IOPS Toolkit for Risk-based Supervision

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

2. RBS Process

4. 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

5. Risk Mitigants: APRA

6. Risk Matrix: OFSI Canada

7. 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

8. Risk Weightings: APRA

9. 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

10. Probability: APRA

11. 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.)

12. Impact Measures - Example

13. 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.

14. Consistency of Scores

15. Thank You Presentations of practical examples to follow