CHAPTER 1. INTRODUCTION
1.1. Market Definition
1.2. Executive Summary
1.3. The Scope of the Study
CHAPTER 2. RESEARCH METHODOLOGY
2.1. Secondary Research
2.2. Primary Research
2.3. Analytic Tools and Model
2.4. Economic Indicator
2.4.1 Base Year, Base Currency, Forecasting Period
2.5. Expert Validation
2.6. Study Timeline
CHAPTER 3. MARKET ANALYSIS
3.1. Industry Value Chain Analysis
3.2. Porter's Five Force Analysis
3.2.1. Bargaining Power of Buyers
3.2.2. Bargaining Power of Suppliers
3.2.3. Threats of Substitutes
3.2.4. Threats of New Entrants
3.2.5. Degree of Competition
3.3. PESTLE Analysis
3.3.1. Political
3.3.2. Economical
3.3.3. Social
3.3.4. Technological
3.3.5. Legal
3.3.6. Environmental
3.4. SWOT Analysis
3.4.1. Strengths
3.4.2. Weakness
3.4.3. Opportunities
3.4.4. Threats
3.5. Y-O-Y Analysis
CHAPTER 4. MARKET DYNAMICS
4.1. Market Drivers
4.1.1. A large number of fraudulent activities in healthcare
4.1.2. High returns on investment
4.1.3. Prepayment review mode
4.1.4. Growing pressure of fraud, waste, and abuse on healthcare spending
4.2. Market Restraints & Challenges
4.2.1. Reluctance to adopt healthcare fraud analytics in emerging countries
4.2.2. Time-consuming deployment and need for frequent upgrades
4.3. Market Opportunities
4.3.1. The emergence of social media and its impact on the healthcare industry
4.3.2. Cloud-Based Analytics
CHAPTER 5. GLOBAL HEALTHCARE FRAUD DETECTION MARKET – BY
COMPONENT
5.1. Software
5.2. Services
CHAPTER 6. GLOBAL HEALTHCARE FRAUD DETECTION MARKET – BY
DELIVERY MODEL
6.1. On-Premise Delivery Models
6.2. On-Demand Delivery Models
CHAPTER 7. GLOBAL HEALTHCARE FRAUD DETECTION MARKET – BY TYPE
7.1. Descriptive Analytics
7.2. Predictive Analytics
7.3. Prescriptive Analytics
CHAPTER 8. GLOBAL HEALTHCARE FRAUD DETECTION MARKET – BY
APPLICATION
8.1. Insurance Claims Review
8.2. Payment Integrity
8.3. Other Applications
CHAPTER 9. GLOBAL HEALTHCARE FRAUD DETECTION MARKET – BY END
USER
9.1. Private Insurance Payers
9.2. Public/Government Agencies
9.3. Third-Party Service Providers
9.4. Employers
CHAPTER 10. GLOBAL HEALTHCARE FRAUD DETECTION MARKET - BY
GEOGRAPHY
10.1. Introduction
10.2. North America
10.2.1. U.S.
10.2.2. Canada
10.2.3. Mexico
10.2.4. Costa Rica
10.3. South America
10.3.1. Brazil
10.3.2. Argentina
10.3.3. Chile
10.3.4. Columbia
10.3.5. Others
10.4. Europe
10.4.1. U.K.
10.4.2. Germany
10.4.3. France
10.4.4. Italy
10.4.5. Spain
10.4.6. Russia
10.4.7. Netherlands
10.4.8. Switzerland
10.4.9. Poland
10.4.10. Others
10.5. APAC
10.5.1. China
10.5.2. Japan
10.5.3. India
10.5.4. South Korea
10.5.5. Australia & New Zealand
10.5.6. Malaysia
10.5.7. Singapore
10.5.8. Others
10.6. Middle East & Africa
10.6.1. UAE
10.6.2. Saudi Arabia
10.6.3. Iran
10.6.4. Iraq
10.6.5. Qatar
10.6.6. South Africa
10.6.7. Algeria
10.6.8. Morocco
10.6.9. Nigeria
10.6.10. Egypt
10.6.11. Others
CHAPTER 11. GLOBAL HEALTHCARE FRAUD DETECTION MARKET -
COMPANY PROFILES
11.1 IBM Corporation
11.2 Optum (A Part of UnitedHealth Group)
11.3 Verscend Technologies
11.4 Mckesson Corporation
11.5 Fair Isaac (Fico)
11.6 SAS Institute
11.7 Scio Health Analytics
11.8 Wipro Limited
11.9 Conduent
11.10 HCL Technologies
11.11 CGI Group
11.12 DXC Technology
11.13 Northrop Grumman
11.14 LexisNexis (A Part of Relx Group)
11.15 Pondera Solutions
CHAPTER 12. GLOBAL HEALTHCARE FRAUD DETECTION MARKET -
COMPETITIVE LANDSCAPE
12.1. Market Share Analysis
12.2. Strategies adopted by top companies
12.3. Mergers, Acquisitions, Collaborations & Agreements
CHAPTER 13. MARKET INSIGHTS
13.1. Industry Experts Insights
13.2. Analysts Opinions
13.3. Investment Opportunities
CHAPTER 14. APPENDIX
14.1. List of Tables
12.2. List of Figures
