• Cat-intel
  • MedIntelliX
  • Consulting
  • Resources
  • About Us
  • News
  • Careers
  • Contact Us
  • Login
    • Request Free Sample ×
    Medical Payment Fraud Detection Market Research Report - Forecast till 2034 Infographic

    Kindly complete the form below to receive a free sample of this Report

    Leading companies partner with us for data-driven Insights

    clients tt-cursor

    Medical Payment Fraud Detection Market

    ID: MRFR/MED/8300-HCR
    120 Pages
    Kinjoll Dey
    September 2025

    Medical Payment Fraud Detection Market Research Report Information By Type (Descriptive Analytics, Predictive Analytics, Prescriptive Analytics), By Component (Services, Software), By Delivery Mode (On-premise, Cloud-based), By Source of Service (In-house, Outsourced), By End-User (Private Insurance Payers, Public/Government Agencies, Third-Party Service Providers), And By Region (North America, Europe, Asia-Pacific, And Rest Of The World) –Market Forecast Till 2034

    Share:
    Download PDF ×

    We do not share your information with anyone. However, we may send you emails based on your report interest from time to time. You may contact us at any time to opt-out.

    Medical Payment Fraud Detection Market Research Report - Forecast till 2034 Infographic
    Purchase Options
    $ 4,950.0
    $ 5,950.0
    $ 7,250.0
    Compare License
    Table of Contents

    Medical Payment Fraud Detection Market Summary

    The Global Medical Payment Fraud Detection Market is projected to experience substantial growth from 1.76 USD Billion in 2024 to 14.7 USD Billion by 2035.

    Key Market Trends & Highlights

    Medical Payment Fraud Detection Key Trends and Highlights

    • The market is expected to grow at a compound annual growth rate of 21.29% from 2025 to 2035.
    • By 2035, the market valuation is anticipated to reach 14.7 USD Billion, indicating a robust expansion.
    • In 2024, the market is valued at 1.76 USD Billion, highlighting its current scale and potential for growth.
    • Growing adoption of advanced analytics due to increasing fraudulent activities is a major market driver.

    Market Size & Forecast

    2024 Market Size 1.76 (USD Billion)
    2035 Market Size 14.7 (USD Billion)
    CAGR (2025-2035) 21.29%

    Major Players

    LexisNexis Risk Solutions, International Business Machines Corporation, Optuminsight, OSP Labs, DXC Technology Company, Unitedhealth Group, SAS Institute, Fair Isaac Corporation, EXL Service Holdings, Inc., CGI GROUP

    Medical Payment Fraud Detection Market Trends

      • Growing obese population is driving the market growth

    The market CAGR for medical payment fraud detection is expanding as a result of a significant number of fraudulent actions in the healthcare industry. Fraud based on deception or misrepresentation can be committed by healthcare professionals, patients, and other individuals who purposefully trick the healthcare system into granting them illegal advantages. Kickbacks, billing, invoicing for services that were never rendered, medical testing, and other fraudulent practices are all part of this fraud and abuse.

    In 2021, the National Health Care Anti-Fraud Association projected that medical payment fraud costs the country roughly $68 billion year, or about 3% of the $2.26 trillion in health care spending, according to Blue Cross Blue Shield Association, a US-based federation. According to other estimates, the amount might reach $230 billion, or 10% of annual health care spending. Consequently, the market for medical payment fraud detection is expanding as a result of the rising number of fraudulent activities in the field of medicine.

    A prominent trend gaining traction in the medical payment fraud detection market is the adoption and development of new technologies. To bolster their market position, the main corporations are concentrating on releasing products and services that are driven by statistical data analysis and artificial intelligence (AI). These statistical operations include data mining, regression analysis, machine learning, pattern recognition, supervised learning, and unsupervised learning. These fraud detection approaches also do other statistical tasks. For instance, Codoxo, a US-based AI-driven healthcare solution, introduced its healthcare integrity suite in December 2020.

    The ongoing evolution of technology in healthcare is likely to enhance the capabilities of fraud detection systems, thereby improving the integrity of medical payment processes.

    U.S. Department of Health and Human Services

    Medical Payment Fraud Detection Market Drivers

    Market Growth Projections

    The Global Medical Payment Fraud Detection Market Industry is projected to experience substantial growth in the coming years. The market is expected to reach a valuation of 1.76 USD Billion in 2024 and is anticipated to expand to 14.7 USD Billion by 2035. This growth trajectory suggests a compound annual growth rate (CAGR) of 21.29% from 2025 to 2035. Such projections indicate a robust demand for innovative fraud detection solutions as healthcare organizations seek to combat the rising tide of fraudulent activities. The increasing complexity of healthcare billing and the need for compliance with regulatory standards further contribute to this market expansion.

