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Risk management that deals with the imperfect world

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In comment and analysis on the energy market losses experienced by the hedge fund Aramanth, a number of market commentators have remarked that the losses occurred from what was termed "a ninth sigma" event — "an event with a probability so low that such events simply do not happen".

Whether this was or was not the reason for its problems, it does focus on the extent to which enterprises should rely on mathematical models for their risk management.

The "science" or quantitative features of financial risk management has progressed significantly over the past 10 years. Technological advances have played a significant role in the advance of the science of risk management.

The scale and capacity of computing power and its response time have improved exponentially. Moreover, they are available and at rapidly diminishing costs and resource. Availability of substantially improved database technology providing storage capability, capacity and ease of access are specific areas of improved technological competence which have benefited the science of financial risk management. Technological advances have responded to increased financial regulatory demands over this facet of regulation.

The enhancements in quantitative scope and capability have enabled organisations to adopt more sophisticated approaches to risk management. Improved database technology has enabled storage, retention of, and accessibility to, vast repositories of mathematical and statistical data, which may be interrogated and analysed rapidly and cost effectively.

Financial institutions have emerged with sophisticated proprietary mathematical risk models to assist the management of the financial risk of their enterprises. Quantitative risk models should, of course, be varied and adapted in the light of experience and judgement. Basically, they are highly sophisticated tools for managing the risk of the enterprise. The models should not make the decisions or dis-intermediate the decision-making function of the risk manger because fundamentally they don't recognise the so-called external imperfect environment.

One of the major challenges to mathematical risk models is the so-called "imperfect world". This is where qualitative risk management should be deployed.

What is qualitative risk management? The qualitative aspects of risk management are the application of management skills, judgement and experience to assessment and review of the risk management models. Most importantly, qualitative risk management applies an external environmental assessment to the quantitative risk management model.

Qualitative factors impact risk models and the risks those models measure. Financial modelling, their parameters, the selection and character of the underlying data, as well as periods, are important judgmental factors, which contribute to the assembly of all risk models. For example, most banks have internal risk rating systems. They probably have a variety of applications: identify and track problem loans; determining mode and method of approval requirements.

Internal risk rating systems are used to assess the likely outcome of loans: the default probability and the amount of the loss anticipated from that default. Internal risk rating systems apply the intangibles: maturity, experience in different markets and economic conditions.

Qualitative risk management is the pro-active form of risk management. In that form it provides the premium value to risk management. It provides input to quantitative risk management in terms of influencing the shape and design of the quantitative model. It then steers the current quantitative model. However, the qualitative model can only provide a premium service when it supports a strong and refined quantitative risk management model.

Qualitative risk management delivers an intangible, premium element to risk management, which cannot be provided by quantitative risk management. At the same time it cannot function without the underlying quantitative risk management. Management experience in terms of judgement and experience should be applied to tailor and refine these models for day-to-day use and service. The qualitative aspects of risk management are of equal importance to risk management of a financial institution.

Copyright © 2006, IT-Analysis.com

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