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Healthcare Fraud Detection Market Research Report by Solution Type, Delivery Mode, Application, End User, State - Cumulative Impact of COVID-19, Russia Ukraine Conflict, and High Inflation - United States Forecast 2023-2030

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    Report

  • 159 Pages
  • January 2023
  • Region: United States
  • 360iResearch™
  • ID: 5722077
The United States Healthcare Fraud Detection Market is projected to grow with a significant CAGR in the forecast period. Economic development and substantial infrastructure development have constituted regional revenue generation. Further, the patterns associated with domestic production, import and export, and consumption have helped market participants to analyze and capitalize on potential opportunities. Besides, the qualitative and quantitative parameters provided in the report with detailed analysis highlights the driving and restraining factors of the United States Healthcare Fraud Detection Market.

Cumulative Impact of COVID-19:

COVID-19 is an unprecedented global public health emergency that affected almost every industry, and the long-term impacts are projected to reflect on the growth of various end-use industries during the forecast period. This ongoing research amplifies the research framework to ensure the inclusion of underlying COVID-19 issues and potential paths forward. The report delivers insights on COVID-19, considering the changes in consumer behavior and demand, purchasing patterns, re-routing of the supply chain, dynamics of current market forces, and the significant interventions of governments. The dedicated section in the report uncovers a detailed analysis of the impact of COVID-19 and its subsequent variant outbreaks on demand, supply, price, and vendor uptake and provides recommendations for sustainable outcomes. The updated study provides insights, analysis, estimations, and forecasts, considering the COVID-19 impact on the United States Healthcare Fraud Detection Market.

Cumulative Impact of Russia-Ukraine Conflict:

The publisher continuously monitors and update reports considering unceasing political and economic uncertainty due to the Russia-Ukraine Conflict. Negative impacts are globally foreseen, especially across Eastern Europe, European Union, Eastern & Central Asia, and the United States. This contention has severely affected people’s lives and livelihoods and represents far-reaching disruptions in trade dynamics. The potential effects of ongoing war and uncertainty in Eastern Europe are expected to have an adverse impact on Ukraine and reverberate harsh long-term effects on Russia. The report uncovers the implications for demand-supply balances, pressure on pricing variants, impact on import/export and trading, and short-term recommendations to the United States Healthcare Fraud Detection Market considering the current update on the conflict and its global responses.

Cumulative Impact of High Inflation:

The high inflation in developed economies globally has resulted in an overall price surge over the past two years. The cumulatively eroding overall purchasing power is expected to impact developing economies significantly and is considered helpful in numerous ways. The report uncovers the effect of high inflation on the long-term performance of the global economy and provides details on fiscal policies measuring and reducing its short-term impacts on demand/supply, cash flow, and currency exchange. The United States Healthcare Fraud Detection Market report delivers the high inflation expectation considering the related impact from cost-push and demand-pull inflation.

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 United States Healthcare Fraud Detection 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 your market plan. This research report categorizes the United States Healthcare Fraud Detection 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 Mode, the market is studied across On-Cloud and On-Premise.
  • Based on Application, the market is studied across Insurance Claims Review and Payment Integrity.
  • Based on End User, the market is studied across Government Agencies and Healthcare Payer.
  • Based on State, the market is studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas.

FPNV Positioning Matrix:

The FPNV Positioning Matrix evaluates and categorizes vendors in the United States Healthcare Fraud Detection 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 United States Healthcare Fraud Detection 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 United States Healthcare Fraud Detection 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 United States Healthcare Fraud Detection 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.

Company Usability Profiles:

The report profoundly explores the recent significant developments by the leading vendors and innovation profiles in the United States Healthcare Fraud Detection Market, including CGI Inc., Change Healthcare, Conduent Inc., Cotiviti Inc., DXC Technology Company, ExlService Holdings Inc., Fair Isaac Corporation, FraudLens Inc., H20.ai, HCL Technologies Limited, International Business Machines Corporation, Northrop Grumman Corporation, Optum Inc., OSP Labs, SAS Institute Inc., and Wipro Ltd..

The report provides insights on the following pointers:

1. Market Penetration: Provides comprehensive information on the market offered by the key players
2. Market Development: Provides in-depth information about lucrative emerging markets and analyzes penetration across mature segments of the markets
3. Market Diversification: Provides detailed information about new product launches, untapped geographies, recent developments, and investments
4. Market Trends: Provides comprehensive understanding of the Cumulative Impact of COVID-19, the Russia-Ukraine Conflict, and the High Inflation
5. Competitive Assessment & Intelligence: Provides an exhaustive assessment of market shares, strategies, products, certification, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players
6. Product Development & Innovation: Provides intelligent insights on future technologies, R&D activities, and breakthrough product developments

The report answers questions such as:

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

Table of Contents

1. Preface
1.1. Objectives of the Study
1.2. Market Segmentation & Coverage
1.3. Years Considered for the Study
1.4. Currency & Pricing
1.5. Language
1.6. Limitations
1.7. Assumptions
1.8. Stakeholders

2. Research Methodology
2.1. Define: Research Objective
2.2. Determine: Research Design
2.3. Prepare: Research Instrument
2.4. Collect: Data Source
2.5. Analyze: Data Interpretation
2.6. Formulate: Data Verification
2.7. Publish: Research Report
2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights
5.1. Market Dynamics
5.1.1. Drivers
5.1.1.1. Escalating fraudulent activities in the healthcare sector
5.1.1.2. Government involvement in reducing healthcare frauds in the U.S.
5.1.2. Restraints
5.1.2.1. Less adoption and knowledge about healthcare fraud detection systems
5.1.3. Opportunities
5.1.3.1. Integration of advanced technologies in healthcare fraud detection platforms
5.1.4. Challenges
5.1.4.1. Dearth of skilled and experienced workforce
5.2. Cumulative Impact of COVID-19
5.3. Cumulative Impact of Russia-Ukraine Conflict
5.4. Cumulative Impact of High Inflation
5.5. Porter’s Five Forces Analysis
5.5.1. Threat of New Entrants
5.5.2. Threat of Substitutes
5.5.3. Threat of Substitutes
5.5.4. Threat of Substitutes
5.5.5. Industry Rivalry
5.6. Value Chain & Critical Path Analysis
5.7. Regulatory Framework
5.8. Client Customization

6. Healthcare Fraud Detection Market, by Solution Type
6.1. Introduction
6.2. Descriptive Analytics
6.3. Predictive Analytics
6.4. Prescriptive Analytics

7. Healthcare Fraud Detection Market, by Delivery Mode
7.1. Introduction
7.2. On-Cloud
7.3. On-Premise

8. Healthcare Fraud Detection Market, by Application
8.1. Introduction
8.2. Insurance Claims Review
8.3. Payment Integrity

9. Healthcare Fraud Detection Market, by End User
9.1. Introduction
9.2. Government Agencies
9.3. Healthcare Payer

10. California Healthcare Fraud Detection Market
10.1. Introduction

11. Florida Healthcare Fraud Detection Market
11.1. Introduction

12. Illinois Healthcare Fraud Detection Market
12.1. Introduction

13. New York Healthcare Fraud Detection Market
13.1. Introduction

14. Ohio Healthcare Fraud Detection Market
14.1. Introduction

15. Pennsylvania Healthcare Fraud Detection Market
15.1. Introduction

16. Texas Healthcare Fraud Detection Market
16.1. Introduction

17. Competitive Landscape
17.1. FPNV Positioning Matrix
17.1.1. Quadrants
17.1.2. Business Strategy
17.1.3. Product Satisfaction
17.2. Market Ranking Analysis, By Key Player
17.3. Market Share Analysis, By Key Player
17.4. Product Portfolio Analysis, By Key Player
17.5. Competitive Scenario
17.5.1. Merger & Acquisition
17.5.2. Agreement, Collaboration, & Partnership
17.5.3. New Product Launch & Enhancement
17.5.4. Investment & Funding
17.5.5. Award, Recognition, & Expansion

18. Company Usability Profiles
18.1. CGI Inc.
18.2. Change Healthcare
18.3. Conduent Inc.
18.4. Cotiviti Inc.
18.5. DXC Technology Company
18.6. ExlService Holdings Inc.
18.7. Fair Isaac Corporation
18.8. FraudLens Inc.
18.9. H20.ai
18.10. HCL Technologies Limited
18.11. International Business Machines Corporation
18.12. Northrop Grumman Corporation
18.13. Optum Inc.
18.14. OSP Labs
18.15. SAS Institute Inc.
18.16. Wipro Ltd.

