Healthcare Fraud Detection Market Size, Share, and Trends 2024 to 2033

Healthcare Fraud Detection Market (By Type: Descriptive Analytics, Predictive Analytics, Prescriptive Analytics; By Application: Review of Insurance Claims, Payment Integrity; By End-user: Private Insurance Payers, Government Agencies) - Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2024-2033

  • Last Updated : February 2024
  • Report Code : 3877
  • Category : Healthcare

Healthcare Fraud Detection Market Size and Growth 2024 to 2033

The global healthcare fraud detection market size was valued at USD 2.02 billion in 2023 and is estimated to hit around USD 6.64 billion by 2033 with a CAGR of 12.65% from 2024 to 2033. Rising cases of health insurance claim fraud contributed to the growth of the healthcare fraud detection market.

Healthcare Fraud Detection Market Size 2024 to 2033

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Key Takeaways

  • By region, North America dominated the market in 2023.
  • By region, Asia Pacific is expected to grow at a significant rate during the forecast period.
  • By type, the descriptive analytics segment dominated the market in 2023.
  • By type, the predictive analytics segment is expected to grow at a notable pace during the forecast period.
  • By application, the review of the insurance claim segment dominated in 2023.
  • By application, the payment integrity segment is expected to grow at a significant rate in the market during the anticipated period.
  • By end-user, the healthcare payers segment held the largest share of the market in 2023.

Healthcare Fraud Detection Market in the U.S. 2024 to 2033

The U.S. healthcare fraud detection market size was valued at USD 550 million in 2023 and is anticipated to reach around USD 1,810 million by 2033, poised to grow at a CAGR of 12.70% from 2024 to 2033.

U.S. Healthcare Fraud Detection Market Size 2024 to 2033

North America dominated the healthcare fraud detection market in 2023. The growth of the market in the region is attributed to the rising healthcare infrastructure and increased expenditure on medical facilities, resulting in the rising number of health insurance companies, which contributed to the growth of the market. Developed economies like the United States and Canada have increasing per capita income and rising spending on healthcare infrastructure, which drives the growth of the market in the region. The region is the early adopter of technologies in every sector as compared to the other regions, and the increasing presence of the major market players is collectively contributing to the growth of the healthcare fraud detection market.

  • The U.S. Justice Department announced the federal and local criminal charges targeting 16 states and 78 defendants on the part of the law enforcement actions consisting of $2.5 billion in illegal claim healthcare fraud schemes accusing aged people, disabled people, pregnant women, and HIV patients.

Healthcare Fraud Detection Market Share, By Region, 2023 (%)

Asia Pacific is expected to significantly increase its presence in the healthcare fraud detection market during the forecast period. The growth of the region is expected to grow in the market owing to its continuously rising population in countries like China and India, and the rising healthcare expenditure from these countries is driving the healthcare market in the region. The increasing healthcare cost is one of the major factors of growing health insurance companies in the region, and the increasing fraud rates in healthcare are driving the demand for fraud prevention solutions, which accelerated the growth of the healthcare fraud detection market across the region.

Healthcare Fraud Detection Market Overview

Healthcare fraud is the type of fraud associated with the healthcare system by medical providers, individuals, or the insurance company. Healthcare fraud includes medical claim auditing, accounts auditing, and auditing of healthcare funds. Healthcare fraud does not seem like a crime that can hurt another individual, but it does have negative impacts on others. Healthcare fraud is commonly the act of intentionally interpreting the symptoms or diseases to receive more advantages or benefits from insurance companies. The U.S. insurance companies are estimated to lose billions of dollars every year to this kind of healthcare fraud. Healthcare fraud prevention works on reducing healthcare fraud, abuse, and waste. The rising number of patients opting for health insurance is boosting the growth of the healthcare fraud detection market.

