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Actuary: Fap4-3

Module 4: Actuarial Solutions

Section 3: Data

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• Objectives
  • Explain the role of data collection in solution design.
  • Describe the considerations in managing data (e.g., sourcing, quality, quantity, relevancy, governance and use).
  • Describe data collection techniques.
• Actuaries indicate that “finding the data I need” is a challenge in their day-to-day work, regardless of their area of practice. According to the SOA Market Research 2003 Member Survey Report, the mean rating of challenge was 57 percent (scaled from 0 = “No challenge at all” to 100 = “A very great challenge”).

• What Is Data? According to the Merriam-Webster online dictionary, data is:

• Data needs must be placed in context with the problem already defined and the potential design of the solution. The actuary must assess the relevance of readily available data to the current project. For any project the actuary must ultimately certify that the data is sufficient and reliable for the purposes of the project. Questions the actuary should ask include:
  • Is the data of acceptable quality? Can the data be improved? What quantities of data are available? Can it be easily adapted for use in prospective models? Are there other potential sources of the relevant data?
  • What governance controls have been established with respect to the data I intend to use?
  • How will I monitor emerging data?
  • Is the data sufficient and reliable? If it isn’t, what are the limitations imposed on the solution design by the data?
• Use of data:
  • As a direct input into models
  • Actuaries have used data analytics to establish appropriate assumptions for their models
  • Actuaries also use analytic techniques to predict outcomes directly from available data, especially in casualty and health insurance.
  Read m4s3-02_DataUse.pdf for more.
• Many modern businesses have decided to compete through analytic strategies. They use strategies developed through often-sophisticated analysis of the available data to gain a competitive advantage. Actuaries have often used analytic strategies to compete in the past. For example, an underwriting program can be considered an analytic strategy.
• Read an article (m4s3-01_DataUnlocks.pdf) from the American Academy of Actuaries entitled, “Data Unlocks the Door of Opportunity for Insurers.”
• There is an Actuarial Standard of Practice (ASOP) developed especially for actuaries who are selecting, reviewing or using data or are relying on data supplied by others. This standard, “#23 – Data Quality,” is important for actuaries in every discipline. Read Section 1 through Section 4 of ASOP #23 (asop023_141.pdf) now.
• Key points from the ASOP summarized in Understanding Actuarial Management (2010), pp. 277-278:
  • The actuary should communicate and disclose all data issues and in particular any data limitations.
  • Data should be appropriate for the scope of the assignments and the intended use of the analysis.
  • Accuracy and completeness of data supplied by others can be relied upon, with the following precautions. There must be disclosure, that is, all reports must identify the supplier and the manner in which the data was relied upon; and, while a complete audit is not required, such data should be reviewed for reasonableness, consistency and questionable values.
  • The actuary must decide if the data is sufficient and is fully useful; is usable, but must be qualified; or is unusable.
• Data quality: For a discussion about the importance of data integrity, click here to read an article (m4s3-03_DataIntegrity.pdf) entitled, “Does Your Data Have Integrity?” by the Casualty Actuarial Society.