Preview Questions Actuary | Role Specific Skill

Question 1: What is the primary advantage of using a Bayesian framework in financial forecasting for actuaries?

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It incorporates prior information and updates with new data

It allows for deterministic predictions

It requires fewer data points

It eliminates the need for scenario analysis

Question 2: How do "Reinsurance Arrangements" influence pricing, and what methods are used to incorporate reinsurance costs into the pricing of insurance products?

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Reinsurance costs are irrelevant for pricing and should be excluded from models

Reinsurance arrangements transfer risk and reduce pricing volatility by adjusting for ceded premiums and claims, and pricing models must reflect reinsurance treaties

Reinsurance only applies to large insurance companies and has no impact on pricing

Reinsurance costs should be ignored if the company is sufficiently capitalized

Question 3: What does the beta coefficient represent in the context of Capital Asset Pricing Model (CAPM) risk modeling?

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The risk-free rate of return

The expected return of a diversified portfolio

The sensitivity of an asset's returns to market returns

The average return on an asset over a period of time

Question 4: Which regulatory framework primarily governs pension plan funding requirements in the United States?

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Solvency II

IFRS (International Financial Reporting Standards)

GAAP (Generally Accepted Accounting Principles)

ERISA (Employee Retirement Income Security Act)

Question 5: Risk-based capital (RBC) regulations in the United States were introduced to:

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Calculate the tax liability of insurers

Ensure that insurers hold sufficient capital to cover their risks

Standardize reinsurance requirements

Guarantee that all insurance premiums are paid on time

Question 6: What is the main disadvantage of using a Na?ve Bayes classifier in an actuarial risk model for pricing?

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Difficulty handling non-linear relationships

Assumption of independence between features

Underfitting with large datasets

Overfitting to small datasets