Insurance Research & Evidence-Based Practice 3

Question 1

In predictive modeling for insurance, what is 'overfitting'?

Accepted Answer

A model that performs well on training data but poorly on new data

Answer

Overfitting occurs when a model captures noise in training data rather than true patterns, reducing its predictive power on out-of-sample data.

Question 2

Which data source would an actuary most likely use for credible industry-wide loss frequency benchmarks in the US property market?

Accepted Answer

ISO (Insurance Services Office) statistical databases

Answer

ISO collects and analyzes loss data from many insurers to produce industry-standard actuarial benchmarks used in ratemaking.

Question 3

What is the difference between 'incurred losses' and 'paid losses' in insurance accounting?

Accepted Answer

Incurred losses include reserves for unpaid claims; paid losses are only amounts disbursed to date

Answer

Incurred losses equal paid losses plus the outstanding reserve for claims not yet fully settled, giving a complete picture of total expected cost.

Question 4

A researcher uses a Generalized Linear Model (GLM) for auto insurance ratemaking. What is the primary advantage of GLMs over ordinary linear regression?

Accepted Answer

GLMs allow non-normal error distributions and link functions appropriate for insurance data

Answer

GLMs extend linear regression by accommodating non-normal distributions (e.g., Poisson for claim counts, Gamma for severity) that better fit insurance data.

Question 5

What does 'external validity' mean in the context of an insurance research study?

Accepted Answer

The extent to which findings can be generalized beyond the study sample

Answer

External validity refers to whether a study's results can be applied to other populations, settings, or time periods outside the original research context.

Insurance Practice Test

Insurance Practice Test

Insurance Research & Evidence-Based Practice 3