CAS.PredictiveModels

Reading: “Regulatory Review of Predictive Models White Paper,” December 2020

• Sections I, IV and VII.

Author: Casualty Actuarial and Statistical (c) Task Force

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BA Quick-Summary: Predictive Models Insurers' use of predictive analytics and big data offers significant benefits by revealing insights into consumer behavior, lowering insurance costs, and encouraging loss mitigation. However, the rapid evolution of these techniques poses challenges for state regulators who often lack the tools to effectively review these models. This white paper aims to establish best practices to guide state insurance departments in reviewing predictive models to ensure compliance with state laws and regulations while promoting consistency, efficiency, and innovation in the insurance market.

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Models&section=all&subSection=all&examRep=all&examYear=all&examTerm=all&quizNum=4Multiple Choice (mini BattleQuiz 4) ← for general review of topic

Study Tips

The content outline states you are responsible for sections I, IV, and VII of this reading, which is only 3 pages altogether, so it shouldn't take long to read and understand this material. There is a fair amount of memorization however and that will take a lot longer than 20 minutes.

Estimated study time: 20 mins (not including subsequent review time)

BattleTable

No past exam questions are available for this reading.

reference	part (a)	part (b)	part (c)	part (d)

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In Plain English!

Section I - Introduction

This is a really simple section. There are no deep concepts so I asked Ian-the-Intern to reduce the whole thing to just 4 BattleCards. See below. Thanks Ian!

Question: What are the potential benefits of using predictive analytics in insurance? [Hint: REL]

• Reveals insights into insurance costs
• Encourages better risk management.
• Lowers many consumer costs

Question: What challenges do state insurance regulators face with predictive models?

• many lack the necessary tools to effectively review rapidly evolving predictive models

Question: What are the 2 main responsibilities given to the Casualty Actuarial and Statistical (C) Task Force?

• draft and propose changes to the Product Filing Review Handbook
• provide state guidance for rate filings based on predictive models

Question: What is the purpose of the guidance provided in the white paper?

• enhance uniformity in regulatory processes while considering state-specific insurance needs

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Section IV - Do Regulators Need Best Practices to Review Predictive Models?

This is another easy section that has simple factual information.

Question: What is the purpose of regulatory best practices for predictive models? [Hint: SIP]

• Support parameter valuation.
• Improve model understanding
• Provide a baseline for state regulators

(Hey, Mr. Regulator, take a SIP of my delicious predictive model tea!)

Question: Do regulatory best practices create standards for filings with predictive models?

• Heck no!! (But they help identify model elements and improve rating plans for consumers.)

Question: How do regulatory best practices help state insurance regulators and the industry?

• regulatory best practices guide regulators
• regulatory best practices identify key model elements
• regulatory best practices facilitate resource sharing
• regulatory best practices improve review quality
• regulatory best practices aid in training

Let's get creative and write a (very) short story: Alice's best predictive model practices help guide regulators by identifying key model elements. Alice is all about sharing her monumental genius and her best practices also facilitate resource sharing among the rest of us, which improves review quality, and aids in training. Win-win-win!! 😁

Question: How do regulatory best practices benefit state insurance marketplaces?

• regulatory best practices enhance market speed and competitiveness by improving review processes

Question: How do regulatory best practices assist new insurance regulators?

• regulatory best practices provide training and help identify needed resources for model reviews

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Section VII - Best Practices for the Regulatory Review of Predictive Models

It's worth emphasizing that the "best practices" discussed in this reading are not best practices for using predictive models, rather they are best practices for the regulatory review of predictive models. With that in mind, this section provides you with yet more incredibly fascinating facts to memorize. 😕

The first paragraph of this section seems to repeat material from Section IV. It explains different ways regulatory best practices help state insurance regulators and state insurance marketplaces, but the answers are slightly different from Section IV. I think if an exam question asked this, the graders would accept any valid answer from either this or previous sections. In any case, here's what Section VII says about how regulatory best practices help state insurance regulators:

• to understand if a predictive model is cost-based
• to understand if the predictive model is compliant with state law
• to understand how the model improves a company’s rating plan

(I suppose these are also characteristics models should have.)

The previous section also mentioned that regulatory best practices can enhance market speed. This point is expanded upon here as follows:

• Best practices can also improve consistency among the regulatory review processes across the states and improve the efficiency of each regulator’s review, thereby helping companies get their products to market faster.

The rest of this section is a crazy detailed bullet point that explains what a regulator's review of a predictive model should include. You can refer to the source text for the details, but on a high level, here's what you need to know. (I doubt very much an exam question would required more detail than what Alice has extracted below:)

Regulatory Review Items to Include #1: Check that the rating factors have these characteristics.

• produce fair rates
• not cause excessive premium disruptions
• comply with state practices

Regulatory Review Items to Include #2: Check the following items regarding the data and the model.

• how the model was built
• accuracy of input data
• adjustments to raw data
• update frequency of risk characteristics

Regulatory Review Items to Include #3: Check interaction of the model with the rating plan.

• must understand input characteristics of model
• must understand integration of model with rating plan
• must understand interaction of model with non-modeled variables

Regulatory Review Items to Include #4: Check for desired characteristics regarding the insurance marketplace.

• enable competition and innovation
• protect model confidentiality
• allow timely reviews for speed to market

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