Quantitative Model Validation Service for Financial Institutions in Australia
Posted by Quantfin on July 10th, 2015
Poor risk management models or framework are often responsible for large losses or business failure. Many blame erroneous model hypotheses, inexperience, misinterpretation of risks, and inability to cope with the circumstances—all of which are valid, but are extremely technical in nature. As financial institutions discover a cyclic occurrence of issues, new generations of analysts are also recognising the pattern and are actively advocating model validation to be an integral part of risk model development in an effort to reverse the vicious cycle.
Financial errors or catastrophes in financial institutions such as banks may not directly result in lethal consequences as crises in the social scale do, but their increasing magnitude can definitely affect the quality of the daily lives of hundreds and even millions. Risk models should, therefore, be validated in all respects, as they are important factors in the decision-making processes of various social and human activities (within and outside of financial contexts).
The effectiveness of risk models and mitigation processes in the finance and banking industry is bounded by ontological elements like; The way in which top management regards or views risk management; the positioning of supervisory control by political authorities; the relationship between social activities and expertise; and the evolution of technology in relation to their use and significance in financial risk modelling.
Quantitative models have been around for quite sometimes in various trading activities. Many institutions also extend the use of various quantitative methods for risk management activities, but it is only recently that model validation was adopted as a mandatory step in the life cycle of its development. Nevertheless, this inclusion has had a tremendous positive impact, not only on the development process, but in the model's overall effectiveness in preventing and mitigating risks.
Still, many companies suffer the classic "it is too complex" syndrome, often compromising their risk management processes by settling for a simplistic model already understood by everyone, albeit less effective. A more sensible approach would be to educate management with the consequences of such limited techniques and recruiting the help and counsel of a quantitative model validation service that can help you find the correct approach for your specific situation.
Banks are expected to optimise their risk profile, without necessarily overlooking risks as they facilitate trades. Lack of oversight, over-reliance, and over specialisation on commonly accepted yet un-validated risk measures can cause financial disasters that can be prevented by adding validation in the risk model's development cycle.
Also See: Risk Management, Model Validation, Risk Models, Financial Institutions, Risk, Quantitative, Model
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