Global Healthcare Fraud Detection Market Size Study, by Component, by Application, by End User, by Type and Regional Forecasts 2022-2032

Description

Global Healthcare Fraud Detection Market, was valued at approximately USD 1.42 billion in 2023, is anticipated to witness significant growth rate of about CAGR 12.68% over the period from 2024 to 2032. Healthcare fraud is characterized by intentional misrepresentation or deception by healthcare professionals or patients, leading to unauthorized payments or benefits. Common examples include falsified data by physicians, duplicate claims by different providers, claims for services not provided, and misrepresented dates or descriptions of treatments. The growing complexity of such fraudulent activities has necessitated the development and deployment of sophisticated fraud detection solutions.

The Global Healthcare Fraud Detection Market is driven by the escalating adoption of advanced data mining and artificial intelligence (AI) technologies in the healthcare sector. Healthcare fraud detection is becoming increasingly critical as healthcare fraudulence cases, including healthcare fund fraud, false medical claims, and insurance fraud, continue to rise. The process involves comprehensive auditing of accounts, medical claims, and healthcare funds to prevent fraud, waste, and abuse. The market is expected to advance rapidly due to the increasing integration of AI, machine learning, and data analytics in healthcare fraud detection systems. These technologies are enhancing the efficiency of fraud detection processes, enabling real-time monitoring and analysis, and improving payment integrity. However, challenges such as rising data breaches in the healthcare industry and lower awareness of fraud analytics solutions in emerging markets may impede market growth.

The key regions considered for the market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. In 2023, North America held the largest revenue share in the healthcare fraud detection market, driven by the high incidence of fraudulence cases in the U.S. and Mexico, coupled with the growing adoption of innovative analytical techniques and software solutions. Furthermore, Asia Pacific is anticipated to grow fastest during the forecast period 2022-2032.

Major market players included in this report are:

Verscend Technologies
Fair Isaac Corporation
CGI Inc.
Wipro Limited
Optum
SAS Institute Inc.
LexisNexis
SCIO Inspire, Corp.
OSP Labs
HCL Technologies

The detailed segments and sub-segment of the market are explained below:

By Component:

Services
Software

By Application:

Payment Integrity
Insurance Claims Review

By End User:

Healthcare Payer
Government Agencies
Others

By Type:

Descriptive Analytics
Predictive Analytics
Prescriptive Analytics

By Region:

North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
RoLA
Middle East & Africa
Saudi Arabia
South Africa
RoMEA

Years considered for the study are as follows:

Historical year - 2022
Base year - 2023
Forecast period - 2024 to 2032

Key Takeaways:

Market Estimates & Forecast for 10 years from 2022 to 2032.
Annualized revenues and regional level analysis for each market segment.
Detailed analysis of geographical landscape with Country level analysis of major regions.
Competitive landscape with information on major players in the market.
Analysis of key business strategies and recommendations on future market approach.
Analysis of competitive structure of the market.
Demand side and supply side analysis of the market

Chapter 1. Global Healthcare Fraud Detection Market Executive Summary

1.1. Global Healthcare Fraud Detection Market Size & Forecast (2022-2032)
1.2. Regional Summary
1.3. Segmental Summary
- 1.3.1. By Component
- 1.3.2. By Application
- 1.3.3. By End User
- 1.3.4. By Type
1.4. Key Trends
1.5. Recession Impact
1.6. Analyst Recommendation & Conclusion

Chapter 2. Global Healthcare Fraud Detection Market Definition and Research Assumptions

2.1. Research Objective
2.2. Market Definition
2.3. Research Assumptions
- 2.3.1. Inclusion & Exclusion
- 2.3.2. Limitations
- 2.3.3. Supply Side Analysis
  - 2.3.3.1. Availability
  - 2.3.3.2. Infrastructure
  - 2.3.3.3. Regulatory Environment
  - 2.3.3.4. Market Competition
  - 2.3.3.5. Economic Viability (Consumer's Perspective)
- 2.3.4. Demand Side Analysis
  - 2.3.4.1. Regulatory frameworks
  - 2.3.4.2. Technological Advancements
  - 2.3.4.3. Environmental Considerations
  - 2.3.4.4. Consumer Awareness & Acceptance
2.4. Estimation Methodology
2.5. Years Considered for the Study
2.6. Currency Conversion Rates

Chapter 3. Global Healthcare Fraud Detection Market Dynamics

3.1. Market Drivers
- 3.1.1. Increasing Incidence of Healthcare Fraud
- 3.1.2. Rising Adoption of AI and Data Mining in Fraud Detection
- 3.1.3. Expansion of Healthcare Services and Insurance Claim Reviews
3.2. Market Challenges
- 3.2.1. Data Breaches in Healthcare
- 3.2.2. Low Awareness of Fraud Detection Solutions in Emerging Markets
3.3. Market Opportunities
- 3.3.1. Technological Advancements in Fraud Detection Software
- 3.3.2. Growing Demand for Healthcare Insurance
- 3.3.3. Expansion of Healthcare Infrastructure in Emerging Economies

Chapter 4. Global Healthcare Fraud Detection Market Industry Analysis

4.1. Porter's 5 Force Model
- 4.1.1. Bargaining Power of Suppliers
- 4.1.2. Bargaining Power of Buyers
- 4.1.3. Threat of New Entrants
- 4.1.4. Threat of Substitutes
- 4.1.5. Competitive Rivalry
- 4.1.6. Futuristic Approach to Porter's 5 Force Model
- 4.1.7. Porter's 5 Force Impact Analysis
4.2. PESTEL Analysis
- 4.2.1. Political
- 4.2.2. Economical
- 4.2.3. Social
- 4.2.4. Technological
- 4.2.5. Environmental
- 4.2.6. Legal
4.3. Top Investment Opportunities
4.4. Top Winning Strategies
4.5. Disruptive Trends
4.6. Industry Expert Perspective
4.7. Analyst Recommendation & Conclusion

