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How Do Actuaries Use Data Containing Errors?: Models of Error Detection and Error Correction

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  • Barbara D. Klein

    (University of Michigan-Dearborn, USA)

Abstract

Information systems provide data for business processes and decision making. There is strong evidence that data items stored in organizational databases have a significant rate of errors. If undetected in use, errors in data may significantly affect business outcomes. The question examined in this paper is the extent to which business professionals are able to evaluate the quality of data in the information systems they use and the impact of their evaluations on decision-making behavior. Models of error detection and error correction processes are developed. The validity of the models is then examined through an analysis of interviews with ten actuaries. The findings show that actuaries detect errors in data using three general methods and that actuaries consider feasibility and costs when deciding whether to correct data errors.

Suggested Citation

  • Barbara D. Klein, 1997. "How Do Actuaries Use Data Containing Errors?: Models of Error Detection and Error Correction," Information Resources Management Journal (IRMJ), IGI Global, vol. 10(4), pages 27-36, October.
    • Handle: RePEc:igg:rmj000:v:10:y:1997:i:4:p:27-36
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/irmj.1997100103
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    Citations

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    Cited by:

    1. Janvrin, Diane J. & Raschke, Robyn L. & Dilla, William N., 2014. "Making sense of complex data using interactive data visualization," Journal of Accounting Education, Elsevier, vol. 32(4), pages 31-48.
    2. Klein, Barbara D., 2001. "Detecting errors in data: clarification of the impact of base rate expectations and incentives," Omega, Elsevier, vol. 29(5), pages 391-404, October.
    3. Klein, B. D. & Rossin, D. F., 1999. "Data quality in neural network models: effect of error rate and magnitude of error on predictive accuracy," Omega, Elsevier, vol. 27(5), pages 569-582, October.

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