• Sahana Munavalli
• Sanjeevkumar Hatture

Fraud and abuse in the health care system have become a significant concern and that too inside health insurance organizations. In the last decade due to expanding misfortunes in incomes, handling medical claims have become a debilitating manual assignment, which is done by a couple of clinical specialists who have the duty of endorsing, adjusting, or dismissing the appropriations mentioned inside a restricted period from their gathering. Standard data mining techniques at this point do not sufficiently address the intricacy of the world. In this way, utilizing Symbolic Data Analysis is another sort of data analysis that permits us to address the intricacy of the real world and to recognize fraud in the healthcare data. In the era of digitization, the frauds are found in all categories of health insurance. It is finished next to deliberate trickiness or fraud for acquiring some pitiful advantage in the form of health expenditures. Bigdata analysis can be utilized to recognize fraud in large sets of insurance claim data. In light of a couple of cases that are known or suspected to be false, the fraud detection technique computes the closeness of each record to be fake by investigating the previous insurance claims. The investigators would then be able to have a nearer examination for the cases that have been set apart by data mining programming. One of the issues in healthcare system claims is the abuse of the medical insurance. Manual detection of frauds in the healthcare industry is strenuous work. In the proposed work the symbolic data object representation reduces the complexity of the medical data and machine learning and symbolic data analysis recognize the fraud detection. The symbolic data approach for fraud detection in healthcare system achieves promising results and can be extended to other healthcare systems.

Fraud detection; Anomaly detection; Data mining; Health insurance; Symbolic data

"Symbolic Data Approach For Fraud Detection In Healthcare System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 7, page no.e313-e323, July-2021, Available :http://www.jetir.org/papers/JETIR2107546.pdf

"Symbolic Data Approach For Fraud Detection In Healthcare System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 7, page no. ppe313-e323, July-2021, Available at : http://www.jetir.org/papers/JETIR2107546.pdf