Healthcare Fraud Detection Market By Type (Descriptive Analytics, Predictive Analytics, Prescriptive Analysis), By Component (Services, Software), By Application (Insurance Claims Review, Payment Integrity), By End User (Healthcare Payer, Government Agenc
Description
Healthcare Fraud Detection Market By Type (Descriptive Analytics, Predictive Analytics, Prescriptive Analysis), By Component (Services, Software), By Application (Insurance Claims Review, Payment Integrity), By End User (Healthcare Payer, Government Agencies, Others): Global Opportunity Analysis and Industry Forecast, 2021-2031
The global healthcare fraud detection Market was valued at $1,098.2 million in 2021, and is projected to reach $3,600.0 million by 2031, registering a CAGR of 12.6% from 2022 to 2031.
The goal of fraud detection is to stop someone from obtaining money or other items through deceptive means. Various industries, including medical and healthcare, use fraud detection techniques. healthcare fraud detection involves account audits and detective work. A thorough account audit might discover suspect policy holders and suppliers. It is ideal to carefully audit each and every claim one at a time. However, there are no realistic way to audit all claims. Fraud detection management is done by the techniques such as to look through millions of transactions, classify, organize, and segment data in order to locate patterns and identify fraud, data mining, estimation of the connections between independent and dependent variables. Data matching is a technique used to compare two collections of data, remove out duplicates, and establish connections between data.
Healthcare fraud, waste, and abuse are actually prevented by the healthcare fraud detection industry. Healthcare fraud is the deliberate distortion of facts by patients or healthcare personnel that results in unlawful payments or benefits. Examples of healthcare fraud include the filing of numerous claims by different providers for the same patients, the falsification of data by doctors, the submission of claims for services that have not been rendered, and the misrepresentation of dates for various treatments, frequency, duration, or service descriptions. The various activities involving fraud in medical industries has increased. Furthermore, the increased fraud cases, abuse of medical products and equipment and misuse of healthcare funds is projected to drive the market growth.
The major factor that drives the market growth of healthcare fraud detection in healthcare market is increase in number of patients seeking health insurance. The other factors such as increase in fraudulent cases, and misuse of funds offered by healthcare boost the growth of the healthcare fraud detection market. A small number of auditors must manually evaluate and pinpoint the dubious medical insurance claims to manually discover healthcare fraud.
However, more effective and automated methods of detecting healthcare frauds have been developed because to recent breakthroughs in machine learning and data mining techniques. In recent years, there has been an increase in interest in mining healthcare data for fraud detection also boosting the global healthcare fraud detection market. The breakthrough advances in machine learning and artificial intelligence, increased in data security concern in healthcare industry restraining the global healthcare fraud detection market.
The healthcare fraud detection market segmented on the basis of type, component, application, end user and region. By type, the market is segmented into descriptive analytics, predictive analytics and prescriptive analysis. By component the market is fragmented into service and software. By application the market divided into insurance claims review and payment integrity.
By end user, the market is segmented into healthcare payer, government agencies and others. The healthcare payer further segmented into public payer and private payer. The others segment includes employers, healthcare providers and third-party service providers. Region wise, the market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
Major key players that operate in the global healthcare fraud detection market are International Business Machines Corporation (IBM), Optum, Verscend Technologies, McKesson Corporation, FAIR ISAAC Corporation, SAS Institute Inc., HCL Technologies, Wipro Limited, Conduent, CGI Group, DXC Technology Company, UnitedHealth Group, Exlservice Holdings Inc., Scio inspire Corp, LexisNexis, OSP Labs, Northrop Grumman.
Key Benefits For Stakeholders
This report provides a quantitative analysis of the market segments, current trends, estimations, and dynamics of the healthcare fraud detectionmarket analysis from 2021 to 2031 to identify the prevailing healthcare fraud detection market opportunities.
The market research is offered along with information related to key drivers, restraints, and opportunities.
Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders make profit-oriented business decisions and strengthen their supplier-buyer network.
In-depth analysis of the healthcare fraud detection market segmentation assists to determine the prevailing market opportunities.
Major countries in each region are mapped according to their revenue contribution to the global market.
Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players.
The report includes the analysis of the regional as well as global healthcare fraud detection market trends, key players, market segments, application areas, and market growth strategies.
Key Market Segments
By Application
Insurance Claims Review
Payment Integrity
By End User
Healthcare Payer
Type
Public Payers
Private players
Government Agencies
Others
By Type
Descriptive Analytics
Predictive Analytics
Prescriptive Analysis
By Component
Services
Software
By Region
North America
U.S.
Canada
Mexico
Europe
Germany
France
UK
Italy
Spain
Rest of Europe
Asia-Pacific
China
Australia
India
South Korea
Rest of Asia-Pacific
Japan
LAMEA
Brazil
Saudi Arabia
South Africa
Rest of LAMEA
Key Market Players
International Business Machines Corporation (IBM)
Optum Inc.
Verscend Technologies
McKesson Corporation
FAIR ISAAC Corporation
SAS Institute Inc.
HCL Technologies
WIPRO LIMITED
Conduent
CGI Group
DXC Technology Company
UnitedHealth Group, Inc.
