Advanced Analytics for
Fraud Detection

Prevent Future Losses

National estimates project that billions of dollars are lost to healthcare fraud and abuse on an annual basis. These losses lead to increased healthcare costs and potential increased costs for coverage.

Duplicate submissions and payments, benefits coordination issues, billing errors, abusive provider billings, and more contribute to hundreds of billions of dollars of overpayments and fraud in healthcare in the U.S. alone.

Actian Big Data & Analytics solutions can help healthcare organizations save money, improve the quality of care, and operate more efficiently by optimizing areas such as claims processing and enabling timely advanced analytics of vast data stores. Such optimization can directly benefit an indemnity plan through claim segmentation, fraud detection and prevention, and recovery identification and capture.


Actian Big Data & Analytics provides business value with a scalable, high-throughput platform to efficiently process and analyze large data sets.

  • Verify eligibility
  • Detect duplicate claim records
  • Catch fraud before payment occurs
  • Recover revenue
  • Prevent errors or delays in care
  • Extract knowledge from massive amounts of data quickly

A leading global systems integrator for tax and revenue management services worked closely with a state government’s department of taxation to implement an identity resolution system to help the state improve its ability to efficiently collects taxes owed it. Facing a state budget squeeze, the department of taxation sought to recover additional tax revenues by identifying people and businesses that neglected to file tax returns. The systems integrator teamed with Actian Big Data & Analytics to design an innovative, tunable identity resolution solution that leverages the high-throughput Actian® DataRush™ engine,plus the advanced matching algorithms of Actian DataRush’s DataMatcher™ library.  Read more about it and download the case study at our case study page.

  • Rapidly identifies exact and close matches
  • Enables de-duplication from data entry errors
  • High throughput and scalability handles growing data volumes
  • Quickly and easily accommodates file format changes
  • Simple to add new data sources

Accelerating Big Data 2.0™