ignoring the risk, the risk appetite and/or the risk taking capacity of the organization

A well established risk management system will have solved the above problems.  However, that does not mean that their problems are over.  In most companies, there are rewards for success in terms of current compensation and promotions.  But it is usually difficult to distinguish luck from talent and good execution in a business about risk taking.  So there is a great temptation for managers to deliberately ignore the risk evaluation, the risk appetite and the risk taking capacity of the firm.  If the excess risk that they then take produces excess losses, then the firm may take a large loss.  But if the excess risk taking does not result in an excess loss, then there may be outsized gains reported and the manager may be seen as highly successful person who saw an opportunity that others did not.  This dynamic will create a constant friction between the Risk staff and those business managers who have found the opportunity that they believe will propel their career forward.

So get to work, risk managers.

Make sure that your organization

1. Understands the risks
2. Articulates and understands the risk appetite
3. Understands the aggregate and remaining risk capacity at all times
4. Keeps careful track of risks and risk taking to be sure to stop any managers who might want to ignore the risk, the risk appetite and the risk taking capacity

Ignoring a Risk

Ignoring is perhaps the most common approach to large but infrequent risks.

Most people think of a 1 in 100 year event as something so rare as it will never happen.

But just take a second and look at the mortality risk of a life insurer.  Each insured has on average around a 1 – 2 in 1000 likelihood of death in any one year.  However, life insurers do not plan for zero claims.  They plan for 1 -2 in 1000 of their policies to have a death claim in any one year.  No one thinks it odd that something with a 1-2 in 1000 likelihood happens hundreds of times in a year.  No one goes around scoffing at the validity of the model or likelihood estimate because such a rare event has happened.

But somehow, that seemingly totally simple minded logic escapes most people when dealing with other risks.  They scoff at how silly that it is that so many 1 in 100 events happen in a year.  Of course, they say, such estimated of likelihood MUST be wrong.

So they go forth ignoring the risk and ignoring the attempts at estimating the expected frequency of loss.  The cost of ignoring a low frequency risk is zero in most years.

And of course, any options for transferring such a risk will have both an expected frequency and an uncertainty charge built in.  Which make those options much too expensive.

The big difference is that a large life insurer takes on hundreds of thousands and in the largest cases, millions of exposures to the 1-2 in 1000 risks. Of course, the law of large numbers turns these individual ultra low frequency risks into a predictable claims pattern, in many cases one with a fairly tight distribution of possible claims.

But because they are ignored, no one tries to know how many of those 1 in 100 risks that we are exposed to.  But the statistics of 20 or 50 or 100 totally unrelated 1 in 100 risks is exactly the same as the life insurance math.

With 100 totally unrelated independent 1 in 100 risks, the chance of one or more turning into a loss in any one year is 63%!

And the most common reaction to the experience of a 1 in 100 event happening is to decide that the statistics are all wrong!

After Superstorm Sandy, NY Governor Cuomo told President Obama that NY “has a 100-year flood every two years now.”  Cuomo had been governor for less than two full years at that point.

The point is that organizations must go against the natural human impulse to separately decide to ignore each of their “rare” risks and realize that the likelihood of experiencing one of these rare events is not so rare, what is uncertain is which one.

Diversification of Risks

There are records showing that the power of diversification of risks was known to the ancients.  Investors who financed trading ships clearly favored taking fractions of a number of ships to owning all of a single ship.

The benefits of diversification are clear.  The math is highly compelling.  A portfolio of n risks of the same size A that truly independent have a volatility that is a fraction of the volatility of totally dependent risks.

Here is a simple example.  There is a 1 in 200 chance that a house will be totally destroyed by fire.  Company A writes an insurance policy on one $500,000 house that would pay for replacement in the event of a total loss.  That means that company A has a 1 in 200 chance of paying a $500,000 claim.  Company B decides to write insurance that pays a maximum of $50,000 in the event of a total loss.  How many policies do you think that Company B needs to write to have a 1 in 200 chance of paying $500,000 of claims if the risks are all totally independent and exactly as prone to claims as the $500k house?

The answer is an amazing 900 policies or 90 times as much insurance!

When an insurer is able to write insurance on independent risks, then with each additional risk, the relative volatility of the book of insurance decreases.  Optimal diversification occurs when the independent risks are all of the same size.  For insurers, the market is competitive enough that the company writing the 900 policies is not able to get a profit margin that is proportionate to the individual risks.  The laws of micro economics work in insurance to drive the profit margins down to a level that is at or below the level that makes sense for the actual risk retained.  This provides the most compelling argument for the price for insurance for consumers, they are getting most of the benefit of diversification through the competitive mechanism described above.  Because of this, things are even worse for the first insurer with the one policy.  To the extent that there is a competitive market for insurance for that one $500k house, that insurer will only be able to get a profit margin that is commensurate with the risk of a diversified portfolio of risks. 

It is curious to note than in many situations, both insurers and individuals do not diversify.  RISKVIEWS would suggest that may be explained by imagining that they either forget about diversification when making single decisions (they are acting irrationally), or that they are acting rationally and believe that the returns for the concentrated risk that they undertake are sufficiently large to justify the added risk.

The table below shows the degree to which individuals in various large companies are acting against the principle of diversification.

From a diversification point of view, the P&G folks above are mostly like the insurer above that writes the one $500k policy.  They may believe that P&G is less risky than a diversified portfolio of stocks.  Unlike the insurer, where the constraint on the amount of business that they can write is the 1/200 loss potential, the investor in this case is constrained by the amount of funds to be invested.  So if a $500k 401k account with P&G stock has a likelihood of losing 100% of value of 1/200, then a portfolio of 20 $25k positions in similarly risky companies would have a likelihood of losing 15% of value of 1/1000.  Larger losses would have much lower likelihood.

With that kind of math in its favor, it is hard to imagine that the holdings in employer stock in the 401ks represents a rational estimation of higher returns, especially not on a risk adjusted basis.

People must just not be at all aware of how diversification benefits them.

Or, there is another explanation, in the case of stock investments.  It can be most easily framed in terms of the Capital Asset Pricing Theory(CAPM) terms.  CAPM suggests that stock market returns can be represented by a market or systematic component (beta) and company specific component (alpha).  Most stocks have a significantly positive beta.  In work that RISKVIEWS has done replicating mutual find portfolios with market index portfolios, it is not uncommon for a mutual fund returns to be 90% explained by total market returns.  People may be of the opinion that since the index represents the fund, that everything is highly correlated to the index and therefore not really independent.

