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Usage of R Programming in Data Analytics with Implications on Insurance Fraud Detection

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International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018 (ICICI 2018)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 26))

Abstract

Data logistics and data mining has a dominant role in fraud detection and prevention scenario. Fraud analysts and risk analysts work cordially to develop a better fraud prevention and detection mechanism every year. Machine learning and Deep learning along with some statistical techniques can bring hefty changes in handling fraudsters in this sector. There are various softwares designed to handle this situation, but this paper discusses the aspects of R program in administrating the frauds in insurance claim management.

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References

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Author information

Authors and Affiliations

  1. PG & Research Department of Computer Science, Quaid-E-Millath Government College for Women, Chennai, Tamil Nadu, India

    Ananthi Sheshasaayee & Surya Susan Thomas

Authors
  1. Ananthi Sheshasaayee
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  2. Surya Susan Thomas
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Corresponding author

Correspondence to Surya Susan Thomas .

Editor information

Editors and Affiliations

  1. Department of ECE, Karunya University, Coimbatore, India

    Jude Hemanth

  2. Department of Electrical and Computer Engineering, Ryerson Communications Lab, Ryerson University, Toronto, ON, Canada

    Xavier Fernando

  3. Faculty of Engineering, Department of Telecommunication Engineering, Czech Technical University, Prague, Czech Republic

    Pavel Lafata

  4. School of Science, Joondalup Campus, Edith Cowan University, Joondalup, WA, Australia

    Zubair Baig

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Cite this paper

Sheshasaayee, A., Thomas, S.S. (2019). Usage of R Programming in Data Analytics with Implications on Insurance Fraud Detection. In: Hemanth, J., Fernando, X., Lafata, P., Baig, Z. (eds) International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018. ICICI 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-030-03146-6_46

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