Healthcare Fraud Analytics Market 2021 Global Scope by Solution Type, Application, Delivery, End-User, Outlook, Drivers and Key Player IBM Corporation (US), Optum (US), SAS Institute(US), Change Healthcare(US)

An influential Healthcare Fraud Analytics Market report provides an absolute overview of the market that covers various aspects of market analysis, product definition, market segmentation, key developments, and the existing vendor landscape. The competitive analysis covered here also puts light on the various strategies used by major players of the market which range from new product launches, expansions, agreements, joint ventures, partnerships, acquisitions, and many others that lead to increase their footprints in this market. To achieve a comprehensive analysis of the market structure along with estimations of the various segments and sub-segments of the industry, businesses call for such a well-structured Healthcare Fraud Analytics Market research report.

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Healthcare Fraud Analytics Market by Solution Type (Descriptive, Predictive, Prescriptive), Application (Insurance Claim (Postpayment, Prepayment), Payment Integrity), Delivery (On-premise, Cloud), End-User (Insurance, Government) – Global Forecast to 2025 Some of the major market players in the healthcare fraud analytics market are IBM Corporation (US), Optum (US), SAS Institute(US), Change Healthcare(US), EXL Service Holdings(US), Cotiviti (US), Wipro Limited (India), Conduent(US), HCL (India), Canadian Global Information Technology Group (Canada), DXC Technology Company (US), Northrop Grumman Corporation (US), LexisNexis Group (US), and Pondera Solutions (US).

The healthcare fraud analytics market is projected to reach USD 4.6 billion by 2025 from USD 1.2 billion in 2020 at a CAGR of 29.8%. The emergence of social network analytics, the adoption of technologies such as AI and blockchain, and the growing use of healthcare analytics for fraud detection in emerging nations like the APAC provide growth opportunities in this market. However, the time-consuming deployment of these solutions and the need for frequent updates are some challenges faced by end users of this market.

The on-demand segment is projected to witness the highest growth during the forecast period

On the basis of delivery model, the healthcare fraud analytics market is segmented into on-premise and on-demand models. The on-demand models include the cloud-based and web-based models. The on-demand segment is projected to register the highest CAGR during the forecast period. Factors such as on-demand self-serving analytics, the lack of up-front capital investments for hardware, extreme capacity flexibility, and a pay-as-you-go pricing model are driving the demand for on-demand fraud detection solutions.

The prepayment review model is projected to witness the highest growth during the forecast period

On the basis of application, the healthcare fraud analytics market is segmented into insurance claims review, pharmacy billing misuse, payment integrity, and other applications. The insurance claims review segment is further divided into post payment and prepayment review, with the latter expected to register the highest growth during the forecast period. This is mainly because the use of prepayment review protocols and analytics can help organizations proactively prevent fraud prior to payment, allowing rapid action to be taken. As a result, prepayment review solutions are expected to garner greater attention in the coming years.

The Asia Pacific to witness the highest growth during the forecast period

The Asia Pacific is expected to witness the highest growth during the forecast period (2020 to 2025), owing to factors such as the growing demand for health insurance and increasing collaborations & partnerships between governments and tech giants for leveraging fraud analytics capabilities.

A breakdown of primary participants involved in making this report is mentioned below:

  • By Company Type: Tier 1–45%, Tier 2–18%, and Tier 3–37%
  • By Designation: C Level–35%, Director Level–50%, Others–15%
  • By Region: North America–60%,Asia Pacific–22%, Europe–13%, Latin America–2%, Middle East and Africa–3%

Research Coverage:

The report analyzes the healthcare fraud analytics market and aims at estimating the market size and future growth potential of this market based on various segmentations, such as solution type, delivery model, application, enduser, and region. It also covers the competitive leadership mapping, which analyzes the position of key market players and classifies them based on their capabilities. The report providesa competitive analysis of the key players in this market, along with their profiles, offerings, recent developments, and key market strategies.

