CASTF Task Force Flashcards

(14 cards)

1
Q

Casualty Actuarial and Statistical (C) Task Force

A

charged with identifying “best practices” to serve as a guide
to state insurance departments in their review of the predictive models underlying rating plans.

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2
Q

What are the 2 charges given to TF by the P&C Committee at the request of Big Data

A

1) Draft and propose changes to the Product Filing Review Handbook to include best practices for review of predictive models and analytics filed by insurers to justify rates.

2) Draft and propose state guidance (e.g., information, data) for rate filings based on complex predictive
models.

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3
Q

Purpose of paper?

A

identify best practices for the review of predictive models and analytics filed by insurers with regulators to justify rates and will provide state guidance for the review of rate filings based on predictive models.

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4
Q

how does the task force provide guidance?

A

This guidance is intended only to assist state insurance regulators as they review models to determine whether modeled rates are compliant with existing state laws and/or regulations

with the purpose of “add uniformity and consistency of regulatory processes, while maintaining the benefits of the application of unique
laws and regulations that address the state-specific needs of the nation’s insurance consumers.”

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5
Q

Why do regulators need “best practices”

A

Regulatory best practices need to be developed that do not unfairly or inordinately create barriers for insurers, and ultimately consumers, while providing a baseline of analysis for state insurance regulators to review the referenced filings.

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6
Q

WHY DO REGULATORS NEED BEST PRACTICES TO REVIEW PREDICTIVE MODELS?

A

best practices will assist the states in identifying the model elements they should be looking for in a filing that will aid the regulator in understanding why the company believes that the filed predictive model improves the company’s rating plan and, therefore, makes that rating plan fairer to all consumers in the marketplace

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7
Q

state insurance regulators and the
industry need to recognize that:

A

1) Every state may have a need to review predictive models. Regulators need to identify elements of a model that may influence the regulatory review.

2) Best practices provide a framework for the states to share knowledge and resources to facilitate the technical
review of predictive models.

3) Best practices can lead to improved quality in predictive model reviews across the states, aiding speed to market
and competitiveness of the state’s insurance marketplace.

4) Best practices aid training of new state insurance regulators and/or regulators new to reviewing predictive models.

5) Each state insurance regulator adopting best practices will be better able to identify the resources needed to assist
their state in the review of predictive models.

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8
Q

how do best practices help the state insurance regulator understand a specific predictive model?

A

help regulators udnerstand:
1) if a predictive model is cost-based
2) if the predictive model
is compliant with state law
3) how the model improves a company’s rating plan.

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9
Q

how do best practices help the states from a regulatory standpont?

A

1) improve the
consistency among the regulatory review processes across the states
2) improve the efficiency of each regulator’s review

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10
Q

How does this help insurers?

A

help companies get their products to market faster

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11
Q

4 tasks Regulators should ensure for each review of model

A

1) ensure rating factors are equitable
2) understand the underlying data and assumptions
3) evaluate real world model results
4)promote competition and growth in a stable market

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12
Q

What criteria do rating factors need to meet?

A

produce rates that are not excessive,
inadequate, or unfairly discriminatory.

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13
Q

Why are sound rating factors important?

A

Enable competition and innovation to promote the growth, financial stability, and efficiency of the insurance marketplace.

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14
Q

Qualitative best practices

A

regulators must make sure the data is accurate and understand how the data is cleansed and how missing data is handled.

Determine whether any adjustments to the raw data are handled appropriately, including, but not limited to,
trending, development, capping, and removal of catastrophes.

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