Exlservice Holdings Inc.
Cotiviti Inc.
LexisNexis
OSP Labs
Northrop Grumman
Northrop Grumman Corp
Please Note: It will take 7-10 business days to complete the report upon order confirmation.
The global healthcare fraud detection Market was valued at $1,098.2 million in 2021, and is projected to reach $3,600.0 million by 2031, registering a CAGR of 12.6% from 2022 to 2031.
The goal of fraud detection is to stop someone from obtaining money or other items through deceptive means. Various industries, including medical and healthcare, use fraud detection techniques. healthcare fraud detection involves account audits and detective work. A thorough account audit might discover suspect policy holders and suppliers. It is ideal to carefully audit each and every claim one at a time. However, there are no realistic way to audit all claims. Fraud detection management is done by the techniques such as to look through millions of transactions, classify, organize, and segment data in order to locate patterns and identify fraud, data mining, estimation of the connections between independent and dependent variables. Data matching is a technique used to compare two collections of data, remove out duplicates, and establish connections between data.
Healthcare fraud, waste, and abuse are actually prevented by the healthcare fraud detection industry. Healthcare fraud is the deliberate distortion of facts by patients or healthcare personnel that results in unlawful payments or benefits. Examples of healthcare fraud include the filing of numerous claims by different providers for the same patients, the falsification of data by doctors, the submission of claims for services that have not been rendered, and the misrepresentation of dates for various treatments, frequency, duration, or service descriptions. The various activities involving fraud in medical industries has increased. Furthermore, the increased fraud cases, abuse of medical products and equipment and misuse of healthcare funds is projected to drive the market growth.
The major factor that drives the market growth of healthcare fraud detection in healthcare market is increase in number of patients seeking health insurance. The other factors such as increase in fraudulent cases, and misuse of funds offered by healthcare boost the growth of the healthcare fraud detection market. A small number of auditors must manually evaluate and pinpoint the dubious medical insurance claims to manually discover healthcare fraud.
However, more effective and automated methods of detecting healthcare frauds have been developed because to recent breakthroughs in machine learning and data mining techniques. In recent years, there has been an increase in interest in mining healthcare data for fraud detection also boosting the global healthcare fraud detection market. The breakthrough advances in machine learning and artificial intelligence, increased in data security concern in healthcare industry restraining the global healthcare fraud detection market.
The healthcare fraud detection market segmented on the basis of type, component, application, end user and region. By type, the market is segmented into descriptive analytics, predictive analytics and prescriptive analysis. By component the market is fragmented into service and software. By application the market divided into insurance claims review and payment integrity.
By end user, the market is segmented into healthcare payer, government agencies and others. The healthcare payer further segmented into public payer and private payer. The others segment includes employers, healthcare providers and third-party service providers. Region wise, the market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
Major key players that operate in the global healthcare fraud detection market are International Business Machines Corporation (IBM), Optum, Verscend Technologies, McKesson Corporation, FAIR ISAAC Corporation, SAS Institute Inc., HCL Technologies, Wipro Limited, Conduent, CGI Group, DXC Technology Company, UnitedHealth Group, Exlservice Holdings Inc., Scio inspire Corp, LexisNexis, OSP Labs, Northrop Grumman.
Key Benefits For Stakeholders
This report provides a quantitative analysis of the market segments, current trends, estimations, and dynamics of the healthcare fraud detectionmarket analysis from 2021 to 2031 to identify the prevailing healthcare fraud detection market opportunities.
The market research is offered along with information related to key drivers, restraints, and opportunities.
Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders make profit-oriented business decisions and strengthen their supplier-buyer network.
In-depth analysis of the healthcare fraud detection market segmentation assists to determine the prevailing market opportunities.
Major countries in each region are mapped according to their revenue contribution to the global market.
Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players.
The report includes the analysis of the regional as well as global healthcare fraud detection market trends, key players, market segments, application areas, and market growth strategies.
Key Market Segments
By Application
Insurance Claims Review
Payment Integrity
By End User
Healthcare Payer
Type
Public Payers
Private players
Government Agencies
Others
By Type
Descriptive Analytics
Predictive Analytics
Prescriptive Analysis
By Component
Services
Software
By Region
North America
U.S.
Canada
Mexico
Europe
Germany
France
UK
Italy
Spain
Rest of Europe
Asia-Pacific
China
Australia
India
South Korea
Rest of Asia-Pacific
Japan
LAMEA
Brazil
Saudi Arabia
South Africa
Rest of LAMEA
Key Market Players
International Business Machines Corporation (IBM)
Optum Inc.
Verscend Technologies
McKesson Corporation
FAIR ISAAC Corporation
SAS Institute Inc.
HCL Technologies
WIPRO LIMITED
Conduent
CGI Group
DXC Technology Company
UnitedHealth Group, Inc.
Exlservice Holdings Inc.
Cotiviti Inc.
LexisNexis
OSP Labs
Northrop Grumman
Northrop Grumman Corp
Please Note: It will take 7-10 business days to complete the report upon order confirmation.