Reasons to Buy the Report

The report will enrich established firms as well as new entrants/smaller firms to gauge the pulse of the market to help them garner a greater share of the market. Firms purchasing the report could use one or any combination of the below-mentioned strategies to strengthen their position in the market.

This report provides insights into the following pointers:

  • Market Penetration: Comprehensive information on the portfolios of top players in the global healthcare fraud analytics market. The report analyzes this market by solution type, delivery model, application, end user, and region.
  • Product Enhancement/Innovation: Detailed insights on upcoming technology trends in the global healthcare fraud analytics market
  • Market Development: Comprehensive information on the lucrative emerging markets
  • Market Diversification: Exhaustive information about growing geographies, recent developments, and collaborations in the healthcare fraud analytics market
  • Competitive Assessment: In-depth assessment of growth strategies, offerings, and capabilities of leading players in the global healthcare fraud analytics market

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Table of Contents

1 Introduction
1.1 Objectives of the Study
1.2 Market Definition
1.3 Market Scope
1.3.1 Markets Covered
1.3.2 Years Considered for the Study
1.4 Currency
1.5 Limitations
1.6 Stakeholders

2 Research Methodology
2.1 Research Approach
2.1.1 Secondary Sources Key Data From Secondary Sources
2.1.2 Primary Sources Key Data From Primary Sources
2.2 Market Size Estimation
2.3 Market Breakdown and Data Triangulation
2.4 Assumptions for the Study

3 Executive Summary

4 Premium Insights
4.1 Healthcare Fraud Analytics Market Overview
4.2 Asia Pacific: Market, By Solution Type and Application (2019)
4.3 Market: Geographic Growth Opportunities
4.4 Market: Regional Mix
4.5 Market: Developing vs Developed Regions

5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers Large Number of Fraudulent Activities in Healthcare Increasing Number of Patients Seeking Health Insurance Prepayment Review Model High Returns on Investment Rise in Pharmacy Claims-Related Fraud
5.2.2 Restraints Limitations in the Data Capturing Process in Medicaid Services
5.2.3 Opportunities Adoption of Healthcare Fraud Analytics in Developing Countries Emergence of Social Media and Its Impact on the Healthcare Industry Role of AI in Healthcare Fraud Detection
5.2.4 Challenges Dearth of Skilled Personnel Time-Consuming Deployment and the Need for Frequent Upgrades

6 Industry Insights
6.1 Industry Trends
6.1.1 Shifting Focus From On-Premise Models to Cloud-Based On-Demand Models
6.1.2 Mergers and Acquisitions: the Most Adopted Strategy
6.1.3 Technological Advancements
6.1.4 New Use Case: Opioid Epidemic Crisis
6.1.5 End-User Trends: Adoption of Healthcare Fraud Analytics Solutions By Pharmacy Benefit Managers

7 Healthcare Fraud Analytics Market, By Solution Type
7.1 Introduction
7.2 Descriptive Analytics
7.2.1 Descriptive Analytics Segment Accounted for the Largest Market Share
7.3 Predictive Analytics
7.3.1 Predictive Analytics Helps in Simulating Future Events & Trends That Can Enable Payers to Predict Preventable Events
7.4 Prescriptive Analytics
7.4.1 Prescriptive Models Offer Additional Advantages Relating to the Investigation of Suspicious Behavior to Generate Comprehensive Insights

8 Healthcare Fraud Analytics Market, By Delivery Model
8.1 Introduction
8.2 On-Premise Delivery Models
8.2.1 On-Premise Models Account for the Largest Share of the Market
8.3 On-Demand Delivery Models
8.3.1 Cloud-Based Delivery Models Offer Organizations Increased Scalability and Speed

