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Pharmacy Claims Fraud Detection Using Apache Spark (Rajesh Inbasekaran and Giridharan Gurumoorthy)

937 views · Published 27 September 2018 · 37:23 · Indexed 8 November 2026

Channel: Databricks · 2018 · Science & Technology

Rajesh Inbasekaran, a founding member of the Kavi Global, and Giridharan Gurumoorthy, a Business Analytics Senior Consultant at Kavi Global LLC, go over how up to 10% of the pharmacy claims submitted to health plans and insurance companies are estimated to be fraudulent. A two-step process comprising of a combination of unsupervised and supervised learning techniques can be used to effectively identify the Fraud, Waste and Abuse in the Pharmacy industry. Claims submitted by the pharmacies to insurance companies/health plans provide data rich in valuable insights that enable prediction of fraud, waste and abuse. Suspicious activity can be identified by detecting anomalies in the data using unsupervised techniques like clustering, univariate and multi-variate outlier analysis, link analysis, simulated fraud signatures, etc.

Learn more here: https://databricks.com/session/pharmacy-claims-fraud-detection-using-apache-spark

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Pharmacy Claims Fraud Detection Using Apache Spark (Rajesh Inbasekaran and Giridharan Gurumoorthy)

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