Key Principles - EQ
- EQ exposure risk mgt:
- sound and comprehensive EQ exposure risk mgt policy subject to Board oversight and implemented by sr mgt
- EQ Exposure Data:
- appropriately captured and regularly tested for consistency, accuracy and completeness.
- EQ Models:
- used with sound knowledge of assumptions and methods and with caution of uncertainty in the estimates
- PML Estimates; reflect total expected ultimate cost, incl considerations for
- data quality,
- non-modelled exposures,
- model uncertainty
- exposures to multiple regions
- Financial Resources and Contingency Plans
- ensure adequate level of financial resources and contingency plans to successfully manage thru a major EQ
EQ Policies & Procedures
- Risk appetite and risk tolerance for EQ insurance
- Data mgt practices
- Exposure aggregation monitoring and reporting
- Appropriate understanding, selection and use of EQ models, incl model limitations, uncertainties and non-modelled exposures
- id and estimation of PML factors
- Nature and adequacy of financial resources available for PML;
- Contingency plans to ensure adequate claim handling resources and continued efficient operations
- Consideration of post-event claim cost inflation
Board, sr mgt and actuarial oversight responsibilities - EQ
- 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
- Review models used to determine exposures
- Adequacy of reinsurance programs to mitigate these exposures
Req'ts for data quality - EQ
- Data Integrity: sr mgt needs to understand data req'ts and ensure data quality and timely capture
- 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)
- 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)
Process to measure data completeness and accuracy
- Scoring data quality at the time of UW;
- Conducting remediation of sources providing inadequate data;
- Developing and implementing safeguards to prevent data collectors from miscoding
- Investing in technology to improve data quality
Methods to test EQ exposure data quality
- Summarize data by key occupancy and geo and review, e.g. most common values
- Compare year-to-year exposure changes
- Review historical data for consistent issues
- Portfolio-specific data quality sensitivity tests to ensure data quality
EQ Models - Considerations
- Use of EQ Models
- Sound EQ model practices
- Model versions
- Model validation
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
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;
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.
EQ sound practices re: Model Validation
- against actual events in covered areas. if data insufficient, options:
- rest of Canada and world
- compare modelled tail losses to market prices for reinsurance.
- parameters, incl non-modelled risks, should reflect results of model validation process
- id limitations of model / data
Considerations for PML estimates
- Data Quality: understand impact of data limitations and make appropriate adj'ts (not a substitute for proper data capture)
- Non-Modelled Exposures and Risk Factors: consider risks not adequately considered in model
- Model Uncertainty: margin to reflect uncertainty with model assumptions
- Exposures to Multiple Regions:
- insufficient to only consider max of BC and QC -> understate.
- also consider worldwide exposure if material
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
Financial Resources - EQ
- Capital and Surplus
- EQ Reserves
- Reinsurance Coverage
- Capital Market Financing
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
Contingency Plans - EQ
- Ensure continued efficient business operations.
- Address key elements of claims mgt (emergency communication, availability and adequacy of claims personnel)
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
- Total level and type of risk exposure an insurer is willing to undertake to achieve its objectives.
- Qualitative assessment
Specific limits on level and amount of risk an insurer is willing to accept/retain.