9 Healthcare Fraud Analytics Market, By Application
9.1 Introduction
9.2 Insurance Claims Review
9.2.1 Postpayment Review Postpayment Review Dominated the Healthcare Fraud Analytics Insurance Claims Review Market
9.2.2 Prepayment Review The Majority of Prepayment Models Use Predictive Analytics to Detect Fraud and Stop Fraudulent Claims Payments
9.3 Pharmacy Billing Misuse
9.3.1 Fraud, Waste, and Abuse Cases in Pharmacy and Prescription Drug Areas are Driving the Demand for Analytics
9.4 Payment Integrity
9.4.1 Changes in Regulatory Guidelines have Aided the Adoption of Payment Integrity Software
9.5 Other Applications

10 Healthcare Fraud Analytics Market, By End User
10.1 Introduction
10.2 Public & Government Agencies
10.2.1 Public & Government Agencies Dominate the Healthcare Fraud Analytics Market, By End User
10.3 Private Insurance Payers
10.3.1 Private Insurance Payers are Focused on Deploying Analytics to Combat Increasing Monetary Losses
10.4 Third-Party Service Providers
10.4.1 Adoption of Fraud Analytics Solutions By Public Insurers Puts Private Bodies at Risk, Driving Attention Toward Outsourcing
10.5 Employers
10.5.1 Employers are Considering Fraud Analytics Solutions as A Step Toward Better Cost Management

11 Healthcare Fraud Analytics Market, By Region
11.1 Introduction
11.2 North America
11.2.1 US US Dominates the Global Healthcare Fraud Analytics Market
11.2.2 Canada Growing Adoption of Data-Crunching Technologies Like Predictive Analytics to Drive Market Growth
11.3 Europe
11.3.1 Germany Germany is the Fastest-Growing Market for Healthcare Fraud Analytics Solutions in Europe
11.3.2 UK Launch of Initiatives Such as Nhscfa Will Support the Market for Fraud Analytics Solutions in the UK
11.3.3 France Increasing Adoption of Information Technology for the Detection of Healthcare Fraud—A Key Factor Driving Market Growth
11.3.4 Rest of Europe
11.4 Asia Pacific
11.4.1 APAC Market to Witness the Highest Growth in the Healthcare Fraud Analytics Market During the Forecast Period
11.5 Latin America
11.5.1 Volume of Claims Processing is Expected to Increase in Latin American Countries Owing to the Increasing Penetration of Health Insurance
11.6 Middle East & Africa
11.6.1 Healthcare Fraud is One of the Leading Crimes in South Africa

12 Competitive Landscape
12.1 Introduction
12.2 Competitive Situation and Trends
12.2.1 Mergers, Acquisitions, and Joint Ventures
12.2.2 Collaborations, Partnerships, and Agreements
12.2.3 Expansions
12.3 Competitive Leadership Mapping
12.3.1 Visionary Leaders
12.3.2 Innovators
12.3.3 Dynamic Differentiators
12.3.4 Emerging Companies

13 Company Profiles
(Business Overview, Products Offered, Recent Developments, MnM View)*
13.1 IBM
13.2 Optum (A Part of Unitedhealth Group)
13.3 Cotiviti Holdings, Inc.
13.4 Fair Isaac Corporation
13.5 SAS Institute
13.6 Change Healthcare
13.7 EXL Service Holdings, Inc.
13.8 Wipro
13.9 Conduent, Inc.
13.10 HCL Technologies
13.11 CGI Group
13.12 DXC Technology Company
13.13 Northrop Grumman Corporation
13.14 LexisNexis (A Part of Relx Group)
13.15 Pondera Solutions
13.16 Other Players Operating in the Healthcare Fraud Analytics Market
13.16.1 WhiteHatAI
13.16.2 Healthcare Fraud Shield
13.16.3 FraudLens, Inc.
13.16.4 HMS
13.16.5 FraudScope, Inc.

*Business Overview, Products Offered, Recent Developments, MnM View Might Not Be Captured in Case of Unlisted Companies.

14 Appendix
14.1 Discussion Guide
14.2 Knowledge Store: Marketsandmarkets’ Subscription Portal
14.3 Available Customizations
14.4 Related Reports
14.5 Author Details

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