19. Appendix
19.1. Discussion Guide
19.2. License & Pricing

List of Figures
FIGURE 1. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET: RESEARCH PROCESS
FIGURE 2. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, 2022 VS 2030
FIGURE 3. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
FIGURE 4. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY STATE, 2022 VS 2030 (%)
FIGURE 5. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY STATE, 2022 VS 2023 VS 2030 (USD MILLION)
FIGURE 6. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET COMPETITIVE STRATEGIC WINDOW, BY STATE, 2030
FIGURE 7. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET DYNAMICS
FIGURE 8. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET PORTER’S FIVE FORCES ANALYSIS
FIGURE 9. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY SOLUTION TYPE, 2022 VS 2030 (%)
FIGURE 10. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY SOLUTION TYPE, 2022 VS 2023 VS 2030 (USD MILLION)
FIGURE 11. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET COMPETITIVE STRATEGIC WINDOW, BY SOLUTION TYPE, 2030
FIGURE 12. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DESCRIPTIVE ANALYTICS, 2018-2030 (USD MILLION)
FIGURE 13. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY PREDICTIVE ANALYTICS, 2018-2030 (USD MILLION)
FIGURE 14. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY PRESCRIPTIVE ANALYTICS, 2018-2030 (USD MILLION)
FIGURE 15. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DELIVERY MODE, 2022 VS 2030 (%)
FIGURE 16. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DELIVERY MODE, 2022 VS 2023 VS 2030 (USD MILLION)
FIGURE 17. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET COMPETITIVE STRATEGIC WINDOW, BY DELIVERY MODE, 2030
FIGURE 18. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY ON-CLOUD, 2018-2030 (USD MILLION)
FIGURE 19. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY ON-PREMISE, 2018-2030 (USD MILLION)
FIGURE 20. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY APPLICATION, 2022 VS 2030 (%)
FIGURE 21. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY APPLICATION, 2022 VS 2023 VS 2030 (USD MILLION)
FIGURE 22. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET COMPETITIVE STRATEGIC WINDOW, BY APPLICATION, 2030
FIGURE 23. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY INSURANCE CLAIMS REVIEW, 2018-2030 (USD MILLION)
FIGURE 24. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY PAYMENT INTEGRITY, 2018-2030 (USD MILLION)
FIGURE 25. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY END USER, 2022 VS 2030 (%)
FIGURE 26. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY END USER, 2022 VS 2023 VS 2030 (USD MILLION)
FIGURE 27. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET COMPETITIVE STRATEGIC WINDOW, BY END USER, 2030
FIGURE 28. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY GOVERNMENT AGENCIES, 2018-2030 (USD MILLION)
FIGURE 29. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY HEALTHCARE PAYER, 2018-2030 (USD MILLION)
FIGURE 30. CALIFORNIA HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
FIGURE 31. FLORIDA HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
FIGURE 32. ILLINOIS HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
FIGURE 33. NEW YORK HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
FIGURE 34. OHIO HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
FIGURE 35. PENNSYLVANIA HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
FIGURE 36. TEXAS HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
FIGURE 37. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET: FPNV POSITIONING MATRIX, 2022
FIGURE 38. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SHARE, BY KEY PLAYER, 2022
FIGURE 39. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET COMPETITIVE SCENARIO, BY KEY TYPE, 2022


