The Global Anomaly Detection Market is projected to expand significantly during the forecast period. When a healthcare provider or an insured person offers false information in order to have it paid to another party, healthcare provider or policyholder for unauthorized benefits, then it is termed as healthcare frauds. It includes drug fraud, medical fraud, and health insurance fraud. Some of the healthcare frauds include misrepresenting dates and description of services, submitting claims for services that are not provided, and various different claims filed for the same patients by different providers. Healthcare fraud detection prevent these healthcare frauds and hence increase the adoption of such solutions in the industry.
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The global anomaly detection market is expected to show optimistic growth during the forecast period. The growth is attributed to the increasing number of fraudulent activities in the healthcare industry and the increasing population pool of the patients looking for health insurance. However, factors such as the increasing need for recurrent upgrades in the fraud detection software and the reluctance to use healthcare fraud detection solutions especially in the developing economies may drive the growth of the global anomaly detection market.
In the healthcare sector, fraudulent activities can be done by patients itself such as prescription fraud, evasion of medical charges, and fraudulent procurement of sickness certificates. The healthcare industry has witnessed the numerous cases of frauds by doctors, physicians, and other medical specialists for the sake of profit. Moreover, medical professionals are involved in fraudulent activities such as errors concerning payments for medical tests, facility services, and consultations. Electronically fraud detection cases in healthcare are common practices, while electronic fraud detection is a relatively new field within the health insurance branch.
Advances in information technology, digitalization of health care information and the research on health insurance fraud have opened an area for data mining and machine learning applications to fight fraud. Within the area of data mining and machine learning, technologies have been widely studied and with knowledge from similar areas, progress has been made. Especially data-mining (DM) is gaining more attention by researchers as a potential tool to find health insurance fraud more easily. Data mining became a possibility now supercomputers, data warehouses, and big data are becoming more commonplace.
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Global Anomaly Detection Market- Segmentation
By Deployment
- On-Premise
- Cloud-Based
By End-User
- BFSI
- Manufacturing
- IT and Telecom
- Healthcare
- Others
Global Anomaly Detection Market– Segment by Region
North America
- United States
- Canada
Europe
- UK
- Germany
- Spain
- France
- Italy
- Rest of Europe
Asia-Pacific
- India
- China
- Japan
- South Korea
- Rest of APAC
Rest of The World
Company Profiles
- Anodot, Ltd.
- Cisco Systems, Inc.
- Flowmon Networks A.S.
- Guardian Analytics, Inc.
- Gurucul Happiest Minds Technologies Pvt. Ltd.
- Hewlett Packard Enterprise Co.
- IBM Corp.
- LogRhythm, Inc.
- Microsoft Corp.
- Netskope, Inc.
- Rapid7
- SAS Institute Inc.
- Symantec Corp.
- Trend Micro Inc.
- Trustwave Holdings, Inc
- Varonis Systems, Inc.
- Verint Systems Inc.
- Wipro Ltd.
- WSO2 Inc.
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