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

Vittoria La Serra and Emiliano Svezia

No 821, Questioni di Economia e Finanza (Occasional Papers) from Bank of Italy, Economic Research and International Relations Area

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.

Keywords: insurance data; data quality management; record linkage; statistical matching; machine learning (search for similar items in EconPapers)
JEL-codes: C18 C81 G22 (search for similar items in EconPapers)
Date: 2023-12
New Economics Papers: this item is included in nep-big, nep-cmp and nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:bdi:opques:qef_821_23

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