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A Multi-Polar rather than a Bi-Polar Investment World
The results we have looked at so far with regard to this model assume a bi-polar world of money/cash or interest-bearing securities. Suppose however that our investment world is much more complex than that, involving equities, fixed income securities, money market funds and money/cash. As a central bank cuts interest rates, the effect of this should be spread across these asset classes, which in turn react in different ways. If a central bank cuts interest rates, this should cause the investor to cut their portfolio weighting in money market funds and increase it in equities. In the short term, it should also cause an increase in the weighting for fixed income securities as the capital gain should offset the lost income. Eventually, however, we should assume that it causes a reduction in the weighting for fixed income securities. Finally, a rate cut should also lead to an increase in the weighting of money/cash. The reduction in money market funds and fixed income securities should logically equal the sum of the increase in weighting in equities and money/cash. Since money/cash has to share its gains with equities, one should assume that the effect on money demand and therefore prices is reduced. Prices should rise less than they would otherwise do without the influence of equities. Consequently, as prices rise by less, the exchange rate should also depreciate by less than one would otherwise expect. In the same way, an interest rate increase should in this multi-polar investment world lead to less of an exchange rate appreciation than would be expected in a bi-polar investment world.
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IT systems project failure
Numerous cases of cancelled or failed IT projects in the finance industry happen on an alarming scale. Many within the banking world are unreported because of reputation risk, i.e. risk of losing clients or looking foolish in front of rivals.
There are four major reasons for IT systems failure:
The risk management system was initially unsuitable for the bank or fund and could not be successfully tailored for use.
The skills base of the business project implementation was not properly understood or resourced.
Organisational politics or budgetary problems hindered progress.
Operational errors or poor systems design ruined chances of success. -
FINANCIAL IT SYSTEM SUPPORT
Financial IT development projects took a massive boost in the mid-1980s following “Big Bang”. Open systems running on common client-server architecture became the industry standard at the beginning of the 1990s and system choice for banks and fund managers increased. There are now numerous vendors, e.g. Algorithmics, Barra, Erisk, Misys, Reuters, Sungard, who will be happy to entertain you. The hardest job is to select which one. Finding the right supplier can provide real business value-added service at a competitive price. Technology has enabled a huge number of private investors to take part in whatever investment at a touch of a button. This has resulted in an unprecedented widening of the clientele within global exchanges. But, technology increased the potential for IT and systems failures, commonly lumped into the catch-all “operational risk”. Some banks have met spectacular failures, or have been taken over by more capable and risk-aware banks.
Choose substance and not style in risk management systems. Many system vendors promise to provide you with the “best” systems for every business line. We must choose the “best” IT systems supplier to design and install our specific business environment.
Good use of IT is not about buying fancier computer boxes and designing jazzier websites. All computer-based financial modelling tools and complex IT systems promise to help you. The Loss Database for Basel II is one product that holds a lot of potential. The question is whether it will deliver. The key to success lies in its project implementation.
The Basel II Loss Database project
The new Basel II banking regulations are geared to raising the overall level of risk management in banking and fund management portfolios. Basel II will enable regulators to request advanced operational risk-managed financial institutions to set up and maintain the Loss Database. It has two business drivers, one a mandatory requirement and an optional “nice-to-have”.
First – all financial institutions wishing to have the status of an “Advanced” risk-managed company must comply with the Basel II. One of the requirements is the formation of the Loss Database.
Second – there is the goal of detecting consistent patterns of loss, and extrapolating from the data to predict the likely level of future business losses.
The ultimate objective is to reduce their level of losses and increase the predictability of the remaining losses. The downside risk of this project is an expensive business and an IT white elephant that does not meet business expectations.
A large global bank can have an expensive loss database, both in terms of number and value of loss items, plus the huge project costs of creating the database. They cannot afford to get it wrong because to do so would be both costly and embarrassing. Backing out a failed loss database project from all global branches would also be a high-profile noticeable loss (compare: Reputational risk).
An operational loss database, driven by the desire for good management or by the regulators, represents a large investment. An empowered band of financial specialists can reap real rewards for the company, supported by IT systems staff to “drill-down” within the loss database. This data-mining involves finding out lines of causality for:
who
when
how much was lost
how much could have been lost
why it all happened in the first place.
