Reasoning by analogy from a different field of endeavour than the one in which we are presently submerged (as section 1 has done) is one of the best ways of thinking ‘out of the box’ of legacy approaches that quite often lead to sub-optima and dead ends. Here is another example, this time from medical science. ‘The belief is growing on me that the disease is communicated by the bite of the mos- quito,’ suggested Ronald Ross, a British doctor in India. That insight won him a Nobel prize.3
Defying age-old notions that malaria was caused (as its name suggests) by foul air, Ross showed how it really spread. Unfortunately, those who succeeded him
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in the task of fighting malaria have been short of imagination as well as of accountability for results. This should not happen with risk management.
Once we know the causes, the application of effective solutions can limit expected losses and provide better insight into unexpected losses caused by counterparties, financial instruments, the business environment and/or a failure in the institution’s internal control system. Some of the ingredients of continuing effective risk control are:
● Rigorous auditing
● Better performance measurement
● Appropriate capital allocation, and
● Realistic pricing of financial products.
In all these cases, thinking out of the box improves the accountant’s ability to gauge additional risk factors that exist outside the immediate trading and back- office functions. Regrettably, this is not common practice. In the course of the research project that led to this book, experts in financial analysis, trading, treas- ury operations and the control of risk commented that in a large number of insti- tutions current risk management systems cannot cope with the explosion in types and severity of exposures because they are too much tuned to what has happened in the past.
The inadequacy of current approaches has been caused by a variety of factors, chief among them being traditional thinking and the fact that members of the board of directors seldom have direct experience of risk management (Chapter 12). Still another factor is that the institution continues using obsolete and incompatible information systems:
● Designed to address simpler business activities
● Using a variety of heterogeneous design methodologies, and
● Handling incompatible data formats, on different technical platforms and with a variety of programming languages.
All this is part of traditional thinking. Organizations that have done their home- work in restructuring their risk management solutions have come to the conclusion that there is an overwhelming need for homogeneous systems and approaches able to provide any-to-any immediate consolidation, calculation and presentation of limits, positions and risks (section 5) – as well as opportunities to trade.
New strategic-level departures to risk management are vital because mammoth financial institutions and the so-called ‘non-bank banks’ challenge the traditional domain of a credit institution’s activity. They also overrun the classical risk control
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concept and, by extension, bank regulation, which is typically based on the notion of firms with specialized activities. To be in charge in this fact-changing environ- ment, management needs to:
● Introduce a broader mix of risks originating in diverse business lines, and
● Provide a comprehensive but flexible risk control approach that take a view of the firm as a whole.
An example of this broader mix is the sale by insurance companies of credit risk protection through credit derivatives (Chapter 6). The contracts straddle the investment and underwriting activities of insurers, which are conventionally managed separately. By so doing, large and sophisticated entities increase de facto their risk appetite because of an excessive concentration of most diverse financial activities; hence, they need a vastly strengthened system of risk control.
Accountants, auditors and internal control specialists are key to this system, because they both provide inputs to it and use its outputs. Thinking out of the box suggests that these inputs must be redesigned to serve the needs of both the more classical analysis of exposure and a discipline known as meta-analysis.
Meta is a Greek word meaning a level higher than the one we have been clas- sically working. Meta-knowledge is knowledge about knowledge; meta-accounting is accounting analysis beyond filling pigeonholes in accounting books. The concept of meta-analysis has existed for six decades, but it has grown over the last 20 years. Originally invented in 1948, it blossomed with expert systems and knowledge engineering4as a way of:
● Extracting statistically meaningful information from lots of small account- ing entries or results of trials, and
● Reaching far-sighted conclusions even if trials have been conducted, and accounts written in ways that make it difficult to compare the results.
Notice that the conclusions of meta-analysis are only valid if the outcomes of both positive and negative trials are included in the study. If the negative trials are left out then the results may be too optimistic, as often happens with the interpretation of experimental outcomes that are screened to weed out what is (wrongly) considered to be irrelevant outliers.
The science of risk management, whose conquest was introduced in Chapter 1, requires that nothing is discarded a priori. Every information element counts.
Outliers are a means of thinking out of the box. High-impact risks are often hid- ing at the long leg of the distribution of exposures, and it is the duty of the ana- lyst to flash them out and put them in perspective.
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