This article was first published in Who’s Who Legal: Insurance & Reinsurance, May, 2014.
"The avalanche of regulation following the latest financial crisis is a case in point. Somewhere in there are good progressive steps; however, they risk being swamped by information overload and large volumes of prescriptive rules that miss the mark and divert resources away from the core issues."
It is a cliché that generals fight the last war and policymakers solve the last crisis – the implication being that taking effective steps to solve a crisis is not enough to handle the next one that arises. I’m not so sure.
Tackling the Causes of a Crisis
It seems that the root causes of different financial crises have a lot in common, even if the specific manifestation of each crisis is different. Therefore, tackling the root causes of one crisis would go a long way towards avoiding another. My concern is that the standard reaction to crises – stacking new regulation on top of old – may do no more than address symptoms and, in the process, create new problems.
The avalanche of regulation following the latest financial crisis is a case in point. Somewhere in there are good progressive steps; however, they risk being swamped by information overload and large volumes of prescriptive rules that miss the mark and divert resources away from the core issues.
The drivers of every financial crisis are rooted in human behaviour – more specifically, in the factors that drive human behaviour. Until regulation prioritises understanding and tackling these drivers, financial crises will roll around with disheartening regularity. These drivers include opportunism, irrationality and fear. They almost invariably manifest themselves in warning signs that, in retrospect, seem clear. This article examines some of the causes of crises, along with the good – and not so good – policy responses.
Some of the measures taken in the wake of the latest financial crisis recognise the need to address the drivers of behaviour. For example, there is a recognition that inappropriate incentive schemes and absence of risk for key participants can encourage unhealthy opportunistic behaviour.
It makes perfect sense to tackle incentive schemes that encourage short-term risk taking at the expense of long-term stability. It is now almost 30 years since I was introduced to the world of insurance law following the collapse of an Irish insurer. A contributory factor in that collapse was an ill-conceived executive incentive scheme. It is well past time to address that issue comprehensively.
There is also some sense in ensuring that certain key participants in a market retain risk. It is now well accepted that the “originate to distribute” model (that resulted in institutions originating mortgages purely to distribute all risk through securitisation) was a contributory factor to the financial crisis. However, simply requiring risk retention is a crude instrument and may well miss the mark. For example, should an insurer fronting a product developed and administered by a reinsurer be required to retain risk in the business? That is unlikely to achieve anything other than increased cost. If retaining risk is a solution to imprudent behaviour, then, at the very least, the requirement should be more refined. It should focus on ensuring that the person with the expertise and opportunity to evaluate risk in the product retains an incentive to act prudently. Even then, the minimum level of risk retention needed to encourage prudent behaviour is not at all clear. This must be balanced carefully with the need for institutions to have flexibility to hedge risks. Solutions like risk retention must address unhealthy opportunistic behaviour, not leave risk unnecessarily in institutions.
There are limits to what prescriptive regulation can do. The current fashion in regulatory frameworks is to encourage the development of complex mathematical models and embed these in banking and insurance businesses. These models are designed to measure and price risk based on plausible and stressed scenarios that may emerge in future. The aim is to ensure that the financial institutions can withstand the impact of those risks. However to be perfect, models would have to predict the future – which they manifestly cannot do. Therefore, they have limitations and within those limitations lie dangers arising from complexity, opacity and human nature.
A particular challenge for models is predicting irrational behaviour. Nursing losses from the South Sea bubble, Isaac Newton is reputed to have said that he could “calculate the movement of the stars but not the madness of men”.
If models cannot predict the “madness of men”, can boards of directors and regulators? They can certainly look for warning signs.
It is interesting how obvious the causes of a crisis are, after the event. At the risk of oversimplifying, the De LaRosiere report to the European Commission on the causes of the last crisis identified the rapid growth in mortgage backed securities as one significant contributor. Viewed in retrospect, the warning signs were clear. As money supply increased, returns on US treasury stock reduced. Asset managers needed a higher yielding alternative to treasuries. The rated mortgage backed security came into its own. However, as demand increased, asset quality deteriorated without a commensurate adjustment of ratings. Whatever the failings of rating agencies, rapid growth in any asset class should have raised concerns among financial institutions, policy makers and regulators. But it didn’t.
