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IOPS Toolkit for Risk-based Supervision

Learn about key risk mitigants and factors to consider, such as governance quality, compliance culture, and operational management effectiveness, to develop robust risk mitigation strategies and scoring methods in financial supervision. Understand weighting methodologies, probability models, and impact measures to enhance your risk-based supervision process. Explore examples and best practices for consistent risk assessment.

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IOPS Toolkit for Risk-based Supervision

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

  2. RBS Process

  3. Risk Mitigants Main mitigating factors to be considered: • Quality of governing board / trustees - Their understanding of responsibilities, their experience, competence & integrity, and any presence of conflict of interest. • Management controls - Management quality and structure, decision making process, strategic planning process and risk control attitude. • Compliance culture - Compliance with laws and regulations and involves assessment of the competence, integrity and independence of staff, as well as the pension fund’s information systems

  4. Risk Mitigants • Effectiveness of operational management - Includes human resources policies, management of outsourced operations, pension fund organisational structure, group relationship, reporting lines and responsibility structure. • Adequacy of risk management systems - Quality of arrangements for identifying and measuring risk, setting limits, monitoring compliance and reporting. • Adequacy of independent review - Independence and competence of actuary, external auditor and internal auditor, and the quality of their reports.

  5. Risk Mitigants • Role of administrator - The experience of the administrator and the quality of the services provided. • Sponsor - In Defined Benefit funds, the financial strength of the employer. • Financial support - This may refer to the level of reserves in a DB Fund (or DC), or financial support from a parent entity.

  6. 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

  7. 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

  8. Probability: Financial Services Board

  9. 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.)

  10. Impact Measures - Example

  11. 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.

  12. Consistency of Scores

  13. Thank You Presentations of practical examples to follow

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