Table of Contents
310 Pages
- CHAPTER 1:INTRODUCTION
- 1.1.Report description
- 1.2.Key market segments
- 1.3.Key benefits to the stakeholders
- 1.4.Research Methodology
- 1.4.1.Secondary research
- 1.4.2.Primary research
- 1.4.3.Analyst tools and models
- CHAPTER 2:EXECUTIVE SUMMARY
- 2.1.Key findings of the study
- 2.2.CXO Perspective
- CHAPTER 3:MARKET OVERVIEW
- 3.1.Market definition and scope
- 3.2.Key findings
- 3.2.1.Top investment pockets
- 3.3.Porter’s five forces analysis
- 3.4.Top player positioning
- 3.5.Market dynamics
- 3.5.1.Drivers
- 3.5.2.Restraints
- 3.5.3.Opportunities
- 3.6.COVID-19 Impact Analysis on the market
- CHAPTER 4: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE
- 4.1 Overview
- 4.1.1 Market size and forecast
- 4.2 Descriptive Analytics
- 4.2.1 Key market trends, growth factors and opportunities
- 4.2.2 Market size and forecast, by region
- 4.2.3 Market analysis by country
- 4.3 Predictive Analytics
- 4.3.1 Key market trends, growth factors and opportunities
- 4.3.2 Market size and forecast, by region
- 4.3.3 Market analysis by country
- 4.4 Prescriptive Analysis
- 4.4.1 Key market trends, growth factors and opportunities
- 4.4.2 Market size and forecast, by region
- 4.4.3 Market analysis by country
- CHAPTER 5: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT
- 5.1 Overview
- 5.1.1 Market size and forecast
- 5.2 Services
- 5.2.1 Key market trends, growth factors and opportunities
- 5.2.2 Market size and forecast, by region
- 5.2.3 Market analysis by country
- 5.3 Software
- 5.3.1 Key market trends, growth factors and opportunities
- 5.3.2 Market size and forecast, by region
- 5.3.3 Market analysis by country
- CHAPTER 6: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION
- 6.1 Overview
- 6.1.1 Market size and forecast
- 6.2 Insurance Claims Review
- 6.2.1 Key market trends, growth factors and opportunities
- 6.2.2 Market size and forecast, by region
- 6.2.3 Market analysis by country
- 6.3 Payment Integrity
- 6.3.1 Key market trends, growth factors and opportunities
- 6.3.2 Market size and forecast, by region
- 6.3.3 Market analysis by country
- CHAPTER 7: HEALTHCARE FRAUD DETECTION MARKET, BY END USER
- 7.1 Overview
- 7.1.1 Market size and forecast
- 7.2 Healthcare Payer
- 7.2.1 Key market trends, growth factors and opportunities
- 7.2.2 Market size and forecast, by region
- 7.2.3 Market analysis by country
- 7.2.4 Healthcare Payer Healthcare Fraud Detection Market by Type
- 7.2.4.1 Public Payers Market size and forecast, by region
- 7.2.4.2 Private players Market size and forecast, by region
- 7.3 Government Agencies
- 7.3.1 Key market trends, growth factors and opportunities
- 7.3.2 Market size and forecast, by region
- 7.3.3 Market analysis by country
- 7.4 Others
- 7.4.1 Key market trends, growth factors and opportunities
- 7.4.2 Market size and forecast, by region
- 7.4.3 Market analysis by country
- CHAPTER 8: HEALTHCARE FRAUD DETECTION MARKET, BY REGION
- 8.1 Overview
- 8.1.1 Market size and forecast
- 8.2 North America
- 8.2.1 Key trends and opportunities
- 8.2.2 North America Market size and forecast, by Type
- 8.2.3 North America Market size and forecast, by Component
- 8.2.4 North America Market size and forecast, by Application
- 8.2.5 North America Market size and forecast, by End User
- 8.2.5.1 North America Healthcare Payer Healthcare Fraud Detection Market by Type
- 8.2.6 North America Market size and forecast, by country
- 8.2.6.1 U.S.