    Rising Healthcare Expenditure

    Rising healthcare expenditure is a substantial factor influencing the Global Medical Payment Fraud Detection Market Industry. As global healthcare spending continues to increase, the potential for fraud also escalates. With healthcare costs projected to rise significantly, the financial stakes associated with fraudulent claims become more pronounced. This scenario compels healthcare providers and insurers to adopt advanced fraud detection mechanisms to protect their financial interests. The market's growth trajectory, with an expected value of 14.7 USD Billion by 2035, indicates that stakeholders are increasingly prioritizing investments in fraud detection technologies to mitigate risks associated with rising expenditures.

    Growing Awareness Among Stakeholders

    Growing awareness among stakeholders regarding the impact of medical payment fraud is a significant driver for the Global Medical Payment Fraud Detection Market Industry. Healthcare providers, insurers, and patients are increasingly recognizing the detrimental effects of fraud on healthcare systems. This heightened awareness is prompting stakeholders to seek out effective fraud detection solutions to protect their interests. As a result, investments in fraud detection technologies are on the rise, with healthcare organizations prioritizing the implementation of systems that can safeguard against fraudulent activities. This trend is expected to contribute to the market's robust growth in the coming years.

    Increasing Incidence of Fraudulent Claims

    The rising incidence of fraudulent claims is a primary driver for the Global Medical Payment Fraud Detection Market Industry. As healthcare costs escalate, fraudulent activities such as billing for services not rendered or upcoding have become more prevalent. In 2024, the market is valued at 1.76 USD Billion, reflecting the urgent need for robust detection systems. The financial implications of these fraudulent claims are substantial, with estimates suggesting that healthcare fraud costs the industry billions annually. Consequently, healthcare providers and insurers are increasingly investing in advanced fraud detection technologies to mitigate these losses and enhance operational efficiency.

    Technological Advancements in Detection Systems

    Technological advancements play a crucial role in shaping the Global Medical Payment Fraud Detection Market Industry. Innovations such as artificial intelligence and machine learning are being integrated into fraud detection systems, enabling more accurate identification of suspicious activities. These technologies can analyze vast amounts of data in real-time, significantly improving the efficiency of fraud detection processes. As the market is projected to grow to 14.7 USD Billion by 2035, the adoption of these advanced technologies is likely to accelerate, providing healthcare organizations with the tools necessary to combat increasingly sophisticated fraudulent schemes.

    Regulatory Compliance and Government Initiatives

    Regulatory compliance and government initiatives are pivotal in driving the Global Medical Payment Fraud Detection Market Industry. Governments worldwide are implementing stricter regulations to combat healthcare fraud, which necessitates the adoption of effective fraud detection solutions. For instance, the Centers for Medicare & Medicaid Services in the United States has introduced various programs aimed at reducing fraud and abuse in healthcare. These initiatives not only promote accountability but also encourage healthcare providers to invest in fraud detection technologies, thereby expanding the market. The anticipated CAGR of 21.29% from 2025 to 2035 underscores the growing importance of compliance in this sector.

    Market Segment Insights

    Medical Payment Fraud Detection Type Insights

    The medical payment fraud detection market segmentation, based on type includes Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics. The descriptive analytics segment dominated the market due to its widespread use and simplicity. It uses both recent and historical data to find trends and connections. This improves the process of identifying potential scams. Additionally, it serves as a foundation for the efficient use of prescriptive and predictive analytics. This helps the segment's expansion even more.

    Figure 1: Medical Payment Fraud Detection Market, by Type, 2022 & 2032 (USD billion) 

    Medical Payment Fraud Detection Market, by Type, 2022 & 2032

    Source: Secondary Research, Primary Research, Market Research Future Database and Analyst Review

    Medical Payment Fraud Detection Component Insights

    The medical payment fraud detection market segmentation, based on component, includes Services and Software. The services category generated the most income. The detection of fraudulent activity in the delivery of medical services is known as service medical payment fraud detection. It involves charging for goods or services that are not received and billing for services that are not provided. The payment of kickbacks and bribes by service providers to refer patients to their facilities is another type of service healthcare fraud.

    Medical Payment Fraud Detection Delivery Mode Insights

    The medical payment fraud detection market segmentation, based on delivery mode, includes On-premise and Cloud-based. The on-premise category generated the most income because data is readily accessible on the website, i.e., hospitals, etc., which has led to better record management and data monitoring, among other things. The current technologies are useful in small organisations, but when scaled up, they can make data management challenging and laborious if the organization works with a sizable dataset. This could entail a substantial financial outlay for data security and storage.

    Medical Payment Fraud Detection Source of Service Insights

    The medical payment fraud detection market segmentation, based on source of service, includes In-house and Outsourced. The outsourced category generated the most income. Medical billing services are third parties providers can use to outsource their medical payment. As compensation for handling several facets of the clinic's revenue cycle management, these billing services often take a percentage of a practice's collections.