Growth Factors

  • The rising healthcare sector and the increasing number of patients getting health insurance for claiming hospital bills are driving the growth of the healthcare fraud detection market. The rising operational efficiency and reduced healthcare expenditure are further boosting the growth of the market.
  • The increasing number of fraud activities in the healthcare industry is driving the demand for the healthcare fraud prevention system. The rising technological advancements in the healthcare industry are driving the growth of the market.
  • Technological advancements such as software-based data mining, artificial intelligence, and machine learning are all collectively driving the growth of the healthcare fraud detection market.
  • The rising population and the increasing number of geriatric population and chronic diseases are boosting the growth of the health insurance market, which requires a safer and more preventive environment due to the rising number of fraud activities that are driving the growth of the market.
  • The cases of healthcare fraud are rising every year, and the traditional healthcare detection system is limited; it is not efficient and effective in use; thus, the increasing demand for the latest healthcare fraud detection prevention system accelerates the growth of the market.

Healthcare Fraud Detection Market Scope

Report Coverage Details
Growth Rate from 2024 to 2033 CAGR of 12.65%
Global Market Size in 2023 USD  2.02 Billion
Global Market Size by 2033 USD 6.64 Billion
U.S. Market Size in 2023 USD 550 Million
U.S. Market Size by 2033 USD 1,810 Million
Base Year 2023
Forecast Period 2024 to 2033
Segments Covered By Type, By Application, and By End-user
Regions Covered North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa


Healthcare Fraud Detection Market Dynamics

Driver: Technological advancement in the market

Predictive modeling can use predictive analytics, data mining, and quantitive analysis to identify patterns in provider behavior and fraud. Blockchain can make it impossible to change the data for fraudulent practices and enables detailed asset tracking. AI-based pattern recognition technology can allow, automate, and learn about the process of identifying billions of coding errors, leading to saving money, time, and resources. Such integration of technologies is observed to create a significant driver for the healthcare fraud detection market.

Predictive modeling can use predictive analytics, data mining, and quantitive analysis to identify patterns in provider behavior and fraud. Blockchain can make it impossible to change the data for fraudulent practices and enables detailed asset tracking. AI-based pattern recognition technology can allow, automate, and learn about the process of identifying billions of coding errors, leading to saving money, time, and resources.

Restraint: Lack of knowledge about the service

The healthcare fraud detection market is observed to get hampered due to the lack of knowledge and awareness regarding the services offered for fraud detection in the healthcare sector. Multiple underdeveloped areas lack professionals that can manage such services with the integration of technology.

Opportunity: Investments in ICT

The rapidly growing amount of healthcare data is predicted to be accompanied by a steady growth in the usage of new technologies, such as artificial intelligence (AI). Investing in ICT to boost fraud management efficacy is a crucial component of fraud detection. This entails making investments in personnel and systems that are specifically designed to detect and prevent fraudulent activities, which are rapidly changing in a digital setting.

The creation of a web-based online pharmacy system is explained by the need to create a system for more effective billing and medication delivery. It enables the development of an interoperable system with partner pharmacies and enhancements to the billing process. The rising number of on-time claim submissions, efficiency gains, and fraud reduction are all significantly impacted by the system.

Type Insights

The descriptive analytics segment dominated the healthcare fraud detection market in 2023. Descriptive analytics is often called the simplest form of data analysis because it explains relationships and trends. It is the process of analyzing the historical and current data for the identification of trends and relationships. Descriptive analytics are one of the essential parts of the healthcare sector. It is an essential application in the healthcare sector for enabling the trends, patterns, and benchmarks of the patient's data. Descriptive analysis helps extract knowledge from healthcare for the understanding of history, and that helps facilitate informed decision-making in the upcoming period.

The predictive analytics segment is observed to expand at a rapid pace during the forecast period. Predictive analytics is the advanced technology of data analytics used in future prediction by analyzing historical data. The advancements in big data machine learning contribute to the expansion of predictive analytics. The predictive analysis process uses machine learning, data analysis, statistical models, and artificial intelligence to find the pattern that may predict future behavior. Predictive analytics technology is highly beneficial for the healthcare industry, where it can predict future forecasts and help identify high-risk patients.