- 8.2.6.1.1 Market size and forecast, by Type
- 8.2.6.1.2 Market size and forecast, by Component
- 8.2.6.1.3 Market size and forecast, by Application
- 8.2.6.1.4 Market size and forecast, by End User
- 8.2.6.2 Canada
- 8.2.6.2.1 Market size and forecast, by Type
- 8.2.6.2.2 Market size and forecast, by Component
- 8.2.6.2.3 Market size and forecast, by Application
- 8.2.6.2.4 Market size and forecast, by End User
- 8.2.6.3 Mexico
- 8.2.6.3.1 Market size and forecast, by Type
- 8.2.6.3.2 Market size and forecast, by Component
- 8.2.6.3.3 Market size and forecast, by Application
- 8.2.6.3.4 Market size and forecast, by End User
- 8.3 Europe
- 8.3.1 Key trends and opportunities
- 8.3.2 Europe Market size and forecast, by Type
- 8.3.3 Europe Market size and forecast, by Component
- 8.3.4 Europe Market size and forecast, by Application
- 8.3.5 Europe Market size and forecast, by End User
- 8.3.5.1 Europe Healthcare Payer Healthcare Fraud Detection Market by Type
- 8.3.6 Europe Market size and forecast, by country
- 8.3.6.1 Germany
- 8.3.6.1.1 Market size and forecast, by Type
- 8.3.6.1.2 Market size and forecast, by Component
- 8.3.6.1.3 Market size and forecast, by Application
- 8.3.6.1.4 Market size and forecast, by End User
- 8.3.6.2 France
- 8.3.6.2.1 Market size and forecast, by Type
- 8.3.6.2.2 Market size and forecast, by Component
- 8.3.6.2.3 Market size and forecast, by Application
- 8.3.6.2.4 Market size and forecast, by End User
- 8.3.6.3 UK
- 8.3.6.3.1 Market size and forecast, by Type
- 8.3.6.3.2 Market size and forecast, by Component
- 8.3.6.3.3 Market size and forecast, by Application
- 8.3.6.3.4 Market size and forecast, by End User
- 8.3.6.4 Italy
- 8.3.6.4.1 Market size and forecast, by Type
- 8.3.6.4.2 Market size and forecast, by Component
- 8.3.6.4.3 Market size and forecast, by Application
- 8.3.6.4.4 Market size and forecast, by End User
- 8.3.6.5 Spain
- 8.3.6.5.1 Market size and forecast, by Type
- 8.3.6.5.2 Market size and forecast, by Component
- 8.3.6.5.3 Market size and forecast, by Application
- 8.3.6.5.4 Market size and forecast, by End User
- 8.3.6.6 Rest of Europe
- 8.3.6.6.1 Market size and forecast, by Type
- 8.3.6.6.2 Market size and forecast, by Component
- 8.3.6.6.3 Market size and forecast, by Application
- 8.3.6.6.4 Market size and forecast, by End User
- 8.4 Asia-Pacific
- 8.4.1 Key trends and opportunities
- 8.4.2 Asia-Pacific Market size and forecast, by Type
- 8.4.3 Asia-Pacific Market size and forecast, by Component
- 8.4.4 Asia-Pacific Market size and forecast, by Application
- 8.4.5 Asia-Pacific Market size and forecast, by End User
- 8.4.5.1 Asia-Pacific Healthcare Payer Healthcare Fraud Detection Market by Type
- 8.4.6 Asia-Pacific Market size and forecast, by country
- 8.4.6.1 Japan
- 8.4.6.1.1 Market size and forecast, by Type
- 8.4.6.1.2 Market size and forecast, by Component
- 8.4.6.1.3 Market size and forecast, by Application
- 8.4.6.1.4 Market size and forecast, by End User
- 8.4.6.2 China
- 8.4.6.2.1 Market size and forecast, by Type
- 8.4.6.2.2 Market size and forecast, by Component
- 8.4.6.2.3 Market size and forecast, by Application
- 8.4.6.2.4 Market size and forecast, by End User
- 8.4.6.3 Australia
- 8.4.6.3.1 Market size and forecast, by Type
- 8.4.6.3.2 Market size and forecast, by Component
- 8.4.6.3.3 Market size and forecast, by Application
- 8.4.6.3.4 Market size and forecast, by End User
- 8.4.6.4 India
- 8.4.6.4.1 Market size and forecast, by Type
- 8.4.6.4.2 Market size and forecast, by Component
- 8.4.6.4.3 Market size and forecast, by Application
- 8.4.6.4.4 Market size and forecast, by End User
- 8.4.6.5 South Korea
- 8.4.6.5.1 Market size and forecast, by Type
- 8.4.6.5.2 Market size and forecast, by Component
- 8.4.6.5.3 Market size and forecast, by Application
- 8.4.6.5.4 Market size and forecast, by End User
- 8.4.6.6 Rest of Asia-Pacific
- 8.4.6.6.1 Market size and forecast, by Type
- 8.4.6.6.2 Market size and forecast, by Component
- 8.4.6.6.3 Market size and forecast, by Application
- 8.4.6.6.4 Market size and forecast, by End User
- 8.5 LAMEA
- 8.5.1 Key trends and opportunities
- 8.5.2 LAMEA Market size and forecast, by Type
- 8.5.3 LAMEA Market size and forecast, by Component
- 8.5.4 LAMEA Market size and forecast, by Application
- 8.5.5 LAMEA Market size and forecast, by End User
- 8.5.5.1 LAMEA Healthcare Payer Healthcare Fraud Detection Market by Type
- 8.5.6 LAMEA Market size and forecast, by country
- 8.5.6.1 Brazil
- 8.5.6.1.1 Market size and forecast, by Type
- 8.5.6.1.2 Market size and forecast, by Component
- 8.5.6.1.3 Market size and forecast, by Application
- 8.5.6.1.4 Market size and forecast, by End User
- 8.5.6.2 Saudi Arabia
- 8.5.6.2.1 Market size and forecast, by Type
- 8.5.6.2.2 Market size and forecast, by Component
- 8.5.6.2.3 Market size and forecast, by Application
- 8.5.6.2.4 Market size and forecast, by End User
- 8.5.6.3 South Africa
- 8.5.6.3.1 Market size and forecast, by Type
- 8.5.6.3.2 Market size and forecast, by Component
- 8.5.6.3.3 Market size and forecast, by Application
- 8.5.6.3.4 Market size and forecast, by End User
- 8.5.6.4 Rest of LAMEA
- 8.5.6.4.1 Market size and forecast, by Type
- 8.5.6.4.2 Market size and forecast, by Component
- 8.5.6.4.3 Market size and forecast, by Application
- 8.5.6.4.4 Market size and forecast, by End User
- CHAPTER 9: COMPANY LANDSCAPE
- 9.1. Introduction
- 9.2. Top winning strategies
- 9.3. Product Mapping of Top 10 Player
- 9.4. Competitive Dashboard
- 9.5. Competitive Heatmap
- 9.6. Key developments
- CHAPTER 10: COMPANY PROFILES
- 10.1 International Business Machines Corporation (IBM)
- 10.1.1 Company overview
- 10.1.2 Company snapshot
- 10.1.3 Operating business segments
- 10.1.4 Product portfolio
- 10.1.5 Business performance
- 10.1.6 Key strategic moves and developments
- 10.2 Optum Inc.