    Medical Payment Fraud Detection End-User Insights

    The medical payment fraud detection market segmentation, based on end-user, includes Private Insurance Payers, Public/Government Agencies, and Third-Party Service Providers. The private insurance payers category generated the most income because more individuals are purchasing health insurance; it also causes an increase in the amount of false claims. Prepayment review and post-payment review are further divisions of the segment.

    Regional Insights

    By region, the study provides the market insights into North America, Europe, Asia-Pacific and Rest of the World. The North American medical payment fraud detection market area will dominate this market due to factors including the high healthcare spending per capita, the sizable elderly and sick population, the high number of persons with health insurance, the prevalence of medical payment fraud, the favorable government anti-fraud programs, and the push to lower healthcare costs.

    The expansion of the business in the region is also being aided by the rise in service providers and technological developments in software designed to catch such misconduct.

    Further, the major countries studied in the market report are The US, Canada, German, France, the UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.

    Figure 2: MEDICAL PAYMENT FRAUD DETECTION MARKET SHARE BY REGION 2022 (%) 

    MEDICAL PAYMENT FRAUD DETECTION MARKET SHARE BY REGION 2022

    Source: Secondary Research, Primary Research, Market Research Future Database and Analyst Review

    Europe medical payment fraud detection market accounts for the second-largest market share due to improvements in the health infrastructure of the surrounding nations, an increase in the prevalence of infectious diseases, and favorable reimbursement policies. Further, the German medical payment fraud detection market held the largest market share, and the UK medical payment fraud detection market was the fastest growing market in the European region

    The Asia-Pacific Medical payment fraud detection Market is expected to grow at the fastest CAGR from 2023 to 2032 due to the existence of major industry players as well as the increased adoption of cutting-edge medical imaging equipment and software in developing nations like India and China. Moreover, China’s medical payment fraud detection market held the largest market share, and the Indian medical payment fraud detection market was the fastest growing market in the Asia-Pacific region.

    Key Players and Competitive Insights

    Leading market players are investing heavily in research and development in order to expand their product lines, which will help the medical payment fraud detection market, grow even more. Market participants are also undertaking a variety of strategic activities to expand their footprint, with important market developments including new product launches, contractual agreements, mergers and acquisitions, higher investments, and collaboration with other organizations. To expand and survive in a more competitive and rising market climate, medical payment fraud detection industry must offer cost-effective items.

    Manufacturing locally to minimize operational costs is one of the key business tactics used by manufacturers in the medical payment fraud detection industry to benefit clients and increase the market sector. In recent years, the medical payment fraud detection industry has offered some of the most significant advantages to medicine. Major players in the medical payment fraud detection market attempting to increase market demand by investing in research and development operations include LexisNexis Risk Solutions, International Business Machines Corporation, Optuminsight, OSP Labs, DXC Technology Company, Unitedhealth Group, SAS Institute, Fair Isaac Corporation, EXL Service Holdings, Inc., and CGI GROUP.

    Data management and business intelligence software services are offered by SAS Institute Inc (SAS). The company's solution portfolio comprises advanced analytics solutions, AI, ML, cloud, data management, decisioning, fraud and security intelligence, IoT, marketing analytics, operationalizing analytics, and risk management. Agriculture, banking, education, healthcare, insurance, the life sciences, manufacturing, the public sector, retail and consumer goods, small and midsize businesses, sports, communications, media and technology, and utilities are just a few of the sectors SAS supports.

    A provider of consultancy services and information technology (IT), DXC Technology Co. The company's service portfolio comprises workplace and mobility solutions, analytics, cloud applications, cloud infrastructure, corporate apps, data security services, and IT outsourcing (ITO). It additionally offers its services via a network of partners. DXC provides services to the insurance, healthcare, life sciences, aerospace, defence, consumer, retail, manufacturing, travel, hotel, utilities, oil and gas, technology, media, and telecommunications sectors, as well as the public, banking, and capital markets.

    Key Companies in the Medical Payment Fraud Detection Market market include

    Industry Developments

    June 2020: WhiteHatAI was purchased by Sharecare, an Atlanta-based digital health startup, for an unknown sum. By acquiring WhiteHatAI, a portfolio-based AI-driven suite that assists in detecting FWA before it happens, Sharecare will be able to increase the efficiency and effectiveness of healthcare organizations. Healthcare artificial intelligence firm WhiteHatAI is in the US and focuses on preventing fraud, waste, and abuse in healthcare payments.

    Future Outlook

    Medical Payment Fraud Detection Market Future Outlook

    The Medical Payment Fraud Detection Market is projected to grow at a 21.29% CAGR from 2024 to 2035, driven by technological advancements, regulatory changes, and increasing fraud cases.

