1. Key Principles - EQ
    1. EQ exposure risk mgt:
    2. sound and comprehensive EQ exposure risk mgt policy subject to Board oversight and implemented by sr mgt
    3. EQ Exposure Data:
      • appropriately captured and regularly tested for consistency, accuracy and completeness.
    4. EQ Models:
      • used with sound knowledge of assumptions and methods and with caution of uncertainty in the estimates
    5. PML Estimates; reflect total expected ultimate cost, incl considerations for
      • data quality,
      • non-modelled exposures,
      • model uncertainty
      • exposures to multiple regions
    6. Financial Resources and Contingency Plans
      • ensure adequate level of financial resources and contingency plans to successfully manage thru a major EQ
  2. EQ Policies & Procedures
    1. Risk appetite and risk tolerance for EQ insurance
    2. Data mgt practices
    3. Exposure aggregation monitoring and reporting
    4. Appropriate understanding, selection and use of EQ models, incl model limitations, uncertainties and non-modelled exposures
    5. id and estimation of PML factors
    6. Nature and adequacy of financial resources available for PML;
    7. Contingency plans to ensure adequate claim handling resources and continued efficient operations
    8. Consideration of post-event claim cost inflation
  3. Board, sr mgt and actuarial oversight responsibilities - EQ
    • Board:
      • Oversee development of EQ policies and procedure
      • ensure effective implementation
    • Sr mgt:
      • Implement policies and procedures.
      • ongoing exposure mgt and reporting
    • Board and Sr mgt:
      • Ensure appropriate controls to monitor effectiveness of, and compliance with, policies and procedures.
      • Controls to ensure EQ exposure (low frequency / high impact) is aligned with coverage design
    • Actuarial:
      • Review models used to determine exposures
      • Adequacy of reinsurance programs to mitigate these exposures
  4. Req'ts for data quality - EQ
    1. Data Integrity: sr mgt needs to understand data req'ts and ensure data quality and timely capture
    2. Data verification:
      • Process in place to verify databases accuracy
      • Assess overall data quality when has limited access to underlying data processing system (e.g. reinsurer)
    3. Data limitation:
      • Sr mgt needs to understand impact of data limitations and possible errors, and adjust model estimates.
      • regular review of data by those independent of data collectors (completeness, accuracy and consistency)
  5. Process to measure data completeness and accuracy
    1. Scoring data quality at the time of UW;
    2. Conducting remediation of sources providing inadequate data;
    3. Developing and implementing safeguards to prevent data collectors from miscoding
    4. Investing in technology to improve data quality
  6. Methods to test EQ exposure data quality
    1. Summarize data by key occupancy and geo and review, e.g. most common values
    2. Compare year-to-year exposure changes
    3. Review historical data for consistent issues
    4. Portfolio-specific data quality sensitivity tests to ensure data quality
  7. EQ Models - Considerations
    • Use of EQ Models
    • Sound EQ model practices
    • Model versions
    • Model validation
  8. Sound EQ Model Practices
    • Understand alternative models and why selected model is most appropriate
    • Qualified staff to run models when used in-house;
    • Use >1 model (to encounter inherent risk of model)
    • When >1 model and produce materially dif results (PML), explain differences and resulting model adjustment
    • Understand assumptions, methods and limitations of model to interpret results
    • Understand model uncertainty and effects on capital & reinsurance requirements;
    • Regularly review and update model
    • Document how use of EQ models fits within EQ risk mgt process
    • Able to justify appropriateness of granularity and data quality
  9. Key assumptions, methodologies and limitations u/l model
    • How dif settings / parameters impact PML and why selected are appropriate when dif from suggested from model;
    • Ability to handle demand surge, fire following etc.
    • How changes in portfolio characteristics influence PML variability;
    • Modelled vs. non-modelled losses;
  10. EQ sound practices re: Model Versions
    • To counter inherent uncertainty in models, use > 1 model.
    • material updates to commercial models in a timely manner (within 1 year of release or explain why not)
    • When using vendor software to determine PML, understand model and limitations
    • When developed in-house, regular review and update and test of PML against other commercial models.
  11. EQ sound practices re: Model Validation
    1. against actual events in covered areas. if data insufficient, options:
      • rest of Canada and world
      • compare modelled tail losses to market prices for reinsurance.
    2. parameters, incl non-modelled risks, should reflect results of model validation process
    3. documentation
    4. id limitations of model / data
  12. Considerations for PML estimates
    1. Data Quality: understand impact of data limitations and make appropriate adj'ts (not a substitute for proper data capture)
    2. Non-Modelled Exposures and Risk Factors: consider risks not adequately considered in model
    3. Model Uncertainty: margin to reflect uncertainty with model assumptions
    4. Exposures to Multiple Regions:
      • insufficient to only consider max of BC and QC -> understate.
      • also consider worldwide exposure if material
  13. Non-Modelled Exposures and Risk Factors
    • Exposure growth btw date of data and end of exposure period
    • Contingent BI
    • Auto and marine insurance
    • Claims handling expenses
    • Adequacy of insurance to value
    • Demand surge/Post‐event inflation
  14. Financial Resources - EQ
    1. Capital and Surplus
    2. EQ Reserves
    3. Reinsurance Coverage
    4. Capital Market Financing
  15. Restrictive conditions for reinsurance overage and capital market financing
    • Reinsurance Coverage:
      • When incl non-CAT reinsurance in financial resources, need to consider per event limits and other events, terms that would o/w exhaust coverage
      • Insurers that participate in global CAT reinsurance program must consider
        • on-going protection for Canadian operations
        • recoverability if other regions impacted by same event
    • Capital Market Financing: Prior OSFI approval before can be recognized as financial resource under MCT Guidelines
  16. Contingency Plans - EQ
    • Ensure continued efficient business operations.
    • Address key elements of claims mgt (emergency communication, availability and adequacy of claims personnel)
  17. Probable max Loss (PML) - Defn
    • $ threshold beyond which losses from major EQ unlikely.
    • Probabilistic models: PML is return period loss ($ level expected to be exceeded once every X years).
    • Gross PML: after ded before reinsurance protection.
    • Net PML: after ded and reinsurance protection
  18. Risk Appetite
    • Total level and type of risk exposure an insurer is willing to undertake to achieve its objectives.
    • Qualitative assessment
  19. Risk Tolerance
    Specific limits on level and amount of risk an insurer is willing to accept/retain.
Card Set
OSFI: EQ Exposure Sound Practices Guideline