- 10.2.1 Company overview
- 10.2.2 Company snapshot
- 10.2.3 Operating business segments
- 10.2.4 Product portfolio
- 10.2.5 Business performance
- 10.2.6 Key strategic moves and developments
- 10.3 Verscend Technologies
- 10.3.1 Company overview
- 10.3.2 Company snapshot
- 10.3.3 Operating business segments
- 10.3.4 Product portfolio
- 10.3.5 Business performance
- 10.3.6 Key strategic moves and developments
- 10.4 McKesson Corporation
- 10.4.1 Company overview
- 10.4.2 Company snapshot
- 10.4.3 Operating business segments
- 10.4.4 Product portfolio
- 10.4.5 Business performance
- 10.4.6 Key strategic moves and developments
- 10.5 FAIR ISAAC Corporation
- 10.5.1 Company overview
- 10.5.2 Company snapshot
- 10.5.3 Operating business segments
- 10.5.4 Product portfolio
- 10.5.5 Business performance
- 10.5.6 Key strategic moves and developments
- 10.6 SAS Institute Inc.
- 10.6.1 Company overview
- 10.6.2 Company snapshot
- 10.6.3 Operating business segments
- 10.6.4 Product portfolio
- 10.6.5 Business performance
- 10.6.6 Key strategic moves and developments
- 10.7 HCL Technologies
- 10.7.1 Company overview
- 10.7.2 Company snapshot
- 10.7.3 Operating business segments
- 10.7.4 Product portfolio
- 10.7.5 Business performance
- 10.7.6 Key strategic moves and developments
- 10.8 WIPRO LIMITED
- 10.8.1 Company overview
- 10.8.2 Company snapshot
- 10.8.3 Operating business segments
- 10.8.4 Product portfolio
- 10.8.5 Business performance
- 10.8.6 Key strategic moves and developments
- 10.9 Conduent
- 10.9.1 Company overview
- 10.9.2 Company snapshot
- 10.9.3 Operating business segments
- 10.9.4 Product portfolio
- 10.9.5 Business performance
- 10.9.6 Key strategic moves and developments
- 10.10 CGI Group
- 10.10.1 Company overview
- 10.10.2 Company snapshot
- 10.10.3 Operating business segments
- 10.10.4 Product portfolio
- 10.10.5 Business performance
- 10.10.6 Key strategic moves and developments
- 10.11 DXC Technology Company
- 10.11.1 Company overview
- 10.11.2 Company snapshot
- 10.11.3 Operating business segments
- 10.11.4 Product portfolio
- 10.11.5 Business performance
- 10.11.6 Key strategic moves and developments
- 10.12 UnitedHealth Group, Inc.
- 10.12.1 Company overview
- 10.12.2 Company snapshot
- 10.12.3 Operating business segments
- 10.12.4 Product portfolio
- 10.12.5 Business performance
- 10.12.6 Key strategic moves and developments
- 10.13 Exlservice Holdings Inc.
- 10.13.1 Company overview
- 10.13.2 Company snapshot
- 10.13.3 Operating business segments
- 10.13.4 Product portfolio
- 10.13.5 Business performance
- 10.13.6 Key strategic moves and developments
- 10.14 Cotiviti Inc.
