The problem of fraudulent claims is intensifying in the healthcare sector and is a burden to society. Healthcare fraud detection generally involves account auditing and detective investigation for fraudulent activities. Some of the common healthcare fraud cases include billing for services that are not provided, separate billing for laboratory tests performed together to claim higher reimbursements, usage of healthcare cards by others, and many more. Such fraudulent activities are detected by using statistical, analytical, deep learning, and predictive modeling methods. The healthcare sector is witnessing more payment breaches than ever before due to which the adoption of healthcare fraud detection solutions has gained enormous importance. Market Research Future (MRFR) has launched a new report on the global healthcare fraud detection market and has indicated that the market is primed to capture a CAGR of 26.7% over the forecast period. The Healthcare Fraud Detection market Trends was valued at USD 639.07 Mn in 2017.
Competitive Landscape
International Business Machines Corporation (IBM), Wipro, HCL Technologies, SAS Institute, Northrop Grumman, McKesson, Fair Isaac, Scio Health Analytics, Pondera Solutions, Conduent, Optum, Verscend Technologies, LexisNexis, DXC Technology, and CGI Group are the eminent players in the healthcare fraud detection market.
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Segmentation
The healthcare fraud detection market has been segmented based on component, delivery model, type, application, end-user.
- By component, the healthcare fraud detection market has been segmented into services and software.
- By delivery model, the healthcare fraud detection market has been segmented into on-premise delivery models and on-demand delivery models.
- By type, the healthcare fraud detection market has been segmented into descriptive analytics, predictive analytics, and prescriptive analytics. Descriptive analytics is the base for effective application of predictive or prescriptive analytics and the descriptive analytics segment is thus anticipated to lead the market.
- By application, the healthcare fraud detection market has been segmented into insurance claims review and payment integrity. The insurance claims review segment has been further segmented into post-payment review and prepayment review.
- By end-user, the healthcare fraud detection market has been segmented into private insurance payers, government agencies, employers, and others.
Regional Analysis
Region-wise, the healthcare fraud detection market has been segmented into the Americas, the Middle East Africa (MEA), Europe, and Asia Pacific (APAC).
The Americas is governing the global fraud detection market. The rising number of fraudulent activities in the region, along with government initiatives to curb frauds in the healthcare sector is boosting the growth of the market. Increased spending on healthcare IT, the presence of major players in the region, and technological advancements in the region are other driving factors.
The spiraling rise in the number of healthcare forgery and corruption incidents in Europe has significantly driven the healthcare fraud detection market in the region. The governments in the region are endeavoring to integrate IT into the healthcare infrastructure and are outlaying significant amounts on the same.
APAC healthcare fraud detection market is slated to expand at a torrid pace over the forecast period. Swiftly developing healthcare sector, surging incidence rate of cybercrimes in the region, and increased investment in healthcare IT are propelling the growth of the market in APAC.
The MEA market is likely to capture the least share of the market over the forecast period. The majority of the market growth is anticipated to be cornered towards the Middle East, where investments are being poured in for the development of the healthcare sector due to rising incidences of health insurance frauds.
Industry Updates
- August 2019 - Deep Labs, am AI-driven technology company partnered with Visual Connections, provider of a spectrum of cutting-edge IT services and solutions, to develop AI-driven healthcare fraud detection system.
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