    New opportunities lie in:

    • Develop AI-driven analytics tools to enhance fraud detection accuracy.
    • Implement blockchain technology for secure transaction verification.
    • Create tailored compliance solutions for diverse healthcare providers.

    By 2035, the market is expected to be robust, reflecting substantial advancements in fraud detection technologies.

    Market Segmentation

    Medical Payment Fraud Detection Type Outlook

    • Descriptive Analytics
    • Predictive Analytics
    • Prescriptive Analytics

    Medical Payment Fraud Detection End-User Outlook

    • Private Insurance Payers
    • Public/Government Agencies
    • Third-Party Service Providers

    Medical Payment Fraud Detection Regional Outlook

    • US
    • Canada

    Medical Payment Fraud Detection Component Outlook

    • Services
    • Software

    Medical Payment Fraud Detection Delivery Mode Outlook

    • On-premise
    • Cloud-based

    Medical Payment Fraud Detection Source of Service Outlook

    • In-house
    • Outsourced

    Report Scope

    Report Attribute/Metric Details
    Market Size 2024    1.76 (USD Billion)
    Market Size 2025    2.13 (USD Billion)
    Market Size 2034   12.13 (USD Billion)
    Compound Annual Growth Rate (CAGR)   21.30 % (2025 - 2034)
    Report Coverage Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
    Base Year 2024
    Market Forecast Period 2025 - 2034
    Historical Data 2020 - 2024
    Report Coverage Revenue Forecast, Market Competitive Landscape, Growth Factors, and Trends
    Segments Covered Type, Component, Delivery Mode, Source of Services, End-User, and Region
    Geographies Covered North America, Europe, Asia Pacific, and the Rest of the World
    Countries Covered The US, Canada, German, France, UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil
    Key Companies Profiled LexisNexis Risk Solutions, International Business Machines Corporation, Optuminsight, OSP Labs, DXC Technology Company, Unitedhealth Group, SAS Institute, Fair Isaac Corporation, EXL Service Holdings, Inc., and CGI GROUP.
    Key Market Opportunities Payments in response to the COVID 19 pandemic could unleash an unpredicted surge of healthcare scams and frauds
    Key Market Dynamics The rising number of patients opting for health insurance Increasing pressure of fraud

    Market Highlights

    Author
    Kinjoll Dey
    Research Analyst Level I

    He is an extremely curious individual currently working in Healthcare and Medical Devices Domain. Kinjoll is comfortably versed in data centric research backed by healthcare educational background. He leverages extensive data mining and analytics tools such as Primary and Secondary Research, Statistical Analysis, Machine Learning, Data Modelling. His key role also involves Technical Sales Support, Client Interaction and Project management within the Healthcare team. Lastly, he showcases extensive affinity towards learning new skills and remain fascinated in implementing them.

    Get In Touch
    Leave a Comment

    FAQs

    How much is the medical payment fraud detection market?

    The global medical payment fraud detection market size was valued at USD 1.2 Billion in 2022.

    What is the growth rate of the medical payment fraud detection market?

    The global market is projected to grow at a CAGR of 21.30% during the forecast period, 2023-2032.

    Which region held the largest market share in the medical payment fraud detection market?

    North America had the largest share in the global market

    Who are the key players in the medical payment fraud detection market?

    The key players in the market are LexisNexis Risk Solutions, International Business Machines Corporation, Optuminsight, OSP Labs, DXC Technology Company, Unitedhealth Group, SAS Institute, Fair Isaac Corporation, EXL Service Holdings, Inc., and CGI GROUP.

    Which type led the medical payment fraud detection market?

    The descriptive analytics category dominated the market in 2022.

    Which source of service had the largest market share in the medical payment fraud detection market?

    The outsourced category had the largest share in the global market.

