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IAI Actuarial Core Principles · Business Management · Using data, company functions, people skills, influence and clear communication

A pricing actuary at a general insurer in Pune receives a motor claims extract. About 12% of the records have a blank 'vehicle age' field, and the blanks are concentrated in claims handled by one branch that uses an older system. The actuary must decide how to proceed before fitting a model. Which action is most appropriate?

The actuary should investigate why the blanks occur, assess possible bias since they cluster in one branch, then apply a justified treatment and document its limitations. Simple deletion or averaging may distort results, and memory-based filling would introduce unreliable data.

  1. ADelete all records with blanks, since missing values cannot affect results
  2. BReplace every blank with the portfolio average vehicle age and report no caveat
  3. CInvestigate why the blanks arise, consider whether they bias the data, and document any treatment adopted and its limitationsCorrect
  4. DDrop the vehicle age variable and tell management the model is fully reliable
  5. Ask the branch to fill the blanks from memory so the dataset is complete

Explanation

Blanks concentrated in one branch suggest the data are not missing at random, so deleting or averaging could bias results. The actuary should understand the cause, choose a justified treatment and document assumptions and limitations. Filling from memory introduces unreliable data.

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