The simplest way to refute that thought is to show the variety of returns that can be found in the returns of the stocks in the major sectors:

The S&P 500 return for 2012 was 16%.  Clearly, all sectors do not have returns that are closely related to the index, either in 2012 or for any other period shown here.

Both insurance companies and investors can have a large number of different risks but not be as well diversified as they would think.  That is because of the statement above that optimal diversification results when all risks are equal.  Investors like the 401k participants with half or more of their portfolio in one stock may have the other half of their money in a diversified mutual fund.  But the large size of the single position is difficult to overcome.  The same thing happens to insurers who are tempted to write just one, or a few risks that are much larger than their usual business.  The diversification benefit of their large portfolio of smaller risks disappears quickly when they add just a few much larger risks.

Diversification is the universal power tool of risk management.  But like any other tool, it must be used properly to be effective.

This is one of the seven ERM Principles for Insurers

Where is the Metric for Diversity?

“What gets measured, gets managed.” – Peter Drucker

By gaetanlee, via Wikimedia Commons

It seems that while diversification is widely touted as the fundamental principle behind insurance and behind risk management in general, there is no general measure of diversity. So based upon Drucker’s rule of thumb RISKVIEWS would say that we all fail to manage diversity.

A measure of diversity would tell us when we take more similar risks and when we are taking more distinct risks.  But we do not even look.

This may well be another part of good financial management that has been stolen by the presumptions of financial economics.  Financial economics PRESUMES that we all have full diversification.  It tells us that we cannot get paid for our lack of diversification.

But those presumptions are untested and untestable, at least as long as we fail to even measure diversity.

Correlation is the best measure that we have and it is barely used.  For the most part, correlation is used mainly to look at macro portfolio effects on Economic Capital Models.  And it is not a particularly good measure of diversity anyway.  It actually only measures a certain type of statistical comovement of data.  For example, below is a chart that shows that equity market comovement is increasing.

But have the activities of the largest companies in those markets been converging?  Or is this picture just an artifact of the continuing Euro crisis? In either case, if we were looking at a measure of diversity, rather than just comovement, we might have an idea whether this chart makes any sense or not.

Many believe that they are protected by indexing.  That an index is automatically diverse.  But there is little guarantee of that.  Particularly for a market-value weighted index.  In fact, a market-values weighted index is almost guaranteed to have less diversity just when it is needed most.

For a clear indication of that look at the TSX index during the internet bubble Nortel represented 35% of the index!  Concentration increases risk.  In this case, the results were disastrous for any indexers. While Nortel stock rose in the Dot Com mania, buyers of the TSX index were holding a larger and larger fraction of their investment in a single stock.

We badly need a metric for diversity.

 

The Danger of Optimization

RISKVIEWS was recently asked “How do insurers Optimize Risk and Reward?”

The response was “That is dangerous. Why do you want to know that?” You see, a guru must always answer a question with a question. And in this case, RISKVIEWS was being treated as a guru.

Optimizing risk and reward is dangerous because it is done with a model.  Not all things that use a model are dangerous.  But Optimizing is definitely dangerous.

One definition of optimizing is

“to make as perfect as possible.”

Most often, optimization means taking maximum possible advantage of the diversification effect.  You will often hear someone talking about the ability to add risk without adding capital.  Getting a free ride on risk.

There are two reasons that optimizing ends up being dangerous…

1. The idea of adding risk without adding capital is a misunderstanding.  Adding risk always adds risk.  It may well not add to a specific measure of risk because of either size or correlation or both, but the risk is there.  The idea that adding a risk that is low correlation with the firm’s predominant risk is a free ride will sooner or later seep into the minds of the people who ultimately set the prices.  They will start to think that it is just fine to give away some or all of the risk premium and eventually to give up most of the risk margin because there is thought to be no added risk.  This free risk idea will also lead to possibly taking on too much of that uncorrelated risk.  More than one insurer has looked at an acquisition of a large amount of the uncorrelated risk where the price for the acquisition only makes sense with a diminished risk charge.  But with the acquisition, the risk becomes a major concentration of loss potential and suddenly, the risk charge is substantial.
2. In almost all cases, the best looking opportunities, based on the information that you are getting out of the model are the places where the model is in error, where the model is missing one or more of the real risks.  Those opportunities will look to have unusually fat risk premiums. To the insurer with the incorrect model, those look like extra margin.  This is exactly what happened with the super senior tranches of sub prime mortgage securities.  If you believed the standard assumption that house prices would never go down, there was no risk in the super senior, but they paid 5 – 10 bps more than a risk free bond.

The reliance on a model for optimization is dangerous.

That does not mean that the model is always dangerous.  The model only becomes dangerous when there is undue reliance is placed upon the exact accuracy of the model, without regard for model error and/or parameter uncertainty.

The proper use of the model is Risk Steering.  The model helps to determine the risks that should be held steady, which risks would be good to grow (as long as the environment stays the same as what the model assumes) and which risk to reduce.

Diversity and Resilience

Can’t we all just learn to “Get it Right”?

Just picture a ship with a large flat deck and thousands of passengers on the deck. The boat lists to one side and the passengers scurry to the other side to avoid going over the edge in the side that is dipping. Guess what happens? The boat now lists to the other side. Stabilizing the boat requires that everyone is spread about the entire deck. But since we do not necessarily know the exact spots where everyone needs to stand, some moving around makes sense. Just as long as everyone does not start moving together.

The world we live in is a much more complex and dynamic system than a ship at sea. We definitely do not know what is the safest course of action for everyone to take. We do know what hasn’t worked. We suspect that some of the things that we thought did work in the past were actually not good ideas. We do not know how to get the world to go backwards in time to when things were working best. In fact, they weren’t working best for someone then anyway.

Diversity is the most sensible approach when we do not know what will work. With a diversified approach it is quite possible that some will be doing the exact wrong thing, but at the same time, some will be doing the best thing for what comes next.

Only if we are certain of what will come next can we be sure to pick the best course. When too many people pick any single course of action, however, there often are unintended consequences.
Never before had mortgage loans in the US all gone down together, but when everyone started to increase the amount of leverage in the mortgage system, the leverage itself became the cause of massive correlation.