    1. 'Table of Contents
    2. EXECUTIVE SUMMARY
      1. Market Attractiveness Analysis
        1. Global Medical Payment Fraud Detection Market, by Type
        2. Global
    3. Medical Payment Fraud Detection Market, by Component
      1. Global Medical
    4. Payment Fraud Detection Market, by Delivery Model
      1. Global Medical Payment
    5. Fraud Detection Market, by Source of Services
      1. Global Medical Payment
    6. Fraud Detection Market, by End User
    7. MARKET INTRODUCTION
      1. Definition
      2. Scope of the Study
        1. Research Objective
        2. Assumptions
        3. Limitations
    8. RESEARCH METHODOLOGY
      1. Overview
      2. Data
    9. Mining
      1. Secondary Research
      2. Primary Research
        1. Breakdown
    10. of Primary Respondents
      1. Forecasting Mode
      2. Research Methodology
    11. for Market Size Estimation
      1. Bottom-Up Approach
        1. Top-Down Approach
      2. Data Triangulation
      3. Validation
    12. MARKET DYNAMICS
    13. Overview
      1. Drivers
      2. Restraints
      3. Opportunities
    14. MARKET FACTOR ANALYSIS
      1. Porter’s Five Forces Analysis
    15. Bargaining Power of Suppliers
      1. Bargaining Power of Buyers
    16. Threat of New Entrants
      1. Threat of Substitutes
        1. Intensity of
    17. Rivalry
      1. Value Chain Analysis
        1. R&D and Designing
    18. Manufacturing
      1. Distribution & Sales
        1. Post Sales Type
      2. Impact of Coronavirus (COVID-19) on Global Medical Payment Fraud Detection
    19. Market
      1. Demand-Supply Analysis
        1. Capital Expenditure
    20. Pricing Analysis
      1. Consumption Analysis
        1. Impact on Key Players
        2. Role of Government
    21. GLOBAL MEDICAL PAYMENT FRAUD DETECTION MARKET,
    22. BY TYPE
      1. Overview
      2. Descriptive Analytics
    23. Market Estimates
    24. & Forecast, by Region, 2023–2030
    25. Market Estimates & Forecast,
    26. by Country, 2023–2030
      1. Predictive Analytics
    27. Market Estimates
    28. & Forecast, by Region, 2023–2030
    29. Market Estimates & Forecast,
    30. by Country, 2023–2030
      1. Prescriptive Analytics
    31. Market Estimates
    32. & Forecast, by Region, 2023–2030
    33. Market Estimates & Forecast,
    34. by Country, 2023–2030
    35. GLOBAL MEDICAL PAYMENT FRAUD DETECTION MARKET,
    36. BY COMPONENT
      1. Overview
      2. Services
    37. Market Estimates & Forecast,
    38. by Region, 2023–2030
    39. Market Estimates & Forecast, by Country, 2023–2030
      1. Software
    40. Market Estimates & Forecast, by Region, 2023–2030
    41. Market Estimates & Forecast, by Country, 2023–2030
    42. GLOBAL MEDICAL
    43. PAYMENT FRAUD DETECTION MARKET, BY DELIVERY MODEL
      1. Overview
      2. On-Premise
    44. Market Estimates & Forecast, by Region, 2023–2030
    45. Market Estimates
    46. & Forecast, by Country, 2023–2030
      1. Cloud-Based
    47. Market Estimates
    48. & Forecast, by Region, 2023–2030
    49. Market Estimates & Forecast,
    50. by Country, 2023–2030
    51. GLOBAL MEDICAL PAYMENT FRAUD DETECTION
    52. MARKET, BY SOURCE OF SERVICES
      1. Overview
      2. In-house
    53. Market
    54. Estimates & Forecast, by Region, 2023–2030
    55. Market Estimates &
    56. Forecast, by Country, 2023–2030
      1. Outsourced
    57. Market Estimates
    58. & Forecast, by Region, 2023–2030
    59. Market Estimates & Forecast,
    60. by Country, 2023–2030
    61. GLOBAL MEDICAL PAYMENT FRAUD DETECTION MARKET,
    62. BY END USER
      1. Overview
      2. Private Insurance Payers
    63. Market
    64. Estimates & Forecast, by Region, 2023–2030
    65. Market Estimates &
    66. Forecast, by Country, 2023–2030
      1. Public/Government Agencies
    67. Market
    68. Estimates & Forecast, by Region, 2023–2030
    69. Market Estimates &
    70. Forecast, by Country, 2023–2030
      1. Third-Party Service Providers
    71. Market Estimates & Forecast, by Region, 2023–2030
    72. Market Estimates
    73. & Forecast, by Country, 2023–2030
    74. GLOBAL MEDICAL PAYMENT FRAUD
    75. DETECTION MARKET, BY REGION
      1. Overview
      2. Americas
    76. North America
      1. US
        1. Canada
        2. Latin America
      2. Europe
        1. Western Europe
    77. France
      1. Italy
        1. Spain
    78. Rest of Western Europe
      1. Eastern Europe
      2. Asia-Pacific
    79. Japan
      1. China
        1. India
        2. Australia
    80. South Korea
      1. Rest of Asia-Pacific
      2. Middle East & Africa
        1. Middle East
        2. Africa
    81. COMPANY LANDSCAPE
    82. Overview
      1. Competitor Dashboard
      2. Major Growth Strategy in the
    83. Global Medical Payment Fraud Detection Market
      1. Competitive Benchmarking
      2. The Leading Player in terms of Number of Developments in the Global Medical
    84. Payment Fraud Detection Market
      1. Key Developments & Growth Strategies
        1. New Product Launch/Service Deployment
        2. Merger & Acquisition
        3. Joint Ventures
      2. Major Players Financial Matrix & Market
    85. Ratio
      1. Sales & Operating Income 2018
        1. Major Players
    86. R&D Expenditure 2018
    87. COMPANY PROFILES
      1. LexisNexis Risk Solutions
        1. Company Overview
        2. Products/Type Offered
        3. Financial
    88. Overview
      1. Key Developments
