Report Ocean has released a research study titled “Healthcare Fraud Analytics Market 2023 Forecast to 2031 Analysis by Market Trends.” This study offers precise economic forecasts, global assessments, and country-level insights. It provides a comprehensive view of the competitive market and includes an in-depth supply chain analysis to identify significant industry changes. The study explores the current market status, anticipated future growth, technological advancements, investment opportunities, market economics, and financial data. It thoroughly examines the market and offers insights based on a SWOT analysis of the industry.
Healthcare fraud analytics market to reach USD 6.3 billion by 2027. Global healthcare fraud analytics market is valued approximately at USD 1.2 billion in 2020 and is anticipated to grow with a healthy growth rate of about 26.7% over the forecast period 2021-2027. Healthcare fraud analytics is the fraud detection solutions and software that assist in early detection of frauds in healthcare sector such as errors in claim submissions, duplication of claims, prescription fraud by pharmacists and health insurance frauds. The global healthcare fraud analytics market is being driven by large number of fraudulent activities in healthcare and increased number of patients seeking health insurance.
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Furthermore, role of AI in healthcare fraud detection will provide new opportunities for the global healthcare fraud analytics industry. There has been a significant rise in the population seeking health insurance in different countries across the globe. For instance, as per Statista, 297 million people in the United States had health insurance, as of 2020, an increase from approximately 257 million health insured people in 2010. Also, health insurance sector market size in India was about USD 4.94 billion in 2018 which is expected to reach USD 26.72 billion by 2030. Such growth in the demand for health insurance is expected to increase the demand and adoption of healthcare fraud analytics which is likely to promote the marker growth.
Major market player included in this report are:
International Business Machines Corporation (IBM)
Optum, Inc. (Optum)
SAS Institute, Inc. (SAS)
EXL Service Holdings, Inc.
Hindustan Computers Limited Technologies Limited (HCL)
Canadian Global Information Technology Group Inc. (CGI)
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here’s a comprehensive analysis of key points related to the Healthcare Fraud Analytics market:
- Market Growth and Size:
- The Healthcare Fraud Analytics market is experiencing significant growth due to the rising incidence of fraudulent activities in the healthcare industry.
- Market size is projected to reach [provide estimated figures] by [specify the year], with a notable compound annual growth rate (CAGR).
- Types of Fraud Addressed:
- Healthcare Fraud Analytics solutions are designed to detect various types of fraud, including billing fraud, identity theft, prescription fraud, and unnecessary medical procedures. The market caters to a range of fraudulent activities within the healthcare ecosystem.
- Data Integration and Aggregation:
- Fraud analytics in healthcare relies on the integration and aggregation of vast amounts of healthcare data, including claims data, patient records, and provider information. Analyzing this data helps identify irregular patterns and potential fraud indicators.
- Machine Learning and Predictive Analytics:
- Advanced analytics technologies such as machine learning and predictive analytics play a crucial role in healthcare fraud detection. These technologies enable the identification of anomalies and prediction of potential fraudulent activities based on historical data patterns.
- Real-Time Monitoring:
- Real-time monitoring capabilities are essential in healthcare fraud analytics. Systems continuously monitor transactions and activities, providing instant alerts for suspicious behavior, enabling timely intervention.
- Collaboration with Regulatory Bodies:
- Collaboration with regulatory bodies and compliance with industry standards is critical for healthcare fraud analytics solutions. Adhering to regulations ensures that the analytics tools align with legal frameworks and standards.
- Patient Identity Verification:
- Fraud analytics in healthcare includes solutions for patient identity verification, preventing instances of identity theft and insurance fraud. Accurate patient identification is fundamental to maintaining the integrity of healthcare data.
- Cost Containment and Loss Prevention:
- Healthcare organizations adopt fraud analytics to contain costs and prevent financial losses resulting from fraudulent claims. Identifying and addressing fraudulent activities contribute to the financial health of healthcare providers and insurers.
- Behavioral Analysis:
- Behavioral analysis is a key component of healthcare fraud analytics. Understanding the typical behavior of healthcare providers, payers, and patients allows the system to identify deviations and potential fraudulent patterns.
- Integration with Electronic Health Records (EHR):
- Seamless integration with Electronic Health Records (EHR) is crucial for effective fraud detection. Connecting fraud analytics tools with EHR systems enhances the depth and accuracy of data analysis.
The detailed segments and sub-segment of the market are explained below:
By Solution Type:
By Delivery Model:
Insurance Claims Review
Pharmacy Billing Misuse
By End User:
Public & Government Agencies
Private Insurance Payers
Third-party service providers
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