IOPS Toolkit for Risk-based Supervision Module 4: Risk Mitigation and Scoring.

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Presentation transcript:

IOPS Toolkit for Risk-based Supervision Module 4: Risk Mitigation and Scoring

RBS Process

Risk Mitigants Main mitigating factors to be considered: Quality of governing board / trustees Management controls Compliance culture Effectiveness of operational management Adequacy of risk management systems Adequacy of independent review Role of administrator Sponsor Financial support

Risk Mitigants: APRA

Risk Matrix: OFSI Canada

Risk Weightings The following should be considered when establishing a methodology for weighting risk, Nature of the pension system The type of pension fund (i.e. DC, DB, Hybrid) Risk factors with measureable financial consequences Nature, scale and complexity of the supervised entity External environmental and market (systemic) factors Weightings changing over time Sensitivity tests or back testing to ensure accuracy and consistency

Risk Weightings: APRA

Probability Conditional probability – characteristics historically known to correlate with the occurrence of an event. Probability expressed as a function of the characteristics in a particular fund. Most RBS probability models are either additive or multiplicative, suggesting that risk characteristics are positively correlated. Some supervisors combine probability and impact of risk into a single score – i.e. probability of the risk leading to a significant to high impact. Assumption of high interdependence

Probability: APRA

Impact Impact measures assist in determining the supervisory oversight a fund will receive. Most authorities use size of the entity to capture the damage that would be inflicted if an adverse event occurred. Number of factors to determine ‘size’ – number of active or retired members, total assets, etc. Higher impact assigned to ‘systemically important funds’, although ‘systemic importance’ requires definition. Impact thresholds determined by level of protection in the system (e.g. guarantee schemes, sponsor backup, etc.)

Impact Measures - Example

Consistency of Scores Risk scores need to be checked for accuracy and consistency. Central vs. Individual Judgement. ‘Pre-populating’ scores – useful in centre structuring the judgement of supervisors. Also captures external or systemic risks. Checking mechanisms – central checking to ensure consistency across a large number of supervisors, internal comparisons and validations, training, etc. Separate unit for the design and maintenance of the risk assessment system. Retrospective testing of risk assessment models to validate risk scores given.

Consistency of Scores

Thank You Presentations of practical examples to follow