        1. SWOT Analysis
        2. Key
    89. Strategies
      1. International Business Machines Corporation
      2. Optuminsight
      3. OSP Labs
      4. DXC Technology Company
      5. Unitedhealth Group
      6. SAS Institute
      7. Fair Isaac Corporation
      8. EXL Service Holdings,
    90. Inc.
      1. CGI GROUP
      2. Others
    91. APPENDIX
      1. References
      2. Related Reports
    92. NOTE:
    93. This table of content is tentative and subject
    94. to change as the research progresses.
    95.   In section 13, only the top companies
    96. will be profiled. Each company will be profiled based on the Market Overview, Financials,
    97. Product Portfolio, Business Strategies, and Recent Developments parameters.
    98.  Please note: The financial details of the company cannot be provided if the information
    99. is not available in the public domain and or from reliable sources.
    100. LIST
    101. OF TABLES
    102. –2030 (USD MILLION)
    103. MARKET, BY TYPE, 2023–2030 (USD MILLION)
    104. FRAUD DETECTION MARKET, BY COMPONENT, 2023–2030 (USD MILLION)
    105. GLOBAL MEDICAL PAYMENT FRAUD DETECTION MARKET, BY DELIVERY MODEL, 2023–2030
    106. (USD MILLION)
    107. OF TYPE, 2023–2030 (USD MILLION)
    108. DETECTION MARKET, BY END USER, 2023–2030 (USD MILLION)
    109. MEDICAL PAYMENT FRAUD DETECTION MARKET, BY REGION, 2023–2030 (USD MILLION)
    110. (USD MILLION)
    111. BY COMPONENT, 2023–2030 (USD MILLION)
    112. PAYMENT FRAUD DETECTION MARKET, BY DELIVERY MODEL, 2023–2030 (USD MILLION)
    113. –2030 (USD MILLION)
    114. DETECTION MARKET, BY END USER, 2023–2030 (USD MILLION)
    115. PAYMENT FRAUD DETECTION MARKET, BY TYPE, 2023–2030 (USD MILLION)
    116. US: MEDICAL PAYMENT FRAUD DETECTION MARKET, BY COMPONENT, 2023–2030 (USD
    117. MILLION)
    118. –2030 (USD MILLION)
    119. MARKET, BY SOURCE OF TYPE, 2023–2030 (USD MILLION)
    120. PAYMENT FRAUD DETECTION MARKET, BY END USER, 2023–2030 (USD MILLION)
    121. CANADA: MEDICAL PAYMENT FRAUD DETECTION MARKET, BY TYPE, 2023–2030 (USD
    122. MILLION)
    123. –2030 (USD MILLION)
    124. MARKET, BY DELIVERY MODEL, 2023–2030 (USD MILLION)
    125. PAYMENT FRAUD DETECTION MARKET, BY SOURCE OF TYPE, 2023–2030 (USD MILLION)
    126. (USD MILLION)
    127. BY TYPE, 2023–2030 (USD MILLION)
    128. FRAUD DETECTION MARKET, BY COMPONENT, 2023–2030 (USD MILLION)
    129. LATIN AMERICA: MEDICAL PAYMENT FRAUD DETECTION MARKET, BY DELIVERY MODEL, 2023–2030
    130. (USD MILLION)
    131. BY SOURCE OF TYPE, 2023–2030 (USD MILLION)
    132. PAYMENT FRAUD DETECTION MARKET, BY END USER, 2023–2030 (USD MILLION)
    133. EUROPE: MEDICAL PAYMENT FRAUD DETECTION MARKET, BY TYPE, 2023–2030 (USD
    134. MILLION)
    135. –2030 (USD MILLION)
    136. MARKET, BY DELIVERY MODEL, 2023–2030 (USD MILLION)
    137. PAYMENT FRAUD DETECTION MARKET, BY SOURCE OF TYPE, 2023–2030 (USD MILLION)
    138. (USD MILLION)
    139. DETECTION MARKET, BY TYPE, 2023–2030 (USD MILLION)
    140. MEDICAL PAYMENT FRAUD DETECTION MARKET, BY COMPONENT, 2023–2030 (USD MILLION)
    141. BY DELIVERY MODEL, 2023–2030 (USD MILLION)
    142. PAYMENT FRAUD DETECTION MARKET, BY SOURCE OF TYPE, 2023–2030 (USD MILLION)
    143. –2030 (USD MILLION)
    144. DETECTION MARKET, BY TYPE, 2023–2030 (USD MILLION)
    145. MEDICAL PAYMENT FRAUD DETECTION MARKET, BY COMPONENT, 2023–2030 (USD MILLION)
    146. –2030 (USD MILLION)
    147. DETECTION MARKET, BY SOURCE OF TYPE, 2023–2030 (USD MILLION)
    148. EASTERN EUROPE: MEDICAL PAYMENT FRAUD DETECTION MARKET, BY END USER, 2023–2030
    149. (USD MILLION)
    150. BY TYPE, 2023–2030 (USD MILLION)
    151. FRAUD DETECTION MARKET, BY COMPONENT, 2023–2030 (USD MILLION)
    152. ASIA-PACIFIC: MEDICAL PAYMENT FRAUD DETECTION MARKET, BY DELIVERY MODEL, 2023–2030
    153. (USD MILLION)
    154. BY SOURCE OF TYPE, 2023–2030 (USD MILLION)
    155. PAYMENT FRAUD DETECTION MARKET, BY END USER, 2023–2030 (USD MILLION)
    156. MIDDLE EAST & AFRICA: MEDICAL PAYMENT FRAUD DETECTION MARKET, BY TYPE, 2023–2030
    157. (USD MILLION)
    158. MARKET, BY COMPONENT, 2023–2030 (USD MILLION)
    159. AFRICA: MEDICAL PAYMENT FRAUD DETECTION MARKET, BY DELIVERY MODEL, 2023–2030
    160. (USD MILLION)
    161. MARKET, BY SOURCE OF TYPE, 2023–2030 (USD MILLION)
    162. & AFRICA: MEDICAL PAYMENT FRAUD DETECTION MARKET, BY END USER, 2023–2030
    163. (USD MILLION)
    164. MODEL 2018 (%)
    165. BY SOURCE OF TYPE, 2018 (%)
    166. MARKET SHARE, BY END USER, 2018 (%)
    167. MARKET SHARE, BY REGION, 2018 (%)
    168. DETECTION MARKET SHARE BY REGION, 2018 (%)
    169. PAYMENT FRAUD DETECTION MARKET SHARE, BY COUNTRY, 2018 (%)
    170. MEDICAL PAYMENT FRAUD DETECTION MARKET SHARE, BY REGION, 2018 (%)
    171. WESTERN EUROPE: MEDICAL PAYMENT FRAUD DETECTION MARKET SHARE, BY COUNTRY, 2018 (%)
    172. MARKET SHARE, BY COUNTRY, 2018 (%)
    173. MARKET: COMPANY SHARE ANALYSIS, 2018 (%)
    174. KEY FINANCIALS
    175. LEXISNEXIS RISK SOLUTIONS: REGIONAL REVENUE
    176. MACHINES CORPORATION: KEY FINANCIALS
    177. CORPORATION.: SEGMENTAL REVENUE
    178. REGIONAL REVENUE
    179. SEGMENTAL REVENUE
    180. LABS: KEY FINANCIALS
    181. LABS: REGIONAL REVENUE
    182. COMPANY: REGIONAL REVENUE
    183. UNITEDHEALTH GROUP: SEGMENTAL REVENUE
    184. REVENUE
    185. SEGMENTAL REVENUE
    186. FAIR ISAAC CORPORATION: KEY FINANCIALS
    187. REVENUE
    188. SERVICE HOLDINGS, INC.: KEY FINANCIALS
    189. SEGMENTAL REVENUE