Predictive analytics helps to improve patient outcomes, and data analysis makes personal treatment plans and optimizes resource allocation. Predictive analytics in insurance fraud detection uses statistical techniques and data for the identification of fraud patterns and to disclose fraudulent items. Predictive analytics collect data from various sources like self-service apps, customer portals, telematics, customer relationship management (CRM) systems, etc., and predict accurate insights.

Application Insights

The review of the insurance claim segment dominated the healthcare fraud detection market share of 67% in 2023. The segment is further divided into the post-payments review and prepayment review. The rising acceptance of health insurance by the population and the rising number of fraud activities are boosting the growth of the market. There are various benefits associated with fraud prevention in the insurance claim fraud will be more accurately recognized in every claim that is deemed to be fraudulent and requires very little time for data processing.

Healthcare Fraud Detection Market Share, By Application, 2023 (%)

The payment integrity segment is expected to grow at a significant rate in the healthcare fraud detection market during the anticipated period. Payment integrity for healthcare payers traditionally features fraud detection and provider audits to ensure the healthcare procedures are precisely coded for reimbursement. There are various functions that are included in payment integrity, such as claim accuracy or editing, coordination of benefits, and clinical validation.

In claim accuracy, claims are reviewed to find omissions, errors, and questing data against a larger database that includes government and industrial rules and regulations and the policies governing medical claims. Coordination of benefits ensures that the same person is not paid many times when one person has many insurance policies. Hospital bill audit, clinical review and resolution, DRG validation, and outpatient audit are all part of the clinical validation.

End-user Insights

The healthcare payers segment held the largest share in the healthcare fraud detection market in 2023. The growth of the segment is attributed to the increasing number of insurance agencies that are adopting the healthcare fraud prevention solution for analyzing misleading claims or false information to get payers to the ineligible medical procedures. Several insurance companies used the fraud management system to automate and streamline the overall investigation process to identify and filter the flag suspicious claims. Investigation of the entire process manually takes more time and cannot be done efficiently, though the fraud management system is a reliable source for managing the process and saving more time, money, and resources.

Recent Developments

  • In February 2024, BharatGPT and Vizzhy are about to announce the launch of Healthcare LLM; VizzhyGPT is a multimodal model with a vision of automating diverse hospital processes in the clinical and non-clinical realm.
  • In January 2024, Healthcare Fraud Shield (HCFS), one of the leading firms that provide fraud, waste, abuse, and error (FWAE) protection solutions to the health insurance market, launched FWA360Leads®, the latest solution that automatically prioritizes and identifies fraud, waste, abuse, and error (FWAE) leads as per their severity and importance.

Healthcare Fraud Detection Market Companies

  • CGI Group
  • Conduent
  • DXC Technology Company
  • EXLSERVICE Holdings Inc.
  • Fair ISAAC Corporation
  • HCL Technologies
  • International Business Machines Corporation (IBM)
  • LexisNexis
  • McKesson Corporation
  • Northrop Grumman
  • Optum
  • OSP Labs
  • SAS Institute Inc.
  • Scioinspire CORP.
  • UNITEDHEALTH Group
  • Verscend Technologies
  • WIPRO Limited

Segments Covered in the Report

By Type

  • Descriptive Analytics
  • Predictive Analytics
  • Prescriptive Analytics 

By Application

  • Review of Insurance Claims
  • Payment Integrity

By End-user

  • Private Insurance Payers
  • Government Agencies

By Geography

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East and Africa

Frequently Asked Questions

The global healthcare fraud detection market size is expected to increase USD 6.64 billion by 2033 from USD 2.02 billion in 2023.

The global healthcare fraud detection market will register growth rate of 12.65% between 2024 and 2033.

The major players operating in the healthcare fraud detection market are CGI Group, Conduent, DXC Technology Company, EXLSERVICE Holdings Inc., Fair ISAAC Corporation, HCL Technologies, International Business Machines Corporation (IBM), LexisNexis, McKesson Corporation, Northrop Grumman, Optum, OSP Labs, SAS Institute Inc., Scioinspire CORP., UNITEDHEALTH Group, Verscend Technologies, WIPRO Limited, and Others.