List of Tables
TABLE 1. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SEGMENTATION & COVERAGE
TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2022
TABLE 3. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
TABLE 4. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY STATE, 2018-2030 (USD MILLION)
TABLE 5. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY SOLUTION TYPE, 2018-2030 (USD MILLION)
TABLE 6. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DESCRIPTIVE ANALYTICS, 2018-2030 (USD MILLION)
TABLE 7. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DESCRIPTIVE ANALYTICS, BY STATE, 2018-2030 (USD MILLION)
TABLE 8. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY PREDICTIVE ANALYTICS, 2018-2030 (USD MILLION)
TABLE 9. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY PREDICTIVE ANALYTICS, BY STATE, 2018-2030 (USD MILLION)
TABLE 10. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY PRESCRIPTIVE ANALYTICS, 2018-2030 (USD MILLION)
TABLE 11. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY PRESCRIPTIVE ANALYTICS, BY STATE, 2018-2030 (USD MILLION)
TABLE 12. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DELIVERY MODE, 2018-2030 (USD MILLION)
TABLE 13. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY ON-CLOUD, 2018-2030 (USD MILLION)
TABLE 14. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY ON-CLOUD, BY STATE, 2018-2030 (USD MILLION)
TABLE 15. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY ON-PREMISE, 2018-2030 (USD MILLION)
TABLE 16. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY ON-PREMISE, BY STATE, 2018-2030 (USD MILLION)
TABLE 17. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 18. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY INSURANCE CLAIMS REVIEW, 2018-2030 (USD MILLION)
TABLE 19. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY INSURANCE CLAIMS REVIEW, BY STATE, 2018-2030 (USD MILLION)
TABLE 20. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY PAYMENT INTEGRITY, 2018-2030 (USD MILLION)
TABLE 21. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY PAYMENT INTEGRITY, BY STATE, 2018-2030 (USD MILLION)
TABLE 22. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
TABLE 23. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY GOVERNMENT AGENCIES, 2018-2030 (USD MILLION)
TABLE 24. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY GOVERNMENT AGENCIES, BY STATE, 2018-2030 (USD MILLION)
TABLE 25. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY HEALTHCARE PAYER, 2018-2030 (USD MILLION)
TABLE 26. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SIZE, BY HEALTHCARE PAYER, BY STATE, 2018-2030 (USD MILLION)
TABLE 27. CALIFORNIA HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
TABLE 28. CALIFORNIA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY SOLUTION TYPE, 2018-2030 (USD MILLION)
TABLE 29. CALIFORNIA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DELIVERY MODE, 2018-2030 (USD MILLION)
TABLE 30. CALIFORNIA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 31. CALIFORNIA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
TABLE 32. FLORIDA HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
TABLE 33. FLORIDA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY SOLUTION TYPE, 2018-2030 (USD MILLION)
TABLE 34. FLORIDA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DELIVERY MODE, 2018-2030 (USD MILLION)
TABLE 35. FLORIDA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 36. FLORIDA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
TABLE 37. ILLINOIS HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
TABLE 38. ILLINOIS HEALTHCARE FRAUD DETECTION MARKET SIZE, BY SOLUTION TYPE, 2018-2030 (USD MILLION)
TABLE 39. ILLINOIS HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DELIVERY MODE, 2018-2030 (USD MILLION)
TABLE 40. ILLINOIS HEALTHCARE FRAUD DETECTION MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 41. ILLINOIS HEALTHCARE FRAUD DETECTION MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
TABLE 42. NEW YORK HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
TABLE 43. NEW YORK HEALTHCARE FRAUD DETECTION MARKET SIZE, BY SOLUTION TYPE, 2018-2030 (USD MILLION)
TABLE 44. NEW YORK HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DELIVERY MODE, 2018-2030 (USD MILLION)
TABLE 45. NEW YORK HEALTHCARE FRAUD DETECTION MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 46. NEW YORK HEALTHCARE FRAUD DETECTION MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
TABLE 47. OHIO HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
TABLE 48. OHIO HEALTHCARE FRAUD DETECTION MARKET SIZE, BY SOLUTION TYPE, 2018-2030 (USD MILLION)
TABLE 49. OHIO HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DELIVERY MODE, 2018-2030 (USD MILLION)
TABLE 50. OHIO HEALTHCARE FRAUD DETECTION MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 51. OHIO HEALTHCARE FRAUD DETECTION MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
TABLE 52. PENNSYLVANIA HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
TABLE 53. PENNSYLVANIA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY SOLUTION TYPE, 2018-2030 (USD MILLION)
TABLE 54. PENNSYLVANIA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DELIVERY MODE, 2018-2030 (USD MILLION)
TABLE 55. PENNSYLVANIA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 56. PENNSYLVANIA HEALTHCARE FRAUD DETECTION MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
TABLE 57. TEXAS HEALTHCARE FRAUD DETECTION MARKET SIZE, 2018-2030 (USD MILLION)
TABLE 58. TEXAS HEALTHCARE FRAUD DETECTION MARKET SIZE, BY SOLUTION TYPE, 2018-2030 (USD MILLION)
TABLE 59. TEXAS HEALTHCARE FRAUD DETECTION MARKET SIZE, BY DELIVERY MODE, 2018-2030 (USD MILLION)
TABLE 60. TEXAS HEALTHCARE FRAUD DETECTION MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
TABLE 61. TEXAS HEALTHCARE FRAUD DETECTION MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
TABLE 62. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET: FPNV POSITIONING MATRIX - SCORES, 2022
TABLE 63. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET: FPNV POSITIONING MATRIX - BUSINESS STRATEGY, 2022
TABLE 64. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET: FPNV POSITIONING MATRIX - PRODUCT SATISFACTION, 2022
TABLE 65. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET RANKING, BY KEY PLAYER, 2022
TABLE 66. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET SHARE, BY KEY PLAYER, 2022
TABLE 67. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET PRODUCT PORTFOLIO ANALYSIS, BY KEY PLAYER, 2022
TABLE 68. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET MERGER & ACQUISITION
TABLE 69. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET AGREEMENT, COLLABORATION, & PARTNERSHIP
TABLE 70. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET NEW PRODUCT LAUNCH & ENHANCEMENT
TABLE 71. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET INVESTMENT & FUNDING
TABLE 72. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET AWARD, RECOGNITION, & EXPANSION
TABLE 73. UNITED STATES HEALTHCARE FRAUD DETECTION MARKET: LICENSE & PRICING

Companies Mentioned

  • CGI Inc.
  • Change Healthcare
  • Conduent Inc.
  • Cotiviti Inc.
  • DXC Technology Company
  • ExlService Holdings Inc.
  • Fair Isaac Corporation
  • FraudLens Inc.
  • H20.ai
  • HCL Technologies Limited
  • International Business Machines Corporation
  • Northrop Grumman Corporation
  • Optum Inc.
  • OSP Labs
  • SAS Institute Inc.
  • Wipro Ltd.

Methodology

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