Healthcare Fraud Analytics Global Market Report 2023: Introduction of Healthcare BPO and Fraud Identity Management Software Presents Opportunities


Dublin, April 06, 2023 (GLOBE NEWSWIRE) -- The "Healthcare Fraud Analytics Market Research Report by Solution Type (Descriptive Analytics, Predictive Analytics, Prescriptive Analytics), Delivery Model (On-Demand, On-Premise), Application, End-User - Global Forecast 2023-2030" report has been added to ResearchAndMarkets.com's offering.

The Global Healthcare Fraud Analytics Market size was estimated at USD 5,769.60 million in 2022, USD 6,848.23 million in 2023, and is projected to grow at a CAGR of 19.17% to reach USD 23,475.69 million by 2030.

Market Dynamics

Drivers

  • Increasing Number of Fraudulent Activities in the Healthcare Sector
  • Growing Adoption of Health Insurance Plans Across the Globe
  • Surge in Discipline to Keep Trace of Fraud & Abuse in Health Care Domain

Restraints

  • High Cost of Healthcare Fraud Analytics Services

Opportunities

  • Introduction of Healthcare BPO and Fraud Identity Management Software
  • Proliferation of Social Media Platforms and Their Impact on Healthcare
  • Integration of Ai in Healthcare Services and Solutions

Challenges

  • Issues Related to Data Management

Market Statistics:

The report provides market sizing and forecasts across 7 major currencies - USD, EUR, JPY, GBP, AUD, CAD, and CHF; multiple currency support helps organization leaders to make better decisions. In this report, the years 2018 and 2021 are considered as historical years, 2022 as the base year, 2023 as the estimated year, and years from 2024 to 2030 are considered as the forecast period.

Market Segmentation & Coverage:

The report on the Global Healthcare Fraud Analytics Market identifies key attributes about the customer to define the potential market and identify different needs across the industry. Understanding the potential customer group's economies and geographies can help gain business acumen for better strategic decision-making. The market coverage across different industry verticals reveals the hidden truth about the players' strategies in different verticals and helps the organization decide target audience. This report gives you the composite view of sub-markets coupled with comprehensive industry coverage and provides you with the right way of accounting factors such as norms & regulations, culture, to make right coverage strategy for the market plan. This research report categorizes the Global Healthcare Fraud Analytics Market in order to forecast the revenues and analyze the trends in each of the following sub-markets:

  • Based on Solution Type, the market is studied across Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics.
  • Based on Delivery Model, the market is studied across On-Demand and On-Premise.
  • Based on Application, the market is studied across Insurance Claims Review, Payment Integrity, and Pharmacy Billing Misuse. The Insurance Claims Review is is further studied across Post payment Review and Prepayment Review.
  • Based on End-User, the market is studied across Employers, Private Insurance Payers, Public & Government Agencies, and Third-party service providers.
  • Based on Region, the market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

FPNV Positioning Matrix:

The FPNV Positioning Matrix evaluates and categorizes vendors in the Global Healthcare Fraud Analytics Market. based on Business Strategy (Business Growth, Industry Coverage, Financial Viability, and Channel Support) and Product Satisfaction (Value for Money, Ease of Use, Product Features, and Customer Support) and placed into four quadrants (F: Forefront, P: Pathfinder, N: Niche, and V: Vital). The Global Healthcare Fraud Analytics Market FPNV Positioning Matrix representation/visualization further aids businesses in better decision-making and understanding the competitive landscape.

Market Share Analysis:

The Market Share Analysis offers the analysis of vendors considering their contribution to the overall market, providing the idea of revenue generation into the overall market compared to other vendors in the space. This provides insights on vendors performance in terms of revenue generation and customer base compared to others. The Global Healthcare Fraud Analytics Market Share Analysis offers an idea of the size and competitiveness of the vendors for the base year. The outcome reveals the market characteristics in terms of accumulation, fragmentation, dominance, and amalgamation traits.

Competitive Scenario:

The Competitive Scenario provides an outlook analysis of the various strategies for business growth adopted by the vendors. The news in this section covers valuable insights at various stages while keeping up with the business and engaging stakeholders in the economic debate. The Global Healthcare Fraud Analytics Market Competitive Scenario represents press releases or news of the companies categorized into Merger & Acquisition, Agreement, Collaboration, & Partnership, New Product Launch & Enhancement, Investment & Funding, and Award, Recognition, & Expansion. All the news collected helps vendors understand the gaps in the marketplace and competitor's strengths and weaknesses, providing insights to enhance products and services.

The report answers questions such as:

1. What is the market size and forecast of the Global Healthcare Fraud Analytics Market?
2. What are the inhibiting factors and impact of COVID-19 shaping the Global Healthcare Fraud Analytics Market during the forecast period?
3. Which are the products/segments/applications/areas to invest in over the forecast period in the Global Healthcare Fraud Analytics Market?
4. What is the competitive strategic window for opportunities in the Global Healthcare Fraud Analytics Market?
5. What are the technology trends and regulatory frameworks in the Global Healthcare Fraud Analytics Market?
6. What is the market share of the leading vendors in the Global Healthcare Fraud Analytics Market?
7. What modes and strategic moves are considered suitable for entering the Global Healthcare Fraud Analytics Market?

Key Attributes:

Report AttributeDetails
No. of Pages222
Forecast Period2022 - 2030
Estimated Market Value (USD) in 2022$5769.6 Million
Forecasted Market Value (USD) by 2030$23475.69 Million
Compound Annual Growth Rate19.1%
Regions CoveredGlobal

Key Topics Covered:

1. Preface

2. Research Methodology

3. Executive Summary

4. Market Overview

5. Market Insights

6. Healthcare Fraud Analytics Market, by Solution Type

7. Healthcare Fraud Analytics Market, by Delivery Model

8. Healthcare Fraud Analytics Market, by Application

9. Healthcare Fraud Analytics Market, by End-User

10. Americas Healthcare Fraud Analytics Market

11. Asia-Pacific Healthcare Fraud Analytics Market

12. Europe, Middle East & Africa Healthcare Fraud Analytics Market

13. Competitive Landscape

14. Company Usability Profiles

15. Appendix

Companies Mentioned

  • CGI Inc.
  • Change Healthcare Inc.
  • Conduent, Inc.
  • Coviti, Inc.
  • ExlService Holdings, Inc.
  • Fair Isaac Corporation
  • FraudLens Inc.
  • HCL Technologies Ltd.
  • International Business Machines Corporation
  • Northrop Grumman Corporation
  • Optum, Inc.
  • OSP Labs
  • Qlarant Inc.
  • SAS Institute, Inc.
  • Wipro Limited

For more information about this report visit https://www.researchandmarkets.com/r/sfcu71

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Global Healthcare Fraud Analytics Market

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