- 10.14.1 Company overview
- 10.14.2 Company snapshot
- 10.14.3 Operating business segments
- 10.14.4 Product portfolio
- 10.14.5 Business performance
- 10.14.6 Key strategic moves and developments
- 10.15 LexisNexis
- 10.15.1 Company overview
- 10.15.2 Company snapshot
- 10.15.3 Operating business segments
- 10.15.4 Product portfolio
- 10.15.5 Business performance
- 10.15.6 Key strategic moves and developments
- 10.16 OSP Labs
- 10.16.1 Company overview
- 10.16.2 Company snapshot
- 10.16.3 Operating business segments
- 10.16.4 Product portfolio
- 10.16.5 Business performance
- 10.16.6 Key strategic moves and developments
- 10.17 Northrop Grumman
- 10.17.1 Company overview
- 10.17.2 Company snapshot
- 10.17.3 Operating business segments
- 10.17.4 Product portfolio
- 10.17.5 Business performance
- 10.17.6 Key strategic moves and developments
- 10.18 Northrop Grumman Corp
- 10.18.1 Company overview
- 10.18.2 Company snapshot
- 10.18.3 Operating business segments
- 10.18.4 Product portfolio
- 10.18.5 Business performance
- 10.18.6 Key strategic moves and developments
- LIST OF TABLES
- TABLE 1. GLOBAL HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 2. HEALTHCARE FRAUD DETECTION MARKET SIZE, FOR DESCRIPTIVE ANALYTICS, BY REGION, 2021-2031 ($MILLION)
- TABLE 3. HEALTHCARE FRAUD DETECTION MARKET FOR DESCRIPTIVE ANALYTICS, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 4. HEALTHCARE FRAUD DETECTION MARKET SIZE, FOR PREDICTIVE ANALYTICS, BY REGION, 2021-2031 ($MILLION)
- TABLE 5. HEALTHCARE FRAUD DETECTION MARKET FOR PREDICTIVE ANALYTICS, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 6. HEALTHCARE FRAUD DETECTION MARKET SIZE, FOR PRESCRIPTIVE ANALYSIS, BY REGION, 2021-2031 ($MILLION)
- TABLE 7. HEALTHCARE FRAUD DETECTION MARKET FOR PRESCRIPTIVE ANALYSIS, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 8. GLOBAL HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 9. HEALTHCARE FRAUD DETECTION MARKET SIZE, FOR SERVICES, BY REGION, 2021-2031 ($MILLION)
- TABLE 10. HEALTHCARE FRAUD DETECTION MARKET FOR SERVICES, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 11. HEALTHCARE FRAUD DETECTION MARKET SIZE, FOR SOFTWARE, BY REGION, 2021-2031 ($MILLION)
- TABLE 12. HEALTHCARE FRAUD DETECTION MARKET FOR SOFTWARE, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 13. GLOBAL HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 14. HEALTHCARE FRAUD DETECTION MARKET SIZE, FOR INSURANCE CLAIMS REVIEW, BY REGION, 2021-2031 ($MILLION)
- TABLE 15. HEALTHCARE FRAUD DETECTION MARKET FOR INSURANCE CLAIMS REVIEW, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 16. HEALTHCARE FRAUD DETECTION MARKET SIZE, FOR PAYMENT INTEGRITY, BY REGION, 2021-2031 ($MILLION)
- TABLE 17. HEALTHCARE FRAUD DETECTION MARKET FOR PAYMENT INTEGRITY, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 18. GLOBAL HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 19. HEALTHCARE FRAUD DETECTION MARKET SIZE, FOR HEALTHCARE PAYER, BY REGION, 2021-2031 ($MILLION)
- TABLE 20. HEALTHCARE FRAUD DETECTION MARKET FOR HEALTHCARE PAYER, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 21. GLOBAL HEALTHCARE PAYER HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 22. HEALTHCARE FRAUD DETECTION MARKET, FOR PUBLIC PAYERS, BY REGION, 2021-2031 ($MILLION)
- TABLE 23. HEALTHCARE FRAUD DETECTION MARKET, FOR PRIVATE PLAYERS, BY REGION, 2021-2031 ($MILLION)
- TABLE 24. HEALTHCARE FRAUD DETECTION MARKET SIZE, FOR GOVERNMENT AGENCIES, BY REGION, 2021-2031 ($MILLION)
- TABLE 25. HEALTHCARE FRAUD DETECTION MARKET FOR GOVERNMENT AGENCIES, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 26. HEALTHCARE FRAUD DETECTION MARKET SIZE, FOR OTHERS, BY REGION, 2021-2031 ($MILLION)
- TABLE 27. HEALTHCARE FRAUD DETECTION MARKET FOR OTHERS, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 28. HEALTHCARE FRAUD DETECTION MARKET, BY REGION, 2021-2031 ($MILLION)
- TABLE 29. NORTH AMERICA HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 30. NORTH AMERICA HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 31. NORTH AMERICA HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 32. NORTH AMERICA HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 33. NORTH AMERICA HEALTHCARE PAYER HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 34. NORTH AMERICA HEALTHCARE FRAUD DETECTION MARKET, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 35. U.S. HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 36. U.S. HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 37. U.S. HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 38. U.S. HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 39. CANADA HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 40. CANADA HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 41. CANADA HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 42. CANADA HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 43. MEXICO HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 44. MEXICO HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 45. MEXICO HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 46. MEXICO HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 