The driving factors of the healthcare fraud detection market are the technological advancement in the market and increasing number of patients getting health insurance.

North America region will lead the global healthcare fraud detection market during the forecast period 2024 to 2033.

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology (Premium Insights)

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis 

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on Healthcare Fraud Detection Market 

5.1. COVID-19 Landscape: Healthcare Fraud Detection Industry Impact

5.2. COVID 19 - Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

Chapter 6. Market Dynamics Analysis and Trends

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global Healthcare Fraud Detection Market, By Type

8.1. Healthcare Fraud Detection Market, by Type, 2024-2033

8.1.1 Descriptive Analytics

8.1.1.1. Market Revenue and Forecast (2021-2033)

8.1.2. Predictive Analytics

8.1.2.1. Market Revenue and Forecast (2021-2033)

8.1.3. Prescriptive Analytics

8.1.3.1. Market Revenue and Forecast (2021-2033)

Chapter 9. Global Healthcare Fraud Detection Market, By Application

9.1. Healthcare Fraud Detection Market, by Application, 2024-2033

9.1.1. Review of Insurance Claims

9.1.1.1. Market Revenue and Forecast (2021-2033)

9.1.2. Payment Integrity

9.1.2.1. Market Revenue and Forecast (2021-2033)

Chapter 10. Global Healthcare Fraud Detection Market, By End-user 

10.1. Healthcare Fraud Detection Market, by End-user, 2024-2033

10.1.1. Private Insurance Payers

10.1.1.1. Market Revenue and Forecast (2021-2033)

10.1.2. Government Agencies

10.1.2.1. Market Revenue and Forecast (2021-2033)

Chapter 11. Global Healthcare Fraud Detection Market, Regional Estimates and Trend Forecast

11.1. North America

11.1.1. Market Revenue and Forecast, by Type (2021-2033)

11.1.2. Market Revenue and Forecast, by Application (2021-2033)

11.1.3. Market Revenue and Forecast, by End-user (2021-2033)

11.1.4. U.S.

11.1.4.1. Market Revenue and Forecast, by Type (2021-2033)

11.1.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.1.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.1.5. Rest of North America

11.1.5.1. Market Revenue and Forecast, by Type (2021-2033)

11.1.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.1.5.3. Market Revenue and Forecast, by End-user (2021-2033)

11.2. Europe

11.2.1. Market Revenue and Forecast, by Type (2021-2033)

11.2.2. Market Revenue and Forecast, by Application (2021-2033)

11.2.3. Market Revenue and Forecast, by End-user (2021-2033)

11.2.4. UK

11.2.4.1. Market Revenue and Forecast, by Type (2021-2033)

11.2.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.2.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.2.5. Germany

11.2.5.1. Market Revenue and Forecast, by Type (2021-2033)

11.2.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.2.5.3. Market Revenue and Forecast, by End-user (2021-2033)

11.2.6. France

11.2.6.1. Market Revenue and Forecast, by Type (2021-2033)

11.2.6.2. Market Revenue and Forecast, by Application (2021-2033)

11.2.6.3. Market Revenue and Forecast, by End-user (2021-2033)

11.2.7. Rest of Europe

11.2.7.1. Market Revenue and Forecast, by Type (2021-2033)

11.2.7.2. Market Revenue and Forecast, by Application (2021-2033)

11.2.7.3. Market Revenue and Forecast, by End-user (2021-2033)

11.3. APAC

11.3.1. Market Revenue and Forecast, by Type (2021-2033)

11.3.2. Market Revenue and Forecast, by Application (2021-2033)

11.3.3. Market Revenue and Forecast, by End-user (2021-2033)

11.3.4. India

11.3.4.1. Market Revenue and Forecast, by Type (2021-2033)

11.3.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.3.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.3.5. China

11.3.5.1. Market Revenue and Forecast, by Type (2021-2033)

11.3.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.3.5.3. Market Revenue and Forecast, by End-user (2021-2033)

