Abcd Managing and measuring operational risk in an insurance company John Rowland Tillinghast General Insurance Spring Seminar 19-20 May 2003 Scarman House.

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Presentation transcript:

abcd Managing and measuring operational risk in an insurance company John Rowland Tillinghast General Insurance Spring Seminar May 2003 Scarman House

Agenda What is operational risk? Management and control frameworks A stress and scenario testing approach to manage operational risk Advanced insurance modelling techniques

… through better management of operational risk each of these risk events could have been avoided Why is operational risk important? Pensions mis-selling~£15bn MIG~£5bn LMX spiral~£5bn Equitable Life~£1.5bn Barings~£900m NatWest ~£90m

and to assess the amount of capital add-on that is required for any identified weaknesses in systems and controls Basel 2 / EU CAD 3 definition: direct or indirect loss resulting from inadequate or failed internal processes, people and systems or from external events Financial Services Authority ICAS: + Residual risk - potential risk mitigation failures + Strategic risk - strategic and operational uncertainty + Legal and litigation risks - risks arising from normal operations What is operational risk …

Self certification of the effectiveness of systems and controls across the following dimensions: Systems and control risk: the FSA’s approach Group structure; Risk management; Policies, procedures and controls; Management information; Information technology; Compliance; Internal audit; Outsourcing / third party providers; Business continuity; Corporate governance; Management responsibilities; Human resources.

Under pricing Under reserving Reinsurance failure Gross incompetence Unforeseen catastrophes Rapid expansion Outsourcing Unforeseen claims Fraud and greed False reporting Investment failure Expansion into new areas A effective starting point is to assess the key causes of failure for insurance companies

Agenda What is operational risk? Management and control frameworks A stress and scenario testing approach to manage operational risk Advanced insurance modelling techniques

Regulatory risk management best practice Principles 1-3 Oversight of operational risk provided by the Board or management committee Principles 4-7 Monitoring, measurement and active management of operational risk by operational line management Principle 8: Degree of disclosure of operational risk Source: Basel Committee, Sound practices for the management of operational risk, Feb 2003

Transfer Likelihood Impact £ High Low Control Avoid Assume Risk prioritization framework

IT downtime Reserving Fraudulent claims Computer viruses Fraudulent underwriting Outsourcing Reinsurance failure Pricing Transfer Likelihood Impact £ High Low Control No risks fell into this box Avoid Assume For example, for a typical General Insurer

Control failureResidual risk Cost of risk (£) Assessing the effectiveness of controls It is not cost effective to completely eliminate risk Residual risk is accepted Regulators are concerned about the effectiveness of the controls … … and the cost of either a partial or a full control failure

Agenda What is operational risk? Management and control frameworks A stress and scenario testing approach to manage operational risk Advanced insurance modelling techniques

But - how plausible are they? How adverse are they? But - how plausible are they? How adverse are they? How should we select appropriate tests? FSA prescribed stress and scenario tests Actual versus expected experience Industry benchmarks Worst case / thinking the impossible internal experts external experts

Maximum possible loss Losses Prob. Plausible adverse scenario tests Best estimate loss 1% risk tolerance Shareholders Capital adequacy “Plausible adverse”scenarios … Examples exist in eg Canada and Australia?

Assessment: A file review indicates that 5% of claims are suspect. A doubling is plausible - use as a stress scenario, but double frequency and severity. A capital add-on of 20% of future claims is required. Assessment: Plausible for new agents (1:100 chance), deemed implausible for existing underwriters. Reasonable to assume that no agent could operate undetected for more than 6 months A capital add-on of £10m due to unexpected claims is required. Assessment: A capital add-on of £10m due to unexpected claims is required. Assessment: A capital add-on of 20% of future claims is required. Assessment: A capital add-on of 20% of future claims is required. A capital add-on of £10m due to unexpected claims is required. Plausible, but rejected as TWICL have asked their lawyers to review the wording of each arrangement. The legal opinion is that they are watertight Assessment: A capital add-on of 20% of future claims is required. A capital add-on of £10m due to unexpected claims is required. No capital add-on required Stress scenarios were considered for each risk - for example: Stress test / scenario: Fraudulent claims: Double the expected level of fraudulent claims arise. n Fraudulent underwriting: A broker acts fraudulently, writing business and collecting premiums undetected for 6 months. n Reinsurance failure: The legal documentation defining a re-insurance arrangement is found to be flawed

0 Loss Fit a loss distribution to the data Fraudulent claims: A high likelihood low impact data rich risk event

Agenda What is operational risk? Management and control frameworks A stress and scenario testing approach to manage operational risk Advanced insurance modelling techniques

Sample mean Loss True mean Modelling high impact low probability events is more complex These risks are fat tailed You may have some observations, but the tail won’t have been observed You will not have an estimate of the tail and hence the capital required

Novel approaches are required for operational risks The key is to think out of the box Assessing asbestos and tobacco liabilities Pricing catastrophe insurance Designing alternative risk transfer products for the capital and insurance markets Assessing flood risk or nuclear waste sites Structuring and pricing financial reinsurance transactions

From the extreme value model we find the following percentiles: 95th: 600cm 99th: 850cm From the extreme value model we find the following percentiles: 95th: 600cm 99th: 850cm An engineering example … using extreme value theory models

Risk event Risk event Risk consequen ce Risk consequen ce Risk factor/drive r Risk factor/drive r Identify the risk factors that trigger the event Assess the effectiveness of the risk factor controls Assess the likelihood of a control failure Estimate the severity assuming effective controls partial control failure complete control failure Identify the risk factors that trigger the event Assess the effectiveness of the risk factor controls Assess the likelihood of a control failure Estimate the severity assuming effective controls partial control failure complete control failure For other risks there may not be any realistic internal data or industry benchmarks

Review Risk management and risk measurement are equally important Risk management best practice Risk management framework Stress and scenario tests Approaches to modelling