Ecological systems that are more diverse are more resilient. Human systems are the same.

Reporting on an ERM Program

In a recent post, RISKVIEWS stated six key parts to ERM.  These six ideas can act as the outline for describing an ERM Program.  Here is how they could be used:

1.  Risks need to be diversified.  There is no risk management if a firm is just taking one big bet.

REPORT: Display the risk profile of the firm.  Discuss how the firm has increased or decreased diversification within each risk and between risks in the recent past.  Discuss how this is a result of deliberate risk and diversification related choices of the firm, rather than just a record of what happened as a result of other totally unrelated decisions. 

2.  Firm needs to be sure of the quality of the risks that they take.  This implies that multiple ways of evaluating risks are needed to maintain quality, or to be aware of changes in quality.  There is no single source of information about quality that is adequate.

REPORT:  Display the risk quality of the firm.  Discuss how the firm has increased or decreased risk quality in the recent past and the reasons for those changes.  Discuss how risk quality is changing in the marketplace and how the firm maintains the quality of the risks that are chosen.

3.  A control cycle is needed regarding the amount of risk taken.  This implies measurements, appetites, limits, treatment actions, reporting, feedback.

REPORT:  The control cycle will be described in terms of who is responsible for each step as well as the plans for remediation should limits be breached.  A record of breaches should also be shown.  (Note that a blemish-less record might be a sign of good control or it might simply mean that the limits are ineffectively large.)  Emerging risks should have their own control cycle and be reported as well.

4.  The pricing of the risks needs to be adequate.  At least if you are in the risk business like insurers, for risks that are traded.  For risks that are not traded, the benefit of the risk needs to exceed the cost in terms of potential losses.

REPORT:  For General Insurance, this means reporting combined ratio.  In addition, it is important to show how risk margins are similar to market risk margins.  Note that products with combined ratios over 100% may or may not be profitable if the reserves do not include a discount for interest.  This is accomplished by mark-to-market accounting for investment risks.  Some insurance products have negative value when marked to market (all-in assets and liabilities) because they are sold with insufficient risk margins.  This should be clearly reported, as well as the reasons for that activity.  

5.  The firm needs to manage its portfolio of risks so that it can take advantage of the opportunities that are often associated with its risks.  This involves risk reward management.

REPORT:  Risk reward management requires determining return on risk for all activities as well as a planning process that starts with projections of such and a conscious choice to construct a portfolio of risks.  This process has its own control cycle.  The reporting for this control cycle should be similar to the process described above.  This part of the report needs to explain how management is thinking about the diversification benefits that potentially exist from the range of diverse risks taken.  

6.   The firm needs to provision for its retained risks appropriately, in terms of set asides (reserves or technical provisions) for expected losses and capital for excess losses.

REPORT:  Losses can be shown in four layers, expected losses, losses that decrease total profits, losses that exceed gains from other sources but that are less than capital and losses that exceed capital.  The likelihood of losses in each of those four layers should be described as well as the reasons for material changes.  Some firms will choose to report their potential losses in two layers, expected losses, losses that reach a certain likelihood (usually 99.5% in a year or similar likelihood).  However, regulators should have a high interest in the nature and potential size of those losses in excess of capital.  The determination of the likelihood of losses in each of the four layers needs to reflect the other five aspects of ERM and when reporting on this aspect of ERM, discussion of how they are reflected would be in order.  

Echo Chamber Risk Models

The dilemma is a classic – in order for a risk model to be credible, it must be an Echo Chamber – it must reflect the starting prejudices of management. But to be useful – and worth the time and effort of building it – it must provide some insights that management did not have before building the model.

The first thing that may be needed is to realize that the big risk model cannot be the only tool for risk management.  The Big Risk Model, also known as the Economic Capital Model, is NOT the Swiss Army Knife of risk management.  This Echo Chamber issue is only one reason why.

It is actually a good thing that the risk model reflects the beliefs of management and therefore gets credibility.  The model can then perform the one function that it is actually suited for.  That is to facilitate the process of looking at all of the risks of the firm on the same basis and to provide information about how those risks add up to make up the total risk of the firm.

That is very, very valuable to a risk management program that strives to be Enterprise-wide in scope.  The various risks of the firm can then be compared one to another.  The aggregation of risk can be explored.

All based on the views of management about the underlying characteristics of the risks. That functionality allows a quantum leap in the ability to understand and consistently manage the risks of the firm.

Before creating this capability, the risks of each firm were managed totally separately.  Some risks were highly restricted and others were allowed to grow in a mostly uncontrolled fashion.  With a credible risk model, management needs to face their inconsistencies embedded in the historical risk management of the firm.

Some firms look into this mirror and see their problems and immediately make plans to rationalize their risk profile.  Others lash out at the model in a shoot the messenger fashion.  A few will claim that they are running an ERM program, but the new information about risk will result in absolutely no change in risk profile.

It is difficult to imagine that a firm that had no clear idea of aggregate risk and the relative size of the components thereof would find absolutely nothing that needs adjustment.  Often it is a lack of political will within the firm to act upon the new risk knowledge.

For example, when major insurers started to create the economic capital models in the early part of this century, many found that their equity risk exposure was very large compared to their other risks and to their business strategy of being an insurer rather than an equity mutual fund.  Some firms used this new information to help guide a divestiture of equity risk.  Others delayed and delayed even while saying that they had too much equity risk.  Those firms were politically unable to use the new risk information to reduce the equity position of the group.  More than one major business segment had heavy equity positions and they could not choose which to tell to reduce.  They also rejected the idea of reducing exposure through hedging, perhaps because there was a belief at the top of the firm that the extra return of equities was worth the extra risk.

This situation is not at all unique to equity risk.   Other firms had the same experience with Catastrophe risks, interest rate risks and Casualty risk concentrations.

A risk model that was not an Echo Chamber model would be any use at all in these situation above. The differences between management beliefs and the model assumptions of a non Echo Chamber model would result in it being left out of the discussion entirely.

Other methods, such as stress tests can be used to bring in alternate views of the risks.

So an Echo Chamber is useful, but only if you are willing to listen to what you are saying.

Dissappointment

Michael Thompson often describes the situation where a person or group does not get the experience that they expect as Surprise. I have also heard that called Disappointment.

