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A robust record linkage approach for anomaly detection in granular insurance asset reporting

Author

Listed:
  • Vittoria La Serra

    (Bank of Italy)

  • Emiliano Svezia

    (Bank of Italy)

Abstract

Since 2016, insurance corporations have been reporting granular asset data in Solvency II templates on a quarterly basis. Assets are uniquely identified by codes that must be kept stable and consistent over time; nevertheless, due to reporting errors, unexpected changes in these codes may occur, leading to inconsistencies when compiling insurance statistics. The paper addresses this issue as a statistical matching problem and proposes a supervised classification approach to detect such anomalies. Test results show the potential benefits of machine learning techniques to data quality management processes, specifically of a selected random forest model for supervised binary classification, and the efficiency gains arising from automation.

Suggested Citation

  • Vittoria La Serra & Emiliano Svezia, 2023. "A robust record linkage approach for anomaly detection in granular insurance asset reporting," Questioni di Economia e Finanza (Occasional Papers) 821, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:opques:qef_821_23
    as

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    File URL: https://www.bancaditalia.it/pubblicazioni/qef/2023-0821/QEF_821_23.pdf
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    References listed on IDEAS

    as
    1. Auke Rijpma & Jeanne Cilliers & Johan Fourie, 2020. "Record linkage in the Cape of Good Hope Panel," Historical Methods: A Journal of Quantitative and Interdisciplinary History, Taylor & Francis Journals, vol. 53(2), pages 112-129, April.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    insurance data; data quality management; record linkage; statistical matching; machine learning;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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