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Big Data and Specific Analysis Methods for Insurance Fraud Detection

Ramona Bologa (), Razvan Bologa () and Alexandra Florea ()
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Ramona Bologa: University of Economic Studies, Bucharest, Romania
Razvan Bologa: University of Economic Studies, Bucharest, Romania
Alexandra Florea: University of Economic Studies, Bucharest, Romania

Authors registered in the RePEc Author Service: Ana Ramona Bologa

Database Systems Journal, 2013, vol. 4, issue 4, 30-39

Abstract: Analytics is the future of big data because only transforming data into information gives them value and can turn data in business in competitive advantage. Large data volumes, their variety and the increasing speed their growth, stretch the boundaries of traditional data warehouses and ETL tools. This paper investigates the benefits of Big Data technology and main methods of analysis that can be applied to the particular case of fraud detection in public health insurance system in Romania.

Keywords: Big Data; Social Networks; Data Mining; Fraud Detection (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:aes:dbjour:v:4:y:2013:i:4:p:30-39

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