Chapter 5. Global Healthcare Fraud Detection Market Size & Forecasts by Component (2022-2032)

5.1. Segment Dashboard
5.2. Global Healthcare Fraud Detection Market: Services Revenue Trend Analysis, 2022 & 2032 (USD Billion)
5.3. Global Healthcare Fraud Detection Market: Software Revenue Trend Analysis, 2022 & 2032 (USD Billion)

Chapter 6. Global Healthcare Fraud Detection Market Size & Forecasts by Application (2022-2032)

6.1. Segment Dashboard
6.2. Global Healthcare Fraud Detection Market: Payment Integrity Revenue Trend Analysis, 2022 & 2032 (USD Billion)
6.3. Global Healthcare Fraud Detection Market: Insurance Claims Review Revenue Trend Analysis, 2022 & 2032 (USD Billion)

Chapter 7. Global Healthcare Fraud Detection Market Size & Forecasts by End User (2022-2032)

7.1. Segment Dashboard
7.2. Global Healthcare Fraud Detection Market: Healthcare Payer Revenue Trend Analysis, 2022 & 2032 (USD Billion)
7.3. Global Healthcare Fraud Detection Market: Government Agencies Revenue Trend Analysis, 2022 & 2032 (USD Billion)
7.4. Global Healthcare Fraud Detection Market: Others Revenue Trend Analysis, 2022 & 2032 (USD Billion)

Chapter 8. Global Healthcare Fraud Detection Market Size & Forecasts by Type (2022-2032)

8.1. Segment Dashboard
8.2. Global Healthcare Fraud Detection Market: Descriptive Analytics Revenue Trend Analysis, 2022 & 2032 (USD Billion)
8.3. Global Healthcare Fraud Detection Market: Predictive Analytics Revenue Trend Analysis, 2022 & 2032 (USD Billion)
8.4. Global Healthcare Fraud Detection Market: Prescriptive Analytics Revenue Trend Analysis, 2022 & 2032 (USD Billion)

Chapter 9. Global Healthcare Fraud Detection Market Size & Forecasts by Region (2022-2032)

9.1. North America Healthcare Fraud Detection Market
- 9.1.1. U.S. Healthcare Fraud Detection Market
  - 9.1.1.1. By Component size & forecasts, 2022-2032
  - 9.1.1.2. By Application size & forecasts, 2022-2032
  - 9.1.1.3. By End User size & forecasts, 2022-2032
  - 9.1.1.4. By Type size & forecasts, 2022-2032
- 9.1.2. Canada Healthcare Fraud Detection Market
9.2. Europe Healthcare Fraud Detection Market
- 9.2.1. U.K. Healthcare Fraud Detection Market
- 9.2.2. Germany Healthcare Fraud Detection Market
- 9.2.3. France Healthcare Fraud Detection Market
- 9.2.4. Spain Healthcare Fraud Detection Market
- 9.2.5. Italy Healthcare Fraud Detection Market
- 9.2.6. Rest of Europe Healthcare Fraud Detection Market
9.3. Asia-Pacific Healthcare Fraud Detection Market
- 9.3.1. China Healthcare Fraud Detection Market
- 9.3.2. India Healthcare Fraud Detection Market
- 9.3.3. Japan Healthcare Fraud Detection Market
- 9.3.4. Australia Healthcare Fraud Detection Market
- 9.3.5. South Korea Healthcare Fraud Detection Market
- 9.3.6. Rest of Asia Pacific Healthcare Fraud Detection Market
9.4. Latin America Healthcare Fraud Detection Market
- 9.4.1. Brazil Healthcare Fraud Detection Market
- 9.4.2. Mexico Healthcare Fraud Detection Market
- 9.4.3. Rest of Latin America Healthcare Fraud Detection Market
9.5. Middle East & Africa Healthcare Fraud Detection Market
- 9.5.1. Saudi Arabia Healthcare Fraud Detection Market
- 9.5.2. South Africa Healthcare Fraud Detection Market
- 9.5.3. Rest of Middle East & Africa Healthcare Fraud Detection Market

Chapter 10. Competitive Intelligence

10.1. Key Company SWOT Analysis
10.2. Top Market Strategies
10.3. Company Profiles
- 10.3.1. Verscend Technologies
  - 10.3.1.1. Key Information
  - 10.3.1.2. Overview
  - 10.3.1.3. Financial (Subject to Data Availability)
  - 10.3.1.4. Product Summary
  - 10.3.1.5. Market Strategies
- 10.3.2. Fair Isaac Corporation
- 10.3.3. CGI Inc.
- 10.3.4. Wipro Limited
- 10.3.5. Optum
- 10.3.6. SAS Institute Inc.
- 10.3.7. LexisNexis
- 10.3.8. SCIO Inspire, Corp.
- 10.3.9. OSP Labs
- 10.3.10. HCL Technologies

Chapter 11. Research Process

11.1. Research Process
- 11.1.1. Data Mining
- 11.1.2. Analysis
- 11.1.3. Market Estimation
- 11.1.4. Validation
- 11.1.5. Publishing
11.2. Research Attributes