Health insurance fraud detection

• Author(s) / Creator(s)

  • Gill, Jasmine Kaur

• Healthcare Fraud is an act that causes a loss of billions of dollars every year across the world. The impact of healthcare fraud is very far-reaching and affects the efficiency of healthcare systems. To thwart the perpetrators early on, intelligent fraud detection technologies are required to predict the strategies and schemes in sophisticated organized fraud cases. The work already done in the field of healthcare insurance fraud has been discussed in a systematic literature review with a particular focus on its detection techniques and various aspects associated with it. There are many application solutions available in the market that can be used to detect healthcare fraud. This paper provides a side-by-side comparison of three existing application solutions for fraud detection pertaining to the healthcare insurance domain. The comparative study forms the basis for listing the features desired in an ideal healthcare fraud detection application solution. The research done in this paper aimed to provide a list of features of a best-in-class healthcare insurance fraud detection application solution. Also, some of the key challenges and issues faced by the fraud detection industry have been highlighted along with the potential future direction of research.

• Date created

  2020

• Subjects / Keywords

  • healthcare fraud
  • fraud detection
  • data mining
  • machine learning
  • artificial intelligence

• Type of Item

  Research Material

• DOI

  https://doi.org/10.7939/r3-wvjc-sd55

• License

  Attribution-NonCommercial 4.0 International