Loss databases will have to prove themselves against resilience-based approaches. These data will be analysed time and time again under different data-mining angles. The real test will be that of continual testing and review for cost-benefit analysis.
The loss database is a potentially good corporate risk management tool, but, it is likely to fail where it attracts little support within the corporation. Loss data are input for risk management decision making, and it needs a lot of massaging into acceptable reports before it can help to formulate director-level actions. The initiative stands or falls on whether top management supports and funds it.
The benefits are easier to predict than the costs. An advanced-certified operational risk-managed bank will have lower Basel II regulatory capital charges because its risk management processes are highly developed and evaluated as a lower overall risk. From previous regulatory examples within credit risk, a bank could find its regulatory capital reserve falling by some 6 %.4
How much this will translate into similar savings for OpRisk is to be decided by the regulators interpreting the Basel II guidelines.
Risk appetite becomes more directly linked to risk offer, but risk appetite is also covered by Basel II regulatory capital. Risk support systems alert the danger of capital becoming inadequate to cover expected losses.
The loss database business rationale may be a search for lower risk ratings and knowledge data-mining, forced on them by the regulator. The compliance “Big stick” approach of the regulator may be better at explaining the need for the database, instead of the more complex business cost-benefit analysis.
Losing money has never been in the interests of a bank, nor of its clients. Yet banks and investment funds continue to lose money without knowing where or why. There is some hope that this integrated database, linked to advanced modelling tools, can help make investing less risky. It will most likely be a complex and expensive project to set up, mainly because of the complexity and size of the data collected.
The formation of a complex loss database is a knowledge management structure that we are actively constructing. It requires a lot of data and system integration to link the disparate elements in a global bank. Some call this risk management system a “data warehouse” where information is packaged into one compatible format for analysis (see Enterprise application integration – EAI). The benefits are the harnessing of market intelligence to understand: who, when, how and how much money has been lost. Then, we can reinforce risk management procedures to avoid such a loss recurring, or to reduce the loss when the hazard strikes again. -
CURRENT STATE OF SYSTEMS
Financial institutions will chose their risk management paths and associated IT (information technology) systems. A real-time online dealing system performs as the eyes and ears of modern trading. Linked to a risk management nose for trouble, institutions should be able to trade more securely and more profitably.
There is strong competitive advantage to be derived from a powerful union of business and IT. We have to look at the varying results and levels of success within the IT of many banks and funds. There has been a mountain of literature published about the wonders of working in the new information age. The dot-com craze certainly heightened this sentiment. But, the resounding crash of the IT sector showed that there are real limits to marketing hype. There are potential faults on both sides of supplier and client that raise unrealistic business expectations in IT system delivery. Banking and fund management require skilled coordination between IT and risk management that is focused on business success.
The complexity of financial markets has increased because of the development of newer products and services in an increasingly global economy. Derivative instruments also require a higher level of quantitative techniques to cope with them. Back-office clearing and settlements systems do not always keep up with these technological advances, so mismatches will be frequent with the advent of new trading products.
One of the most prevalent problems is that the antiquity of the major clearing and settlement systems in the back office has meant that they lack the flexibility to be able to handle the welter of new financial products emanating from the front office. Because of this, there is frequent recourse to manual intervention and Excel spreadsheets, with all the attendant potential for error that this entails.
Investor understanding in this respect has declined. Even bank top management has often shed little light upon this extremely unglamorous failure. A huge financial loss arising from a rogue trader is much more understandable than a consistent and innocent seepage from the back office and settlements. Risk management must be focused on accurate goals.
Was the IT project conceived in a manner where initial goals were realistic? These have to be gauged against the bank’s resources and the IT supplier’s own input. When the business culture of the financial institution proves unsuitable to implementing an appropriate system, this quicksand can sink a project before it is launched. Realistic expectations and a good idea of project risk-return are essential pictures for top management to formulate before calling in technology to solve a business problem.
It is advisable to consult RAMP or PRINCE2 2 methodologies before plunging into the deep end of complex risk management systems. Buying solely upon a salesman’s pitch or IT director’s recommendation can be a sorry choice. Companies need the guidance of a methodology such as RAMP. This is a blueprint that is filled in with data and finalised at the end.