Over the last few days, several people have discussed various scenario analysis techniques with me and going on general opinion, this risk assessment technique is very popular among operational risk analysts. Definitely no doubt there, but what scenario analysis means to one analyst, can often be something entirely different to another.
What does scenario analysis really mean to operational risk analysts?
What does scenario analysis really mean to operational risk analysts?
Scenario Analysis for Banks
Scenario analysis isn't particularly a novel risk assessment technique and it isn't always straight forward to facilitate, but it certainly became fashionable when banks reached out to meet Basel II-AMA accreditation. Under the Advanced Measurement Approach for Basel II, banks are able to calculate their own regulatory capital, however; such an exercise can really only happen if a bank has enough loss incident data, and in the early days of Basel II that wasn't the case.
Financial institutions use scenario analysis to describe tail events, to feed their distribution fitting processes and their methods have become best practice in the industry sector. This success in scenario analysis wasn't accidental and it was fuelled by many collusive efforts, such as those which were carried out by the sbAMA working group. I have discussed all of this before on this blog and have a presentation that can be grabbed from this [LINK] that explains the sbAMA working group method in detail.
Financial institutions use scenario analysis to describe tail events, to feed their distribution fitting processes and their methods have become best practice in the industry sector. This success in scenario analysis wasn't accidental and it was fuelled by many collusive efforts, such as those which were carried out by the sbAMA working group. I have discussed all of this before on this blog and have a presentation that can be grabbed from this [LINK] that explains the sbAMA working group method in detail.
Different Methods
Away from banking, scenario analysis is also keenly entertained by risk managers and while these people have the same interest in mind for describing the unknown, they are less concerned about probability distribution functions. These risk analysts are more curious about discovering what could negatively impact them and how they may react to such unwanted, albeit rare events.
These two groups of risk managers make up the largest divided community of scenario analysts out there but other common applications of this tool are quite exciting, even though they are rarely adopted. Given that there are various methods for building a scenario analysis risk framework, I taken to list the five most common approaches in the diagram below.
These two groups of risk managers make up the largest divided community of scenario analysts out there but other common applications of this tool are quite exciting, even though they are rarely adopted. Given that there are various methods for building a scenario analysis risk framework, I taken to list the five most common approaches in the diagram below.
Five Common Scenario Analysis Methods | Causal Capital [Click image to enlarge]
Disappointingly, banks often adopt scenario analysis for economic capital purposes alone and many financial institutions never interpret or use their scenario results for a starting point to improve their risk management practices. Making scenario analysis serve just the statistical end of the game, is pretty limiting and in my opinion, missing the big picture. Conversely, those risk managers that use scenario analysis to deliberate on strange black swans, often rarely put any serious quantification systems underneath their work. This lack of "modelling the method", holds back scenario analysis from being coherent and logical in the way that it represents and ranks risks.
Scenario Method Comparison | Causal Capital [Click image to enlarge]
Scenario analysis in whatever form it takes can produce many different outcomes and alternate methods vary substantially in the way they operate. So then, what is broadly preventing the convergence of methodologies and the evolution of scenario analysis today?
[1] Narrow and singular goals.
[2] A lack of modelling concepts and tools.
Bankers are nearly always going to look at scenario analysis as an economic capital tool for operational risk. While Basel II has been inaugural in bringing the assessment of scenarios squarely into commercial practice, most of the good work here has now been done.
Following our method [4] approach above is part of the "art of risk" as some would say, but it needs to be taken further and into a modelling domain. This is especially the case, if the method is ever to be taken seriously by businesses.
Scenario analysis broadly needs risk analysts to carryout research work, publish papers, play with ideas and importantly collaborate their concepts into broadly accepted best practices. However, the community wide motive to do this just isn't there. Basel II gave risk managers in banks a need for research work and we have regulation to thank for this but without the regulatory incentive, I don't see scenario analysis evolving too quickly.
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