Probably Surprise is a better term.

What is going on is that people expect one sort of experience and get another.

In a recent published article, Ingram and Thompson describe the expectations of various environments as:

• Boom Environment – High Drift, Low Volatility
• Moderate Environment – Moderate Drift, Moderate Volatility
• Bust Environment – Negative Drift, Low Volatility
• Uncertain Environment – Unpredictable Drift, Unpredictable Volatility

With those descriptions, Surprise/Disappointment is easier to describe.  If you believe that the environment is in a Boom and the experience you get is moderate drift and volatility, then you will be surprised and probably disappointed.  And similarly, if you expect a Bust environment and you experience high drift, then you will certainly be Surprised, but probably not Disappointed.  Unless you were really counting on complaining and  are disappointed about good fortune spoiling that.

Surprise is very different for those expecting an Uncertain environment.  For them, it is surprising that they are able to notice any pattern, whether it be high, low or moderate drift and volatility.  They are expecting unpredictable results, a high volatility as well as a high volatility of volatility.  For them, a surprise would be if the experiences did have a reliable volatility.

The Surprise that many of us have been experiencing started out as a Disappointment.  We thought that home prices had a large positive drift and low volatility.  So as many of us started to count upon that expectation, the system reached its carrying capacity for home real estate.  Which is hard to imagine, since with the loans that were over 100% of value, people were being paid by the financial sector to take new homes.

Suddenly, house prices stopped rising.  Most stories about the financial crisis do not even try to give any explanation for that happening.  But it is easy to picture that everyone who was willing to move had already done so recently.  Even in a pay to take, there is a high personal time cost to move.  So the hot market encouraged anyone who might be willing to move and move a year or two or three earlier than they would have otherwise.  But not enough people were willing to do that year after year.  And not enough people were crazy enough to take out mortgages that they had absolutely no chance to pay back.  So the turnover faltered.  Prices simply stopped rising.  And the Surprise hit everyone.

After an extended period of freefall, the market has settled into a much longer period of uncertainty.  No discernable pattern to drift or to volatility.  There is a large and uneven volume of foreclosed real estate in the system.  It comes to market and disrupts prices.  Because the real estate market had relied upon a rather primitive price discovery mechanism, the foreclosures are very disruptive to the pricing of non-foreclosed housing.  This is a major factor in the level of uncertainty of housing and it ripples through the entire financial system and the entire economy.

With this uncertainty, people who are expecting any of the three other patterns of risk are irregularly Surprised, and often Disappointed.  As there are more and more disappointments, more and more people shift their coping strategy to one that makes sense in an Uncertain economy, the strategy of Diversification.  That might sound to be a good thing, but in practice, it ends up meaning avoiding any large or lengthy commitments.  It means a slow down in basic investment and usually a deferral of any of the major investments that would start to fuel the next positive economic cycle.

This Uncertain cycle will end slowly because of the immense amount of extra home real estate that is still in the foreclosure pipeline.

Such cycles usually end when the flip side of the process described above that drove the stoppage in the real estate boom.  What stopped the boom was that people wore out of moving up in housing.  What will stop the Uncertain market will be that people will wear out of not changing houses.  The people who have had one more child will be fed up with the crowding in their smaller house and the people whose kids have moved away will get fed up with maintaining more house than they need.  The people who do well enough to afford a bigger and better house will be fed up with waiting for things to settle down.  And when that happens to enough people, the backlog of existing real estate will finally sell down and a new boom will start again.

And people who had adapted to uncertainty will be Surprised, but not disappointed that their house again finally starts to appreciate.

What’s Next?

Turbulent Times are Next.

At BusinessInsider.com, a feature from Guillermo Felices tells of 8 shocks that are about to slam the global economy.

#1 Higher Food Prices in Emerging Markets

#2 Higher Interest Rates and Tighter Money in Emerging Markets

#3 Political Crises in the Middle East

#4 Surging Oil Prices

#5 An Increase in Interest Rates in Developed Markets

#6 The End of QE2

#7 Fiscal Cuts and Sovereign Debt Crises

#8 The Japanese Disaster

How should ideas like these impact on ERM systems?  Is it at all reasonable to say that they should not? Definitely not.

These potential shocks illustrate the need for the ERM system to be reflexive.  The system needs to react to changes in the risk environment.  That would mean that it needs to reflect differences in the risk environment in three possible ways:

1. In the calibration of the risk model.  Model assumptions can be adjusted to reflect the potential near term impact of the shocks.  Some of the shocks are certain and could be thought to impact on expected economic activity (Japanese disaster) but have a range of possible consequences (changing volatility).  Other shocks, which are much less certain (end of QE2 – because there could still be a QE3) may be difficult to work into model assumptions.
2. With Stress and Scenario Tests – each of these shocks as well as combinations of the shocks could be stress or scenario tests.  Riskviews suggest that developing a handful of fully developed scenarios with 3 or more of these shocks in each would be the modst useful.
3. In the choices of Risk Appetite.  The information and stress.scenario tests should lead to a serious reexamination of risk appetite.  There are several reasonable reactions – to simply reduce risk appetite in total, to selectively reduce risk appetite, to increase efforts to diversify risks, or to plan to aggressively take on more risk as some risks are found to have much higher reward.

The last strategy mentioned above (aggressively take on more risk) might not be thought of by most to be a risk management strategy.  But think of it this way, the strategy could be stated as an increase in the minimum target reward for risk.  Since things are expected to be riskier, the firm decides that it must get paid more for risk taking, staying away from lower paid risks.  This actually makes quite a bit MORE sense than taking the same risks, expecting the same reward for risks and just taking less risk, which might be the most common strategy selected.

The final consideration is compensation.  How should the firm be paying people for their performance in a riskier environment?  How should the increase in market risk premium be treated?

See Risk adjusted performance measures for starters.

More discussion on a future post.

Risk Management Success

Many people struggle with clearly identifying how to measure the success of their risk management program.

But they really are struggling with is either a lack of clear objectives or with unobtainable objectives.

Because if there are clear and obtainable objectives, then measuring success means comparing performance to those objectives.

The objectives need to be framed in terms of the things that risk management concentrates upon – that is likelihood and severity of future problems.

The objectives need to be obtainable with the authority and resources that are given to the risk manager.  A risk manager who is expected to produce certainty about losses needs to either have unlimited authority or unlimited budget to produce that certainty.

