The global healthcare fraud analysis market size is estimated to be $ 3,180 million in 2024 and is expected to reach $ 254.8 billion by 2025 to 2033, and forecast periods (2025-). 2033) is growing with 23.12 % CAGR.
New York, the United States, February 3, 2025 (GLOBE NEWIRE) -Healthcare fraud analysis needs to apply advanced analytical technology and data analysis to detect and suspend unauthorized activities in the medical industry. The importance of this field is increasing because medical providers, insurance companies, and government agencies are striving to identify and compete for fraud that could lead to economic retreat and patient care. Masu.
Healthcare fraud analysis allows you to identify misconduct -related patterns by adopting data modeling and machine learning methodology. Duplicated claims, integrated patient information, non -defined claim patterns, and other irregularities are examples of such patterns. Healthcare fraud analysis plays an important role in maintaining the perfection of the healthcare system by identifying and preventing fraud.
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The increase in healthcare fraud is promoting the global market.
The healthcare department is struggling with the permanent issues of healthcare fraud. The widespread occurrence of fraudulent activities in the healthcare industry is an important propulsion for implementing medical fraud analysis solutions. Various fraudulent practices are classified as fraudulent activities that include false claims, theft of personal information, and claiming schemes.
Healthcare fraud accounted for 431 cases in FY2022, based on data from the US Decision Committee. This accounts for about 8.4 % of crimes, including fraud, physical damage, and theft. Since the fiscal year in 2018, the number of individuals who have been convicted of medical fraud has increased 1.4 %. As a result, the increase in healthcare fraud has promoted a global market for healthcare fraud analysis.
The ability of fraud detection systems has been enhanced by technological development of artificial intelligence, machine learning, and data analysis. These technologies effectively reduce financial and management costs through prompt and accurate detection and preventive prevention of misconduct, compared to conventional approaches. Healthcare organizations use these technologies to analyze a huge amount of datasets and identify the patterns to predict fraud.
For example, AI supports the Indian government's health scheme in the fight against fraud. The Ministry of Health accessed by Hindu in July 2023 indicates that 210 hospitals have been empaneled, and the 53,000 L -Pee AyushMan cards have been disabled, and the 9.5 -crawl penalty has been recovered. 。 These actions were conducted according to information on fraud gained using machine learning and artificial intelligence to protect the insurance system operated by the largest global government using machine learning and artificial intelligence. 。 Thus, AI can improve fraud and prevention and create vendor opportunities to engage in the healthcare fraud analysis market.
Regional analysis
North America is the most important global healthcare fraud analysis market shareholder and is expected to expand significantly during the forecast period. Escalating medical expenses, advanced healthcare infrastructure, expansion of healthcare IT, and increased fraud, all contributing to the rule of the North American region. For example, criminal claims were recently disclosed by the US Department of Justice to 138 defendants, including 42 doctors, nurses, and other approved medical experts. These claims have been submitted to 31 federal districts nationwide. The defendant was presumed to have participated in a number of healthcare scams, so if it was taken over as a whole, an approximate loss of $ 1.4 billion occurred. This claim is about the total forecast of $ 1.1 billion of the US misconduct performed through remote medicine.
In addition, additional funds were eligible. 133 million dollars related to drug abuse treatment facilities, generally known as “SOBER HOMES,” The distribution of opioids nationwide is related. These factors are expected to stimulate the expansion of the regional market.
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Important highlights
The global healthcare fraud analysis market size is estimated to be $ 3,180 million in 2024 and is expected to reach $ 254.8 billion by 2025 to 2033, and forecast periods (2025-). 2033) is growing with 23.12 % CAGR.
Based on the solution type, the global healthcare fraud analysis market is divided into descriptive, predictive, and normative analysis. The description analysis segment is the highest contribution to the market.
Based on the deployment model, the global healthcare fraud analysis market is divided into on -premises and cloud bases. On -premises is the biggest contribution to the market.
Based on the application, the global healthcare fraud analysis market is divided into insurance claim screening, pharmacy claims, and payment of payment. Insurance billing segments are the biggest contributor in the market.
Based on end users, the global healthcare fraud analysis market is branched on public and government agencies, private insurance paymenters, third -party service providers, and employers. Public and government agencies dominate the global market.
North America is the most important global healthcare fraud analysis market shareholder and is expected to expand significantly during the forecast period.
Competitive player
IBM
Cotiviti, Inc.
DXC technology
Optum, inc.
Verisk Analytics
SAS INSTITUTE, Inc.
EXL Service Holdings, Inc.
Wipro Limited
LEXISNEXIS risk solution
CONDUENT, Inc.
HCL Technologies Limited
OSP lab
Recent development
May 2023: Teradata and Fico have announced that they will introduce an integrated advanced analysis solution for optimization, insurance claims, and real -time payment fraud. Integrated data, analysis, and insights in integrated environments promotes the efficient creation of solutions, dealing with various usage cases of financial, health care, retail, manufacturing, and travel.
June 2023: Jack Henry ™ has introduced a Payrailz® fraud monitor, a cloud native component of the AI -driven AI -driven Payrailz Digital Payments platform. This feature starts with the start of payment transactions and detects fraudulent activities in real time.
segmentation
By solution type
Description analysis
Normative analysis
Predictive analysis
By distribution model
On -premises
Cloud -based
By application
Review of insurance claim
Pharmacy billing problem
Payment consistency
others
By end user
Public and government agencies
Payer of private insurance
Third -party service provider
Employee
By region
North America
Europe
Asia -Pacific
Middle East and Africa
latin america
Detailed market segmentation @ https://straitSresearch.com/report/healthcare-fraud-analytics-market/seGmentation
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