11.3.6. Japan

11.3.6.1. Market Revenue and Forecast, by Type (2021-2033)

11.3.6.2. Market Revenue and Forecast, by Application (2021-2033)

11.3.6.3. Market Revenue and Forecast, by End-user (2021-2033)

11.3.7. Rest of APAC

11.3.7.1. Market Revenue and Forecast, by Type (2021-2033)

11.3.7.2. Market Revenue and Forecast, by Application (2021-2033)

11.3.7.3. Market Revenue and Forecast, by End-user (2021-2033)

11.4. MEA

11.4.1. Market Revenue and Forecast, by Type (2021-2033)

11.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.4.4. GCC

11.4.4.1. Market Revenue and Forecast, by Type (2021-2033)

11.4.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.4.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.4.5. North Africa

11.4.5.1. Market Revenue and Forecast, by Type (2021-2033)

11.4.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.4.5.3. Market Revenue and Forecast, by End-user (2021-2033)

11.4.6. South Africa

11.4.6.1. Market Revenue and Forecast, by Type (2021-2033)

11.4.6.2. Market Revenue and Forecast, by Application (2021-2033)

11.4.6.3. Market Revenue and Forecast, by End-user (2021-2033)

11.4.7. Rest of MEA

11.4.7.1. Market Revenue and Forecast, by Type (2021-2033)

11.4.7.2. Market Revenue and Forecast, by Application (2021-2033)

11.4.7.3. Market Revenue and Forecast, by End-user (2021-2033)

11.5. Latin America

11.5.1. Market Revenue and Forecast, by Type (2021-2033)

11.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.5.3. Market Revenue and Forecast, by End-user (2021-2033)

11.5.4. Brazil

11.5.4.1. Market Revenue and Forecast, by Type (2021-2033)

11.5.4.2. Market Revenue and Forecast, by Application (2021-2033)

11.5.4.3. Market Revenue and Forecast, by End-user (2021-2033)

11.5.5. Rest of LATAM

11.5.5.1. Market Revenue and Forecast, by Type (2021-2033)

11.5.5.2. Market Revenue and Forecast, by Application (2021-2033)

11.5.5.3. Market Revenue and Forecast, by End-user (2021-2033)

Chapter 12. Company Profiles

12.1. CGI Group

12.1.1. Company Overview

12.1.2. Product Offerings

12.1.3. Financial Performance

12.1.4. Recent Initiatives

12.2. Conduent

12.2.1. Company Overview

12.2.2. Product Offerings

12.2.3. Financial Performance

12.2.4. Recent Initiatives

12.3. DXC Technology Company

12.3.1. Company Overview

12.3.2. Product Offerings

12.3.3. Financial Performance

12.3.4. Recent Initiatives

12.4. EXLSERVICE Holdings Inc.

12.4.1. Company Overview

12.4.2. Product Offerings

12.4.3. Financial Performance

12.4.4. Recent Initiatives

12.5. Fair ISAAC Corporation

12.5.1. Company Overview

12.5.2. Product Offerings

12.5.3. Financial Performance

12.5.4. Recent Initiatives

12.6. HCL Technologies

12.6.1. Company Overview

12.6.2. Product Offerings

12.6.3. Financial Performance

12.6.4. Recent Initiatives

12.7. International Business Machines Corporation (IBM)

12.7.1. Company Overview

12.7.2. Product Offerings

12.7.3. Financial Performance

12.7.4. Recent Initiatives

12.8. LexisNexis

12.8.1. Company Overview

12.8.2. Product Offerings

12.8.3. Financial Performance

12.8.4. Recent Initiatives

12.9. McKesson Corporation

12.9.1. Company Overview

12.9.2. Product Offerings

12.9.3. Financial Performance

12.9.4. Recent Initiatives

12.10. Northrop Grumman

12.10.1. Company Overview

12.10.2. Product Offerings

12.10.3. Financial Performance

12.10.4. Recent Initiatives

Chapter 13. Research Methodology

13.1. Primary Research

13.2. Secondary Research

13.3. Assumptions

Chapter 14. Appendix

14.1. About Us

14.2. Glossary of Terms

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