The most difficult part of judging the success of a risk management program is when those programs are driven by assessments of risk that end up being totally insufficient.  But again the real answer to this issue is authority and budget.  If the assumptions of the model are under the control of the risk manager, that is totally under the risk manager’s control, then the risk manager would be prudent to incorporate significant amounts of margin either into the model or into the processes that use the model for model risk.  But then the risk manager is incented to make the model as conservative as their imagination can make it.  The result will be no business – it will all look too risky.

So a business can only work if the model assumptions are the join responsibility of the risk manager and the business users.

But there are objectives for a risk management program that can be clear and obtainable.  Here are some examples:

1. The Risk Management program will be compliant with regulatory and/or rating agency requirements
2. The Risk Management program will provide the information and facilitate the process for management to maintain capital at the most efficient level for the risks of the firm.
3. The Risk Management program will provide the information and facilitate the process for management to maintain profit margins for risk (pricing in insurance terms) at a level consistent with corporate goals.
4. The Risk Management program will provide the information and facilitate the process for management to maintain risk exposures to within corporate risk tolerances and appetites.
5. The Risk Management program will provide the information and facilitate the process for management and the board to set and update goals for risk management and return for the organization as well as risk tolerances and appetites at a level and form consistent with corporate goals.
6. The Risk Management program will provide the information and facilitate the process for management to avoid concentrations and achieve diversification that is consistent with corporate goals.
7. The Risk Management program will provide the information and facilitate the process for management to select strategic alternatives that optimize the risk adjusted returns of the firm over the short and long term in a manner that is consistent with corporate goals.
8. The Risk Management program will provide information to the board and for public distribution about the risk management program and about whether company performance is consistent with the firm goals for risk management.

Note that the firm’s goals for risk management are usually not exactly the same as the risk management program’s goals.  The responsibility for achieving the risk management goals is shared by the management team and the risk management function.

Goals for the risk management program that are stated like the following are the sort that are clear, but unobtainable without unlimited authority and/or budget as described above:

X1  The Risk Management program will assure that the firm maintains profit margins for risk at a level consistent with corporate goals.

X2  The Risk Management program will assure that the firm maintains risk exposures to within corporate risk tolerances and appetites so that losses will not occur that are in excess of corporate goals.

X3  The Risk Management program will assure that the firm avoids concentrations and achieve diversification that is consistent with corporate goals.

X4  The Risk Management program will assure that the firm selects strategic alternatives that optimize the risk adjusted returns of the firm over the short and long term in a manner that is consistent with corporate goals.

The worst case situation for a risk manager is to have the position in a firm where there are no clear risk management goals for the organization (item 4 above) and where they are judged on one of the X goals but which one that they will be judged upon is not determined in advance.

Unfortunately, this is exactly the situation that many, many risk managers find themselves in.

Eggs and Baskets

Andrew Carnegie once famously said

“put all your eggs in one basket. and then watch that basket”

It seems impossible on first thought to think of that as a view consistent with risk management.  But Carnegie was phenomenally successful.  Is it possible that he did that flaunting risk management?

Garry Kasparov – World Chess Champ (22 years) put it this way…

“You have to rely on your intuition.  My intuition was wrong very few times.”

George Soros has said that he actually gets an ache in his back when the market is about to turn, indicating that he needs to abruptly change his strategy.

Soros, Kasparov, Carnegie are not your run of the mill punters.  They each had successful runs for many years.

My theory of their success is that the intuition of Kasparov actually does take into account much more than the long hard careful consideration of a middling chess master.  Carnegie and Soros also knew much more about their markets than any other person alive in their time.

While they may not have consciously been following the rules, they were actually incorporating all of the drivers of those rules into their decisions.  Most of those rules are actually “heuristics” or shortcuts that work as long as things are what they have been but are not of much use when things are changing.  In fact, those rules may be what is getting one into trouble during shifts in the world.

Risk models embody an implicit set of rules about how the market work.  Those models fail when the market fails to conform to the rules embedded in the model.  That is when things change, when your thinking needs to transcend the heuristics.

So where does that leave the risk manager?

The insights of the ultra successful types that are cited above can be seen to refute the risk management approach, OR they can be seen as a goal for risk managers.

The basket that Carnegie was putting all of his eggs into was steel.  His insight about steel was correct, but his statement about eggs and baskets is not particularly applicable to situations less transformational than steel.  It is the logic that many applied during the dot com boom, much to their regret in 2001/2002.

The risk manager should look at statements and positions like those above as levels of understanding to strive for.  If the risk managers work starts and remains a gigantic mass of data and risk positions without ever reaching any insights about the underlying nature of the risks that are at play, then something is missing.

Perhaps the business that the risk manager works for is one that by choice and risk tolerance insists on plodding about the middle of the pack in risk.

But the way that the risk manager can add the most value is when they are able to provide the insights about the baskets that can handle more eggs.  And can start to have intuitions about risks that are reliable and perhaps are accompanied by unmistakable physical side effects.

Diversification as ERM

In the recent post, Rational Adaptability, four types of ERM programs are mentioned. One of those four types of ERM is Diversification.

The fourth type of ERM program focuses on Diversification.

Modern practitioners may not agree that a program of Diversification IS in any sense a risk management program.  But in fact it has been one of the most successful risk management programs.

Think about it.  Dollar Cost Averaging is fundamentally a Diversification based risk management program.  The practitioner is admitting that at any point in time, they do not know which risk is better or worse than another.  So they rebalance to eliminate the concentration that has crept into their portfolio.

A diversification risk strategy would also mean taking very different risks.  Firms that focus on a true Diversification strategy will be regularly moving into entirely new businesses.  They are not seeking the mathematical diversification of the Managers with their Risk Steering that tries to take advantage of similar risks that are not totally correlated.  Firms that follow the Diversification strategy want risks that are totally unrelated.  Soap and machine parts.  Their business choices may seem totally insane to the tidy Managers.

Diversification can be shown to provide two benefits for the firm that practices it.  First, they will seek to avoid having too much at risk in any one situation or company.  So avoiding concentration is their prime directive.  Second, there is an upside benefit as well.  Since they are involved in many different markets, they feel that they are likely to be in at least one and possibly two hot products or markets at any one time.  Unsuccessful practitioners of this strategy will find that they have found a way to buy into different risks that are all duds at the same time.