Were the behaviours driving the growth in mortgage-backed securities fundamentally different to the irrational exuberance that drove 18th century investors to buy stock in the South Sea company? Commentators will be quick to point out numerous differences. However, these are differences in the manifestation of irrationality, not in the fundamental driver for the irrational behaviour. Modern investors no more questioned the fundamentals of mortgage-backed securities than Isaac Newton and his counterparts did the fundamentals of the South Sea Company’s business. Assuming that at least some of the investors who lost out in the ensuing crashes were rational and intelligent people, the conditions that create bubbles must also create conditions for a perverse rationality that persuades otherwise clever people to do something that (viewed in retrospect, of course) is very foolish.
Perhaps it’s as simple as Warren Buffet’s observation that nothing sedates rationality like large doses of effortless money. This can lead investors and regulators alike to overlook the dangers of a credit boom and rapidly escalating asset values. Political and market commentators’ assurances that “this time it’s different” and predictions of a soft landing add fuel to the fire. Through a number of downturns, I’ve listened to reassurances about soft landings. I hope I live to see one someday!
The context and details of bubbles may change, but the basic drivers of human behaviour are constant.
The Fear Factor
Irrational behaviour is often based on fear. A housing bubble is typically based on the fear of being priced out of the market. For investors, the fear is often of being left out when others benefit. Sometimes this fear overrides rational judgement. I once spoke to an investment manager during the dot-com boom. He explained to me that it was a classic bubble, most of the businesses had little or no substance, and he expected it to burst before too long. Rationally, therefore, none of his funds should have been invested in dot-com companies. But they were. Otherwise, he explained, his performance would be so far behind his peers that his customers would desert him. His fear of market forces outweighed his rational analysis.
Failure in Financial Institutions
The drivers of failure in financial institutions are very similar to the drivers of a macro-economic crisis. The key to safe institutions is a proper system of checks and balances operated by competent management. In monitoring the functionality of these checks and balances, boards and regulators equally need to apply common sense and be alert to indicators of danger. As very basic examples, unless there is a clear and obvious explanation, over-achievement or estimating losses or contingencies below peer group estimates should spell danger. Attention is equally needed to flagging performance (which may encourage risk taking to make up lost ground). In addition, obvious flaws in business models create danger. For example, over-reliance on short-term borrowing to finance long-term lending, has been identified as a flaw as it depends on continuing money-market liquidity at an affordable price.
Particular attention should be paid to inbuilt incentives to irresponsible risk taking, such as over challenging targets, inappropriate incentive schemes, or employees or divisions able to take a one-way bet where they take the rewards of success but the effect of failure falls on others.
A Model Answer?
The complexity of modern business life and the need to map and measure risk means that complex financial models will sit at the heart of insurance businesses. However, I am concerned that the sheer complexity of prescriptive regulation and of financial models will get in the way of both boards and regulators in identifying the problems that cause failure. Opacity in financial instruments and the complexity of derivative markets helped to fuel the last crisis. It would be a pity if complexity of regulation were to contribute to the next.
While financial models and systems for collating information can help to provide the analyses needed to identify warning signs, identification depends on stepping back and taking a commonsense look at an institution or economic system.
Regulators are not foolish; they know this. Governance requirements are a vital part of emerging regulatory systems. Solvency II is a prime example and, globally, the concept of risk-based management is gaining ground. However, the complex models and related governance developed by banks under Basle II did not prevent bank collapses. A commonsense approach to risk management may well have done better.
So, is regulation a waste of time?
Regulation has an important role to play. For example, grumble though we might, the insurance industry will benefit from requirements to identity, measure, monitor and control risk. Doing this will allow organisations to spot and address threats more efficiently and should help to improve decision-making. We also need to remember that consumer confidence in buying financial products is underpinned by credible regulation. However, there does come a point where particular types of regulation can become counterproductive.
