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Financial/Non Financial Quantification (Examples of learning outcomes (…
Financial/Non Financial Quantification
Scenario Modelling
Scenarios must involve the business and they should not just be conducted by the risk managers. They are important because they feed into capital and liquidity planning, particularly under the Basel rules.
Drawbacks:
Limited information on low frequency yet high impact events
Limited descriptive information about loss events
Limited internal loss data
Unsystematic data collection
Reliable Data?
Loss of information
The insurance effect, i.e. has insurance mitigated the total loss for certain losses where insurance
was in place and did indeed pay out
Scenario analysis is a process of analysing possible future events by considering alternative possible outcomes (sometimes called "alternative worlds")
Design scenerio drawbacks
Outdated information
Failure to generate sufficiently challenging scenarios
Non-availability or inconsistency or lacking of an aggregated view
can the past records generate a meaningful picture for what is to come in the future? This is particularly relevant when we consider that we are operating in a fast-changing environment.
Internal & External data is utilised. Data quality checks are required before use.
Operational Risk models must be overseen by by a good governance framework.
scorecards
Positives
can generate some confidence about treating worst case scenarios well in that the scorecard approach is realistic and traps the big risks.
The technique is relatively fast to put in place –both to set up and review
Negatives
extensive training and competence is essential amongst both the business managers and the risk professionals to make the system work.
There is also an issue about the quality of business judgement on hand within the firm to apply to the task together with the degree of management commitment to the approach in the first place.
Examples of scenario applications:
Regulatory breaches IT failures
Project failure
Litigation
Accidents to staff and customers
Data theft
The broader environment – extreme events Fraud in loans or payments
Misselling
Examples of learning outcomes
Capacity problems
Ratings and reputational damage
Fraud
Impact on the environment
Funding issues
Competitive threats
Failure to meet objectives
Delivery difficulties
Loss of customers/business
Good assessment will contain both Quant/Qualitative