47. EUROPE HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 48. EUROPE HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 49. EUROPE HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 50. EUROPE HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 51. EUROPE HEALTHCARE PAYER HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 52. EUROPE HEALTHCARE FRAUD DETECTION MARKET, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 53. GERMANY HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 54. GERMANY HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 55. GERMANY HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 56. GERMANY HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 57. FRANCE HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 58. FRANCE HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 59. FRANCE HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 60. FRANCE HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 61. UK HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 62. UK HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 63. UK HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 64. UK HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 65. ITALY HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 66. ITALY HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 67. ITALY HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 68. ITALY HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 69. SPAIN HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 70. SPAIN HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 71. SPAIN HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 72. SPAIN HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 73. REST OF EUROPE HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 74. REST OF EUROPE HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 75. REST OF EUROPE HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 76. REST OF EUROPE HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 77. ASIA-PACIFIC HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 78. ASIA-PACIFIC HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 79. ASIA-PACIFIC HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 80. ASIA-PACIFIC HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 81. ASIA-PACIFIC HEALTHCARE PAYER HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 82. ASIA-PACIFIC HEALTHCARE FRAUD DETECTION MARKET, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 83. JAPAN HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 84. JAPAN HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 85. JAPAN HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 86. JAPAN HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 87. CHINA HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 88. CHINA HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 89. CHINA HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 90. CHINA HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 91. AUSTRALIA HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 92. AUSTRALIA HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 93. AUSTRALIA HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 94. AUSTRALIA HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 95. INDIA HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 96. INDIA HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 97. INDIA HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 98. INDIA HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 99. SOUTH KOREA HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 100. SOUTH KOREA HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 101. SOUTH KOREA HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 102. SOUTH KOREA HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 103. REST OF ASIA-PACIFIC HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 104. REST OF ASIA-PACIFIC HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 105. REST OF ASIA-PACIFIC HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 106. REST OF ASIA-PACIFIC HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 107. LAMEA HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 108. LAMEA HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 109. LAMEA HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 110. LAMEA HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 111. LAMEA HEALTHCARE PAYER HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 112. LAMEA HEALTHCARE FRAUD DETECTION MARKET, BY COUNTRY, 2021-2031 ($MILLION)
- TABLE 113. BRAZIL HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 114. BRAZIL HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 115. BRAZIL HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 116. BRAZIL HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 117. SAUDI ARABIA HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 118. SAUDI ARABIA HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 119. SAUDI ARABIA HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 120. SAUDI ARABIA HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 121. SOUTH AFRICA HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 122. SOUTH AFRICA HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 123. SOUTH AFRICA HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 124. SOUTH AFRICA HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 125. REST OF LAMEA HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2021-2031 ($MILLION)
