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Big Data and Specific Analysis Methods for Insurance Fraud Detection

Author

Listed:
  • Ramona BOLOGA

    (University of Economic Studies, Bucharest, Romania)

  • Razvan BOLOGA

    (University of Economic Studies, Bucharest, Romania)

  • Alexandra FLOREA

    (University of Economic Studies, Bucharest, Romania)

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.

Suggested Citation

  • Ramona BOLOGA & Razvan BOLOGA & Alexandra FLOREA, 2013. "Big Data and Specific Analysis Methods for Insurance Fraud Detection," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 4(4), pages 30-39, December.
    • Handle: RePEc:aes:dbjour:v:4:y:2013:i:4:p:30-39
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    References listed on IDEAS

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    1. Elena Geanina ULARU & Florina Camelia PUICAN & Anca APOSTU & Manole VELICANU, 2012. "Perspectives on Big Data and Big Data Analytics," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 3(4), pages 3-14, December.
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    Cited by:

    1. Martin Eling & Davide Nuessle & Julian Staubli, 2022. "The impact of artificial intelligence along the insurance value chain and on the insurability of risks," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(2), pages 205-241, April.
    2. Adela BARA & Iuliana BOTHA & Anda BELCIU & Bogdan NEDELCU, 2016. "Exploring Data in Human Resources Big Data," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 6(3), pages 3-10, January.

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