The practitioners of this strategy will also tend to adopt the same sort of approach to the day to day work of their risk management program.  That would be the “high attention, low delegation” approach.  The conglomerates that operate in this manner will have frequent meetings between the managers and the people at the top of the conglomerate, possibly even with the top person.  Warren Buffett (Berkshire Hathaway) and Jack Welsh (GE) are two examples of this high touch style as is Hank Greenberg (AIG).

Seems pretty simple.  Mix it up and pay attention.

A few firms have managed to combine the high tech economic capital modeling approach with a Diversification ERM system.  In those firms, they have strict concentration limits requiring that at most a small percentage of their economic capital ever be from any one risk.  One such firm will never take on any large amount of any one risk unless they are able to grow all of their other risks.

This post is a part of the Plural Rationalities and ERM project.

It’s Usually the Second Truck

In many cases, companies survive the first bout of adversity.

It is the second bout that kills.

And more often than not, we are totally unprepared for that second hit.

Totally unprepared because of how we misunderstand statistics.

First of all, we believe that large loss events are unlikely and two large loss events are extremely unlikely.  So we decide not to prepare for the extremely unlikely event that we get hit by two large losses at the same time.  And in this case, “at the same time” may mean in subsequent years.  Some who look at correlation, only use an arbitrary calendar year split out of experience data.  So that they would consider losses in the third and fourth quarter to be happening at the same time but fourth quarter and first quarter of the next year would be considered different periods and therefore might show low correlations!

Second, we fail to deal with our reduced capacity immediately after a major loss event.  We still think of our capacity as it was before the first hit.  A part of our risk management plans for a major loss event should have been to immediately initiate a process to rationalize our risk exposures with our newly reduced capacity.  This may in part be due to the third issue.

Third, we misunderstand that the fact of the first event does not reduce the likelihood of the other risk events.  Those joint probabilities that made the dual event, no longer apply.  In fact, with the reduced capacity, the type of even that would incapacitate the firm has suddenly become much more likely.

Most companies that experience one large loss event do not experience a second shortly thereafter, but many companies that fail do.

So if your interest is to reduce the likelihood of failure, you should consider the two loss event situation as a scenario that you prepare for.

But those preparations will present a troubling alternative.  If, after the first major loss event, the actions needed include a sharp reduction in retained risk position, that will severely reduce the likelihood of growing back capacity.

Management is faced with a dilemma – that is two choices, neither of which are desirable.   But as with most issues in risk management, better to face those issues in advance and to make a reasoned plan, rather than looking away and hoping for the best.

But on further reflection, this issue can be seen to be one of over concentration in a single risk.  Some firms have reacted to this whole idea by setting their risk tolerance such that any one loss event will be limited to their excess capital.  Their primary strategy for this type of concentration risk is in effect a diversification strategy.

Take CARE in evaluating your Risks

Risk management is sometimes summarized as a short set of simply stated steps:

1. Identify Risks
2. Evaluate Risks
3. Treat Risks

There are much more complicated expositions of risk management.  For example, the AS/NZ Risk Management Standard makes 8 steps out of that. 

But I would contend that those three steps are the really key steps. 

The middle step “Evaluate Risks” sounds easy.  However, there can be many pitfalls.  A new report [CARE] from a working party of the Enterprise and Financial Risks Committee of the International Actuarial Association gives an extensive discussion of the conceptual pitfalls that might arise from an overly narrow approach to Risk Evaluation.

The heart of that report is a discussion of eight different either or choices that are often made in evaluating risks:

1. MARKET CONSISTENT VALUE VS. FUNDAMENTAL VALUE 
2. ACCOUNTING BASIS VS. ECONOMIC BASIS         
3. REGULATORY MEASURE OF RISK    
4. SHORT TERM VS. LONG TERM RISKS          
5. KNOWN RISK AND EMERGING RISKS        
6. EARNINGS VOLATILITY VS. RUIN    
7. VIEWED STAND-ALONE VS. FULL RISK PORTFOLIO       
8. CASH VS. ACCRUAL 

The main point of the report is that for a comprehensive evaluation of risk, these are not choices.  Both paths must be explored.

The Future of Risk Management – Conference at NYU November 2009

Some good and not so good parts to this conference.  Hosted by Courant Institute of Mathematical Sciences, it was surprisingly non-quant.  In fact several of the speakers, obviously with no idea of what the other speakers were doing said that they were going to give some relief from the quant stuff.

Sad to say, the only suggestion that anyone had to do anything “different” was to do more stress testing.  Not exactly, or even slightly, a new idea.  So if this is the future of risk management, no one should expect any significant future contributions from the field.

There was much good discussion, but almost all of it was about the past of risk management, primarily the very recent past.

Here are some comments from the presenters:

• Banks need regulator to require Stress tests so that they will be taken seriously.
• Most banks did stress tests that were far from extreme risk scenarios, extreme risk scenarios would not have been given any credibility by bank management.
• VAR calculations for illiquid securities are meaningless
• Very large positions can be illiquid because of their size, even though the underlying security is traded in a liquid market.
• Counterparty risk should be stress tested
• Securities that are too illiquid to be exchange traded should have higher capital charges
• Internal risk disclosure by traders should be a key to bonus treatment.  Losses that were disclosed and that are within tolerances should be treated one way and losses from risks that were not disclosed and/or that fall outside of tolerances should be treated much more harshly for bonus calculation purposes.
• Banks did not accurately respond to the Spring 2009 stress tests
• Banks did not accurately self assess their own risk management practices for the SSG report.  Usually gave themselves full credit for things that they had just started or were doing in a formalistic, non-committed manner.
• Most banks are unable or unwilling to state a risk appetite and ADHERE to it.
• Not all risks taken are disclosed to boards.
• For the most part, losses of banks were < Economic Capital
• Banks made no plans for what they would do to recapitalize after a large loss.  Assumed that fresh capital would be readily available if they thought of it at all.  Did not consider that in an extreme situation that results in the losses of magnitude similar to Economic Capital, that capital might not be available at all.
• Prior to Basel reliance on VAR for capital requirements, banks had a multitude of methods and often used more than one to assess risks.  With the advent of Basel specifications of methodology, most banks stopped doing anything other than the required calculation.
• Stress tests were usually at 1 or at most 2 standard deviation scenarios.
• Risk appetites need to be adjusted as markets change and need to reflect the input of various stakeholders.
• Risk management is seen as not needed in good times and gets some of the first budget cuts in tough times.
• After doing Stress tests need to establish a matrix of actions that are things that will be DONE if this stress happens, things to sell, changes in capital, changes in business activities, etc.
• Market consists of three types of risk takers, Innovators, Me Too Followers and Risk Avoiders.  Innovators find good businesses through real trial and error and make good gains from new businesses, Me Too follow innovators, getting less of gains because of slower, gradual adoption of innovations, and risk avoiders are usually into these businesses too late.  All experience losses eventually.  Innovators losses are a small fraction of gains, Me Too losses are a sizable fraction and Risk Avoiders often lose money.  Innovators have all left the banks.  Banks are just the Me Too and Avoiders.
• T-Shirt – In my models, the markets work
• Most of the reform suggestions will have the effect of eliminating alternatives, concentrating risk and risk oversight.  Would be much safer to diversify and allow multiple options.  Two exchanges are better than one, getting rid of all the largest banks will lead to lack of diversity of size.
• Problem with compensation is that (a) pays for trades that have not closed as if they had closed and (b) pay for luck without adjustment for possibility of failure (risk).
• Counter-cyclical capital rules will mean that banks will have much more capital going into the next crisis, so will be able to afford to lose much more.  Why is that good?
• Systemic risk is when market reaches equilibrium at below full production capacity.  (Isn’t that a Depression – Funny how the words change)
• Need to pay attention to who has cash when the crisis happens.  They are the potential white knights.
• Correlations are caused by cross holdings of market participants – Hunts held cattle and silver in 1908’s causing correlations in those otherwise unrelated markets.  Such correlations are totally unpredictable in advance.
• National Institute of Financa proposal for a new body to capture and analyze ALL financial market data to identify interconnectedness and future systemic risks.
• If there is better information about systemic risk, then firms will manage their own systemic risk (Wanna Bet?)
• Proposal to tax firms based on their contribution to gross systemic risk.
• Stress testing should focus on changes to correlations
• Treatment of the GSE Preferred stock holders was the actual start of the panic.  Leahman a week later was actually the second shoe to drop.
• Banks need to include variability of Vol in their VAR models.  Models that allowed Vol to vary were faster to pick up on problems of the financial markets.  (So the stampede starts a few weeks earlier.)
• Models turn on, Brains turn off.

Diversification Causes Correlations

The Bond insurers diversified out of their niche of municpal bonds into real estate backed securities and suddenly these two markets that previously seemed to have low correlation were highly correlated as the sub prime crisis brought down the Bond Insurers and their problems rippled into the Muni market.

(I say seemed uncorrelated, but of course they are highly dependent since a high fraction of municipal incomes comes from taxes relating to real estate values.  That is a major problem with the statistical idea of correlation – statistical approaches must never be used uncritically.)

But the point of the first paragraph above is that interdependencies do not have to come from the fundamentals of two markets – that is to come from common drivers of risk.  Interdependencies especially of market prices can and often do come from common ownership of securities from different markets.  The practice of holding risks from seemingly unrelated risks or markets is generally thought to create better risk adjusted results because of diversification.

But the perverse truth is that like many things in real economics (not book economics) the more people use this rule, the less likely it is that it will work.

There are several reasons for this:

• When a particularly large organization diversifies, their positions in every market will be large.  For anyone to get the most benefit from diversification, they need to have positions in each diversifying risk that are similar in size.  Since even the largest firms had to have started somewhere, they will have a primary business that is very large and so will seek to take very large positions in the diversifying markets to get that diversifying benefit.  So there ends up being some very significant specific risk of a sudden change in correlation if that large firm runs into trouble.  These events only ever happen once to a firm so there is never, ever any historical correlations to be found.  But if you want to avoid this diversification pitfall, it pays to pay attention to where the largest firms operate and be cautious in assuming diversification benefits where THEY are the correlating factor.
• When large numbers of firms use the same correlation factors (think Solvency II), then they will tend to all try to get into the same diversifying lines of business where they can get the best diversification benefits.  This results in both the specific risk factor mentioned above and to a pricing pressure on those markets.  Those risks with “good” diversification will tend to price down to their marginal cost, which will be net of the diversification benefit.  The customers will end up getting the advantage of diversification.
• Diversification is commonly believed to eliminate risk.  THis is decidedly NOT TRUE.  No risk is destroyed via diversification.  All of the losses that were going to happen do happen, unaffected by diversification.  What diversification hopes to accomplish is to make this losses relatively less important and more affordable because some risk taking activity is likely to be showing gains while others is showing losses.  So people who thought that because they were diversified, that they had less risk, were willing to go out and take more risk.  This effect causes more of the stampede for the exits behaviors when times get tough and the losses that were NOT destroyed by diversification occur.
• The theory of a free lunch with diversification encourages firms who are inexperienced with managing a risk to take on that risk because their diversification analysis says that it is “free”.  These firms will often help to drive down prices for everyon, sometimes to the point that they do not make money from their “diversification play” even in good years.  Guess what?  All that fancy correlation math does not work as advertised if the expected earnings from a “diversifying risk” is negative.  These is no diversification from a losing operation because it has no gains to offset the losses of other risks.

Coverage and Collateral

I thought that I must be just woefully old fashioned. 

In my mind the real reason for the financial crisis was that bankers lost sight of what it takes to operating a lending business. 

There are really only two simple factors that MUST be the first level of screen of borrowers:

1.  Coverage

2.  Collateral

And banks stopped looking at both.  No surprise that their loan books are going sour.  There is no theory on earth that will change those two fundamentals of lending. 

The amount of coverage, which means the amount of income available to make the loan payments, is the primary factor in creditworthiness.  Someone must have the ability to make the loan payments. 

The amount of collateral, which means the assets that the lender can take to offset any loan loss upon failure to repay, is a risk management technique that insulates the lender from “expected” losses. 

Thinking has changed over the last 10 – 15  years with the idea that there was no need for collateral, instead the lender could securitize the loan, atomize the risk, thereby spreading the specific risk to many, many parties, thereby making it inconsequential to each party.  Instead of collateral, the borrower would be charged for the cost of that securitization process. 

