Healthcare Fraud Analytics Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032

Healthcare Fraud Analytics Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032


Global Healthcare Fraud Analytics Market was valued at USD 2.3 billion in 2023 and projections indicate a robust growth trajectory, with an anticipated CAGR of 24.1% from 2024 to 2032. This surge is primarily driven by the escalating incidence of healthcare fraud, rising healthcare expenditures, the increasing complexity of healthcare systems, and the widespread adoption of digital health solutions.

As healthcare organizations strive to mitigate the repercussions of fraudulent activities, the demand for real-time fraud detection is intensifying. With real-time analytics, organizations can swiftly pinpoint and address suspicious activities, thereby curtailing the potential for fraud. This growing emphasis on real-time detection is bolstered by advancements in data processing technologies and the pressing need for expedited decision-making in fraud prevention.

The healthcare fraud analytics industry is bifurcated into solution type, deployment mode, application, end-use, and region.

The market segments its solutions into descriptive, prescriptive, and predictive analytics. In 2023, the descriptive analytics segment led the revenue chart, amassing USD 1.2 billion. Descriptive analytics empowers healthcare entities to scrutinize historical fraudulent activities while discerning the patterns, behaviors, and tactics employed by fraudsters. By delving into past data, organizations can pinpoint prevalent fraud schemes, leveraging this insight to bolster their detection systems. This emphasis on learning from historical fraud incidents significantly propels the demand for descriptive analytics.

The market classifies its deployment modes into on-premises and cloud-based solutions. In 2023, the on-premises solutions segment commanded a dominant 58% market share. Given that healthcare entities manage sensitive patient data ranging from medical histories to financial details, these become prime targets for cyber threats. On-premises solutions provide enhanced control over data security, allowing organizations to enforce their own protective measures within their infrastructure. This heightened emphasis on data security and privacy propels the preference for on-premises fraud analytics solutions.

In 2023, North America led the healthcare fraud analytics market with a revenue of USD 883.8 million. Forecasts suggest a growth rate of 23.8% from 2024 to 2032. North America's leadership in technological innovation, especially in data analytics, AI, and machine learning, plays a pivotal role. These advanced technologies facilitate superior fraud detection by sifting through vast data volumes to spot potential fraudulent patterns. Consequently, the region's access to state-of-the-art technology accelerates the adoption of sophisticated fraud analytics solutions.


Chapter 1 Methodology and Scope
1.1 Market scope and definitions
1.2 Research design
1.2.1 Research approach
1.2.2 Data collection methods
1.3 Base estimates and calculations
1.3.1 Base year calculation
1.3.2 Key trends for market estimation
1.4 Forecast model
1.5 Primary research and validation
1.5.1 Primary sources
1.5.2 Data mining sources
Chapter 2 Executive Summary
2.1 Industry 360° synopsis
Chapter 3 Industry Insights
3.1 Industry ecosystem analysis
3.2 Industry impact forces
3.2.1 Growth drivers
3.2.1.1 Rising incidence of healthcare fraud
3.2.1.2 Growing awareness and focus on fraud prevention
3.2.1.3 Technological advancements
3.2.2 Industry pitfalls and challenges
3.2.2.1 High implementation costs
3.2.2.2 Lack of skilled professionals
3.3 Growth potential analysis
3.4 Regulatory landscape
3.5 Reimbursement scenario
3.6 Porter's analysis
3.7 PESTEL analysis
3.8 Policy outlook
3.9 Gap analysis
3.10 Future market trends
Chapter 4 Competitive Landscape, 2023
4.1 Introduction
4.2 Company matrix analysis
4.3 Competitive analysis of major market players
4.4 Competitive positioning matrix
4.5 Strategy dashboard
Chapter 5 Market Estimates and Forecast, By Solution Type, 2021 – 2032 ($ Mn)
5.1 Key trends
5.2 Descriptive analytics
5.3 Prescriptive analytics
5.4 Predictive analytics
Chapter 6 Market Estimates and Forecast, By Deployment Mode, 2021 – 2032 ($ Mn)
6.1 Key trends
6.2 On-premises
6.3 Cloud-based
Chapter 7 Market Estimates and Forecast, By Application, 2021 – 2032 ($ Mn)
7.1 Key trends
7.2 Insurance claims review
7.2.1 Postpayment review
7.2.2 Prepayment review
7.3 Pharmacy billing issue
7.4 Payment integrity
7.5 Other applications
Chapter 8 Market Estimates and Forecast, By End-Use, 2021 – 2032 ($ Mn)
8.1 Key trends
8.2 Healthcare providers
8.3 Insurance companies
8.4 Government organizations
8.5 Other end-users
Chapter 9 Market Estimates and Forecast, By Region, 2021 – 2032 ($ Mn)
9.1 Key trends
9.2 North America
9.2.1 U.S.
9.2.2 Canada
9.3 Europe
9.3.1 Germany
9.3.2 UK
9.3.3 France
9.3.4 Spain
9.3.5 Italy
9.3.6 Netherlands
9.3.7 Rest of Europe
9.4 Asia Pacific
9.4.1 China
9.4.2 Japan
9.4.3 India
9.4.4 Australia
9.4.5 South Korea
9.4.6 Rest of Asia Pacific
9.5 Latin America
9.5.1 Brazil
9.5.2 Mexico
9.5.3 Argentina
9.5.4 Rest of Latin America
9.6 Middle East and Africa
9.6.1 South Africa
9.6.2 Saudi Arabia
9.6.3 UAE
9.6.4 Rest of Middle East and Africa
Chapter 10 Company Profiles
10.1 CGI Inc.
10.2 Change Healthcare
10.3 Conduent Incorporated
10.4 Cotiviti, Inc.
10.5 DXC Technology Company
10.6 EPIC
10.7 ExlService Holdings, Inc.
10.8 Fair Isaac Corporation
10.9 HCL Technologies Limited
10.10 IBM Corporation
10.11 LexisNexis Risk Solutions.
10.12 Optum Inc.
10.13 Qlarant Commercial Solutions, Inc.
10.14 SAS Institute Inc.
10.15 WIPRO LIMITED

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