- TABLE 126. REST OF LAMEA HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2021-2031 ($MILLION)
- TABLE 127. REST OF LAMEA HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2021-2031 ($MILLION)
- TABLE 128. REST OF LAMEA HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2021-2031 ($MILLION)
- TABLE 129.INTERNATIONAL BUSINESS MACHINES CORPORATION (IBM): COMPANY SNAPSHOT
- TABLE 130.INTERNATIONAL BUSINESS MACHINES CORPORATION (IBM): OPERATING SEGMENTS
- TABLE 131.INTERNATIONAL BUSINESS MACHINES CORPORATION (IBM): PRODUCT PORTFOLIO
- TABLE 132.INTERNATIONAL BUSINESS MACHINES CORPORATION (IBM): NET SALES,
- TABLE 133.INTERNATIONAL BUSINESS MACHINES CORPORATION (IBM): KEY STRATERGIES
- TABLE 134.OPTUM INC.: COMPANY SNAPSHOT
- TABLE 135.OPTUM INC.: OPERATING SEGMENTS
- TABLE 136.OPTUM INC.: PRODUCT PORTFOLIO
- TABLE 137.OPTUM INC.: NET SALES,
- TABLE 138.OPTUM INC.: KEY STRATERGIES
- TABLE 139.VERSCEND TECHNOLOGIES: COMPANY SNAPSHOT
- TABLE 140.VERSCEND TECHNOLOGIES: OPERATING SEGMENTS
- TABLE 141.VERSCEND TECHNOLOGIES: PRODUCT PORTFOLIO
- TABLE 142.VERSCEND TECHNOLOGIES: NET SALES,
- TABLE 143.VERSCEND TECHNOLOGIES: KEY STRATERGIES
- TABLE 144.MCKESSON CORPORATION: COMPANY SNAPSHOT
- TABLE 145.MCKESSON CORPORATION: OPERATING SEGMENTS
- TABLE 146.MCKESSON CORPORATION: PRODUCT PORTFOLIO
- TABLE 147.MCKESSON CORPORATION: NET SALES,
- TABLE 148.MCKESSON CORPORATION: KEY STRATERGIES
- TABLE 149.FAIR ISAAC CORPORATION: COMPANY SNAPSHOT
- TABLE 150.FAIR ISAAC CORPORATION: OPERATING SEGMENTS
- TABLE 151.FAIR ISAAC CORPORATION: PRODUCT PORTFOLIO
- TABLE 152.FAIR ISAAC CORPORATION: NET SALES,
- TABLE 153.FAIR ISAAC CORPORATION: KEY STRATERGIES
- TABLE 154.SAS INSTITUTE INC.: COMPANY SNAPSHOT
- TABLE 155.SAS INSTITUTE INC.: OPERATING SEGMENTS
- TABLE 156.SAS INSTITUTE INC.: PRODUCT PORTFOLIO
- TABLE 157.SAS INSTITUTE INC.: NET SALES,
- TABLE 158.SAS INSTITUTE INC.: KEY STRATERGIES
- TABLE 159.HCL TECHNOLOGIES: COMPANY SNAPSHOT
- TABLE 160.HCL TECHNOLOGIES: OPERATING SEGMENTS
- TABLE 161.HCL TECHNOLOGIES: PRODUCT PORTFOLIO
- TABLE 162.HCL TECHNOLOGIES: NET SALES,
- TABLE 163.HCL TECHNOLOGIES: KEY STRATERGIES
- TABLE 164.WIPRO LIMITED: COMPANY SNAPSHOT
- TABLE 165.WIPRO LIMITED: OPERATING SEGMENTS
- TABLE 166.WIPRO LIMITED: PRODUCT PORTFOLIO
- TABLE 167.WIPRO LIMITED: NET SALES,
- TABLE 168.WIPRO LIMITED: KEY STRATERGIES
- TABLE 169.CONDUENT: COMPANY SNAPSHOT
- TABLE 170.CONDUENT: OPERATING SEGMENTS
- TABLE 171.CONDUENT: PRODUCT PORTFOLIO
- TABLE 172.CONDUENT: NET SALES,
- TABLE 173.CONDUENT: KEY STRATERGIES
- TABLE 174.CGI GROUP: COMPANY SNAPSHOT
- TABLE 175.CGI GROUP: OPERATING SEGMENTS
- TABLE 176.CGI GROUP: PRODUCT PORTFOLIO
- TABLE 177.CGI GROUP: NET SALES,
- TABLE 178.CGI GROUP: KEY STRATERGIES
- TABLE 179.DXC TECHNOLOGY COMPANY: COMPANY SNAPSHOT
- TABLE 180.DXC TECHNOLOGY COMPANY: OPERATING SEGMENTS
- TABLE 181.DXC TECHNOLOGY COMPANY: PRODUCT PORTFOLIO
- TABLE 182.DXC TECHNOLOGY COMPANY: NET SALES,
- TABLE 183.DXC TECHNOLOGY COMPANY: KEY STRATERGIES
- TABLE 184.UNITEDHEALTH GROUP, INC.: COMPANY SNAPSHOT
- TABLE 185.UNITEDHEALTH GROUP, INC.: OPERATING SEGMENTS
- TABLE 186.UNITEDHEALTH GROUP, INC.: PRODUCT PORTFOLIO
- TABLE 187.UNITEDHEALTH GROUP, INC.: NET SALES,
- TABLE 188.UNITEDHEALTH GROUP, INC.: KEY STRATERGIES
- TABLE 189.EXLSERVICE HOLDINGS INC.: COMPANY SNAPSHOT
- TABLE 190.EXLSERVICE HOLDINGS INC.: OPERATING SEGMENTS
- TABLE 191.EXLSERVICE HOLDINGS INC.: PRODUCT PORTFOLIO
- TABLE 192.EXLSERVICE HOLDINGS INC.: NET SALES,
- TABLE 193.EXLSERVICE HOLDINGS INC.: KEY STRATERGIES
- TABLE 194.COTIVITI INC.: COMPANY SNAPSHOT
- TABLE 195.COTIVITI INC.: OPERATING SEGMENTS
- TABLE 196.COTIVITI INC.: PRODUCT PORTFOLIO
- TABLE 197.COTIVITI INC.: NET SALES,
- TABLE 198.COTIVITI INC.: KEY STRATERGIES
- TABLE 199.LEXISNEXIS: COMPANY SNAPSHOT
- LIST OF FIGURES
- FIGURE 1.HEALTHCARE FRAUD DETECTION MARKET SEGMENTATION
- FIGURE 2.HEALTHCARE FRAUD DETECTION MARKET,2021-2031
- FIGURE 3.HEALTHCARE FRAUD DETECTION MARKET,2021-2031
- FIGURE 4. TOP INVESTMENT POCKETS, BY REGION
- FIGURE 5.PORTER FIVE-1
- FIGURE 6.PORTER FIVE-2
- FIGURE 7.PORTER FIVE-3
- FIGURE 8.PORTER FIVE-4
- FIGURE 9.PORTER FIVE-5
- FIGURE 10.TOP PLAYER POSITIONING
- FIGURE 11.HEALTHCARE FRAUD DETECTION MARKET:DRIVERS, RESTRAINTS AND OPPORTUNITIES
- FIGURE 12.HEALTHCARE FRAUD DETECTION MARKET,BY TYPE,2021(%)
- FIGURE 13.COMPARATIVE SHARE ANALYSIS OF DESCRIPTIVE ANALYTICS HEALTHCARE FRAUD DETECTION MARKET,2021-2031(%)
- FIGURE 14.COMPARATIVE SHARE ANALYSIS OF PREDICTIVE ANALYTICS HEALTHCARE FRAUD DETECTION MARKET,2021-2031(%)
- FIGURE 15.COMPARATIVE SHARE ANALYSIS OF PRESCRIPTIVE ANALYSIS HEALTHCARE FRAUD DETECTION MARKET,2021-2031(%)
- FIGURE 16.HEALTHCARE FRAUD DETECTION MARKET,BY COMPONENT,2021(%)
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