    Market Segmentation

    Medical Payment Fraud Detection Type Outlook (USD Billion, 2018-2032)

    • Descriptive Analytics
    • Predictive Analytics
    • Prescriptive Analytics

    Medical Payment Fraud Detection Component Outlook (USD Billion, 2018-2032)

    • Services
    • Software

    Medical Payment Fraud Detection Delivery Model Outlook (USD Billion, 2018-2032)

    • On-premise
    • Cloud-based

    Medical Payment Fraud Detection Source of Service Outlook (USD Billion, 2018-2032)

    • In-house
    • Outsourced

    Medical Payment Fraud Detection End-User Outlook (USD Billion, 2018-2032)

    • Private Insurance Payers
    • Public/Government Agencies
    • Third-Party Service Providers

    Medical Payment Fraud Detection Regional Outlook (USD Billion, 2018-2032)

    • North America Outlook (USD Billion, 2018-2032)

      • North America Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • North America Medical Payment Fraud Detection by Component

        • Services
        • Software

      • North America Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • North America Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • North America Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • US Outlook (USD Billion, 2018-2032)

      • US Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • US Medical Payment Fraud Detection by Component

        • Services
        • Software

      • US Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • US Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • US Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • CANADA Outlook (USD Billion, 2018-2032)

      • CANADA Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • CANADA Medical Payment Fraud Detection by Component