Funny thing about accounting.  If the lender does something very conservative (in terms of current standards) and requires collateral that would take up the first layer of loss then there will be no impact on P&L of this prudence. 

If the lender does not require collateral, then this charge that the borrower pays will be reported as profits!  The Banks has taken on more risk and therefore can show more profit! 

EXCEPT, in the year(s) when the losses hit! 

What this shows is that there is a HUGE problem with how accounting systems treat risks that have a frequency that is longer than the accounting period!  In all cases of such risks, the accounting system allows this up and down accounting.  Profits are recorded for all periods except when the loss actually hits.  This account treatment actually STRONGLY ENCOURAGES taking on risks with a longer frequency. 

What I mean by longer frequency risks, is risks that expect to show a loss, say once every 5 years.  These risks will all show profits in four years and a loss in the others.  Let’s say that the loss every 5 years is expected to be 10% of the loan, then the charge might be 3% per year in place of collateral.  So the banks collect the 3% and show results of 3%, 3%, 3%, 3%, (7%).  The bank pays out bonuses of about 50% of gains, so they pay 1.5%, 1.5%, 1.5%, 1.5%, 0.  The net result to the bank is 1.5%, 1.5%, 1.5%, 1.5%, (7%) for a cumulative result of (1%).  And that is when everything goes exactly as planned! 

Who is looking out for the shareholders here?  Clearly the deck is stacked very well in favor of the employees! 

What it took to make this look o.k. was an assumption of independence for the loans.  If the losses are atomized and spread around eliminating specific risk, then there would be a small amount of these losses every year, the negative net result that is shown above would NOT happen because every year, the losses would be netted against the gains and the cumulative result would be positive. 

Note however, that twice above it says that the SPECIFIC risk is eliminated.  That leaves the systematic risk.  And the systematic risk has exactly the characteristic shown by the example above.  Systematic risk is the underlying correlation of the loans in an adverse economy. 

So at the very least, collateral should be resurected and required to the tune of the systematic losses. 

Coverage… well that seems so obvious it doed not need discussion.  But if you need some, try this.

ERM Role in Implementing a Winning Acquisition Strategy (2)

From Mike Cohen

Part 2

(Part 1)

Execution of an Acquisition Strategy Goes Through Several Stages and Involves Many and Varied Complex, Interrelated Business Issues (they must be performed well, and there are numerous junctures where things can go awry … suggesting that many potential risks need to be addressed, and more effectively than they typically are)

– Defining the business case

– Considering the corporate strategy and the resulting (ideally enhanced) business model

* Fit vs. conflict

* Synergies; potential synergies are frequently overstated

* Diversification

– Assessing market opportunities and competitive dynamics

* Products

* Distribution

* Markets/segments

* Brand/reputation

– Financial impact

* Earnings

* Capital

* Economic value

* Assessment of an appropriate price

– Investments

* Asset classes

* Loss positions

* Liquidity

– Operational fit (or problematically, the need to ‘fix’ the target’s operations)

* Technology

* Administration

* Core competencies

– Integrating the target: melding the two organizations so that they can perform effectively together, while mitigating risk, volatility and confusion to the greatest extent possible

Q: Is an acquisition strategy a core competency of your company … can you execute such a transaction successfully?

Due Diligence Performed on any Acquisition Target: A Critical Activity on the Strategic and Tactical Levels

– Valuation, impact on future financial results

– Management/staff

– Profitability of new (potential), existing business

– Competitive market position; product management, distribution capabilities

– Synergies: strategic, operational, financial, market/product/distribution

– Investments

– Expense structure (opportunities for increasing efficiency and/or cost reduction)

– Technological capabilities or possible lack of fit

– Contractual obligations

– Areas of risk or uncertainty

Many acquisitions are viewed retrospectively as failures. A lack of accurate evaluation of/objectivity about prospective acquisition targets (using ‘rose-colored glasses’ leads many (most?) acquirers to have unrealizable goals for their transactions, and as a consequence the end results (strategic, financial or otherwise) do not meet expectations.  There is a considerable level of risk to the acquirer if the due diligence process is not conducted with sufficient accuracy and objectivity.

Evaluating the Capabilities of an Organization to Execute Successful Acquirer: Being a successful acquirer requires a number of skills and mind-sets:

– Knowing one’s own corporate vision, mission, strategy and operating model, and how  acquisitions complement them

– Having a disciplined approach: evaluating fit, paying an appropriate price based on economic value, both current and future

– Performing careful, accurate and objective due diligence on the target company and management counterparts … caveat emptor!

– Executing timely, well planned and orchestrated integration activities focus on achieving a favorable operational model and attaining a satisfactory level of cost savings; a number of  companies that acquired positive reputations as acquirers were in fact poor at integrating their acquisition(s), causing their organizations to implode

– Managing the staffs and corporate cultures sensitively. There is considerable amount of research that identifies human resource related issues as the most prevalent causes for acquisition failure; personalities (egos), conflicting management styles and cultures, and different compensation structures are all too common. Proactive conflict resolution is critical to steer the resulting entity past these pratfalls. Open and continuous communication is critical.

The General Lack of Success from Acquisitions is Attributed to Mismanaging One or More Critical Aspects of the Transaction with Material Risk

Strategy

– Incompatible cultures

– Incompatible business models

– Synergy non-existent or overestimated

Due Diligence

– Acquirer overpaid

– Foreseeable problems overlooked

– Acquired firm too unhealthy

– Overlooking aspects of the target where excessive divestiture or liquidation might be required

Implementation

– Inability to manage target

– Inability to implement change

– Clash of management styles/egos

Conclusion

An acquisition is arguably the most difficult business endeavor a company can undertake. This report discussed a considerable number of elements involved in acquisition activity; they are all complex, and there are many junctures in the process where a number of these elements can go awry or reach adverse conclusions, either derailing transactions that could have otherwise been successful or ‘proving’ the efficacy of transactions that upon closer scrutiny could not have succeeded and should have been avoided.

Studies of acquisition activity across all industries (not just insurance) have consistently  found that approximately two-thirds of these transactions yielded unsatisfactory results. One could observe that this is not surprising, as there are so many steps along the way that can turn into insurmountable roadblocks. Considering the myriad of factors that must be performed well, it is clear than sound, pragmatic risk management throughout the process and beyond is critical in order for acquisition activity to succeed