IDEAS home Printed from https://ideas.repec.org/a/aes/dbjour/v4y2013i4p30-39.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://dbjournal.ro/archive/14/14_4.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.
    3. Martin Eling & Irina Gemmo & Danjela Guxha & Hato Schmeiser, 2024. "Big data, risk classification, and privacy in insurance markets," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 49(1), pages 75-126, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anca APOSTU & Florina PUICAN & Geanina ULARU & George SUCIU & Gyorgy TODORAN, 2014. "New Classes of Applications in the Cloud. Evaluating Advantages and Disadvantages of Cloud Computing for Telemetry Applications," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 5(1), pages 3-14, May.
    2. Zhuang Weiqing & Wang Morgan C. & Nakamoto Ichiro & Jiang Ming, 2021. "Big Data Analytics in E-commerce for the U.S. and China Through Literature Reviewing," Journal of Systems Science and Information, De Gruyter, vol. 9(1), pages 16-44, February.
    3. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aes:dbjour:v:4:y:2013:i:4:p:30-39. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Adela Bara (email available below). General contact details of provider: https://edirc.repec.org/data/aseeero.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.