        • Services
        • Software

      • CANADA Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • CANADA Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • CANADA Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

    • Europe Outlook (USD Billion, 2018-2032)

      • Europe Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • Europe Medical Payment Fraud Detection by Component

        • Services
        • Software

      • Europe Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • Europe Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • Europe Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • Germany Outlook (USD Billion, 2018-2032)

      • Germany Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • Germany Medical Payment Fraud Detection by Component

        • Services
        • Software

      • Germany Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • Germany Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • Germany Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • France Outlook (USD Billion, 2018-2032)

      • France Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • France Medical Payment Fraud Detection by Component

        • Services
        • Software

      • France Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • France Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • France Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • UK Outlook (USD Billion, 2018-2032)

      • UK Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • UK Medical Payment Fraud Detection by Component

        • Services
        • Software

      • UK Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • UK Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • UK Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • ITALY Outlook (USD Billion, 2018-2032)

      • ITALY Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • ITALY Medical Payment Fraud Detection by Component

        • Services
        • Software

      • ITALY Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • ITALY Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • ITALY Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • SPAIN Outlook (USD Billion, 2018-2032)

      • Spain Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • Spain Medical Payment Fraud Detection by Component

        • Services
        • Software

      • Spain Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • Spain Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • Spain Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • Rest Of Europe Outlook (USD Billion, 2018-2032)

      • Rest Of Europe Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • REST OF EUROPE Medical Payment Fraud Detection by Component

        • Services
        • Software

      • REST OF EUROPE Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • REST OF EUROPE Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • REST OF EUROPE Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

    • Asia-Pacific Outlook (USD Billion, 2018-2032)

      • Asia-Pacific Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • Asia-Pacific Medical Payment Fraud Detection by Component

        • Services
        • Software

      • Asia-Pacific Medical Payment Fraud Detection by Delivery Model

        • On-premise
        • Cloud-Based

      • Asia-Pacific Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • Asia-Pacific Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • China Outlook (USD Billion, 2018-2032)

      • China Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • China Medical Payment Fraud Detection by Component

        • Services
        • Software

      • China Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • China Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • China Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • Japan Outlook (USD Billion, 2018-2032)

      • Japan Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • Japan Medical Payment Fraud Detection by Component

        • Services
        • Software

      • Japan Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • Japan Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • Japan Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • India Outlook (USD Billion, 2018-2032)

      • India Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • India Medical Payment Fraud Detection by Component

        • Services
        • Software

      • India Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • India Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • India Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • Australia Outlook (USD Billion, 2018-2032)

      • Australia Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • Australia Medical Payment Fraud Detection by Component

        • Services
        • Software

      • Australia Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • Australia Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • Australia Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • Rest of Asia-Pacific Outlook (USD Billion, 2018-2032)

      • Rest of Asia-Pacific Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • Rest of Asia-Pacific Medical Payment Fraud Detection by Component

        • Services
        • Software

      • Rest of Asia-Pacific Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • Rest of Asia-Pacific Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • Rest of Asia-Pacific Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

    • Rest of the World Outlook (USD Billion, 2018-2032)

      • Rest of the World Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • Rest of the World Medical Payment Fraud Detection by Component

        • Services
        • Software

      • Rest of the World Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • Rest of the World Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • Rest of the World Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

    • Middle East Outlook (USD Billion, 2018-2032)

      • Middle East Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • Middle East Medical Payment Fraud Detection by Component

        • Services
        • Software

      • Middle East Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • Middle East Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • Middle East Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • Africa Outlook (USD Billion, 2018-2032)

      • Africa Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • Africa Medical Payment Fraud Detection by Component

        • Services
        • Software

      • Africa Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • Africa Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • Africa Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers

      • Latin America Outlook (USD Billion, 2018-2032)

      • Latin America Medical Payment Fraud Detection by Type

        • Descriptive Analytics
        • Predictive Analytics
        • Prescriptive Analytics

      • Latin America Medical Payment Fraud Detection by Component

        • Services
        • Software

      • Latin America Medical Payment Fraud Detection by Delivery Model

        • On-Premise
        • Cloud-Based

      • Latin America Medical Payment Fraud Detection by Source of Service

        • In-house
        • Outsourced

      • Latin America Medical Payment Fraud Detection by End-User

        • Private Insurance Payers
        • Public/Government Agencies
        • Third-Party Service Providers
    Medical Payment Fraud Detection Market Research Report - Forecast till 2034 Infographic
    Free Sample Request

    Kindly complete the form below to receive a free sample of this Report

    Related Reports

    No regional reports available for this market.

    Customer Strories

    “I am very pleased with how market segments have been defined in a relevant way for my purposes (such as "Portable Freezers & refrigerators" and "last-mile"). In general the report is well structured. Thanks very much for your efforts.”

    Victoria Milne Founder
    Case Study

    Chemicals and Materials

    Global Magnesium Sulfate Market – Forecast till 2027