“The Dog and the Frisbee”, Andrew Haldane’s speech to delegates at the Federal Reserve Bank of Kansas Economic Policy Symposium in August 2012, addresses this issue very well. It explains how increasingly complex regulation, increased regulatory resources and the information overload inherent in complex models do not necessarily improve the quality of regulation and, in fact, are likely to impair it. Haldane points out that complexity creates opacity. In other words: it’s not possible to see the wood for the trees.
Detailed prescriptive regulation inevitability drives behaviours to stay within the prescriptive rules. The potential detriment to broader governance is clear. We do not need detailed rules and a complex model to tell us that a single banker should not be given freedom to bet the bank. Nor do we need a model to have suspicions about stellar performance from a business segment where there is no apparent explanation for that performance.
The danger is that detailed rules and risk management driven by a model will focus governance on the rules and the model. The resources needed to comply with a myriad of rules, the sheer complexity of a model and the volume of information that it produces may well obscure the real problems. Simple things, like dealing with mistakes, may be overlooked. A small mistake covered up can have a multiplier effect, becoming bigger over time. An institution in for a penny can find itself very quickly caught for a pound. The collapse of Barings Bank offers valuable lessons in this area. Rules and models will not prevent mistakes; instead, institutions need to consider how a person might cover up a mistake and address that. A board dazzled by a super-model risks missing commonsense issues like this.
With the best will in the world, the sheer information overload inherent in detailed rules and complex models may well get in the way of proper oversight. Haldane certainly thinks so. His verdict on Basle II is that the requirement to monitor many small, rule based, risks may have caused regulators to overlook potentially life threatening risks: “Supervision suffered the same fate as the autistic savant – penny-wise but pound foolish.”
Regulators have thought of that. Institutions will be required to monitor and update their models and will not be entitled to follow models slavishly. They should apply common sense and challenge the model if necessary. However, will boards and senior executives really be prepared or, more importantly, equipped to second-guess the output of a complex model encompassing millions of calculations? If they get it wrong, regulators and the press will be quick to criticise them for disregarding the output of their own model. It something goes wrong, the board that followed a state-of-the-art model approved by a regulator may escape more lightly than one that disregarded that model and substituted its own judgement.
Regulators are not immune to being blinded by detail and complexity. It is far easier to police compliance with detailed rules (ticking boxes along the way) than stepping back and identifying warning signs in an apparently healthy institution or economy. If significant resources have to be devoted to the former, will enough attention be paid to the latter? How will smaller, under-resourced, regulators cope?
Haldane argues for less complex regulation administered by fewer and more experienced regulators operating to a smaller, less detailed rule book. I’m with him on that. Where I take a slightly different tack is my hope that, within that rule book, there will space for identifying and monitoring commonsense warning signs based on a better understanding of human behaviour. As things stand, I am not holding my breath. As we rush headlong towards implementing Solvency II, we face more, not less, complexity.
A Personnel Question
We also need to look at who is best qualified to regulate financial institutions. Is it quants or economists, actuaries or lawyers, accountants or investigators, industry professionals or career public servants? Undoubtedly, it should be a mixture of professions but what mixture?
In my view there is no perfect system of regulation. Insurers will continue to collapse and regulation will never change that. It is a normal part of a healthy economic system that businesses fail. I don’t have a magic solution; however, I believe that we can do much more to head off failure. The key is to begin with incentivising prudent behaviour. We should devote sufficient resources (both within institutions and regulators) to monitoring common sense warning signs and fewer to making, complying with and enforcing detailed rules. A focus on warning signs and rules informed by a better understanding of the drivers of human behaviour will help not only to safeguard individual institutions but also to address many of the macro-economic issues exposed by the last crisis.
It will always be difficult to achieve the ideal mix of professions in a regulator. However, until we include experts on human behaviour, that list will be deficient.
The current phase of evolution of regulatory systems is just that, a phase. We need a further phase that should begin with an understanding of the drivers of human behaviour. It should aim to eliminate complexity that impedes both efficient risk management in institutions and efficient supervision by regulators. Otherwise, we will continue to scratch our heads after each crisis wondering why all the shiny new regulation has failed.