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Healthcare Fraud Analytics Market Size, Share & Trends Analysis Report by Solution Type (Descriptive, Predictive, Prescriptive), by Delivery Model, by Application, by End User, by Region, and Segment Forecasts, 2022-2030

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    Report

  • 150 Pages
  • April 2022
  • Region: Global
  • Grand View Research
  • ID: 5595795
The global healthcare fraud analytics market size is expected to reach USD 11.2 billion by 2030. The market is projected to advance at a CAGR of 24.3% from 2022 to 2030. The rising incidence of fraudulent activities in the healthcare sector, increasing number of patients seeking health insurance, high returns on investment, and the increasing number of pharmacy claims-related frauds are the major drivers propelling the market growth.



The COVID-19 pandemic has drastically affected the healthcare industry. The healthcare industry has observed various fraud cases on the part of doctors, patients, physicians, and other healthcare specialists. It is observed that many medical specialists and healthcare providers are engaged in fraudulent activities for profit gains. Many instances prove the increasing number of fraud cases during the COVID-19 pandemic.

The adoption of software used for fraud detection by insurance companies is increasing due to the rising availability of the same in developed regions. For instance, in February 2022, The Canadian Life and Health Insurance Association (CLHIA) launched an industry initiative to pool claims data and use advanced artificial intelligence tools which enhance the investigation and detection of benefits fraud.

Moreover, in June 2021, Artivatic launched the Alfred- AI Health Claims platform. This platform automates end-to-end health claims, and the abuse & fraud detection capacity is almost 30% or more. Moreover, it enables users to self-learn and develop a system for decision-making, risk assessment, and fraud detection. This growth in the availability of the software is because of increasing healthcare expenditure, which triggers the companies to come up with a product or service to meet the market demand.

The rising incidence of fraudulent activities in the healthcare sector drives the market globally. For example, according to data published by the National Library of Medicine, the fraudulent activities count raised from 30 in 2019 to 52 in the year 2021. The market is highly competitive and consists of several major players. With the rising adoption of healthcare IT solutions and the increasing number of fraud cases, smaller or private players are anticipated to enter the market in the coming years.

Initiatives like collaborations or partnerships with local players, acquisitions, or new product launches by market players contribute to the market growth. For example, in April 2019, HCL Technologies Limited launched the CyberSecurity Fusion Center in Texas, U.S., and expanded its U.S. operations with the CyberSecurity Center.

Healthcare Fraud Analytics Market Report Highlights

  • In terms of revenue, the descriptive analytics segment dominated the solution type segment with a share of around 40.5% in 2021, owing to its high penetration.
  • Based on the delivery model, the on-premise segment is expected to show lucrative growth during the forecast period, owing to its higher deployment as compared to the cloud-based delivery model.
  • Insurance claims review dominated the application segment with a share of around 35% as of 2021. The growth can be attributed to the rising adoption of health insurance.
  • The employers' segment is expected to show the fastest growth during the forecast period, owing to the increasing demand for healthcare fraud analytics software by employers for better cost management.
  • The North American region accounted for the largest market share of around 38% in 2021, owing to the presence of major market players in the region .

Table of Contents

Chapter 1 Methodology and Scope
1.1 Market Segmentation and Scope
1.1.1 Segment scope
1.1.2 Regional scope
1.1.3 Estimates and forecast timeline
1.2 Research Methodology
1.3 Information procurement
1.3.1 Purchased database
1.3.2 internal database
1.3.3 Secondary sources
1.3.4 Primary research
1.3.5 Details of primary research
1.4 Information or Data Analysis
1.4.1 Data analysis models
1.5 Market Formulation & Validation
1.6 Model Details
1.7 List of Secondary Sources
1.8 Objectives
Chapter 2 Executive Summary
2.1 Healthcare Fraud Analytics Market Summary
Chapter 3 Healthcare Fraud Analytics Market Variables, Trends & Scope
3.1 Market Lineage Outlook
3.1.1. Parent Market Outlook
3.1.2. Related/Ancillary Market Outlook
3.2. Penetration & Growth Prospect Mapping, 2021
3.3 Healthcare Fraud Analytics Market Dynamics
3.3.1 Market driver analysis
3.3.2 Market restraint analysis
3.3.3. Market opportunity analysis
3.3.4. Market challenge analysis
3.4 Healthcare Fraud Analytics Market Analysis Tools: Porter’s Five Forces
3.4.1 Supplier Power
3.4.2. Buyer Power
3.4.3. Substitution Threat
3.4.4. Threat of New Entrants
3.4.5. Competitive Rivalry
3.5 Healthcare Fraud Analytics Industry Analysis-PEST (Political & Legal, Economic, Social, and Technological)
3.5.1 Political/Legal Landscape
3.5.2 Economic Landscape
3.5.3 Social Landscape
3.5.4 Technology Landscape
3.6. Regulatory Overview
Chapter 4 COVID-19 Impact Analysis
4.1 COVID-19 Prevalence Analysis
4.2. Current and Future Impact Analysis
4.3. Impact of COVID-19 on Market Players
Chapter 5 Healthcare Fraud Analytics Market: Segment Analysis, by Solution Type, 2017-2030 (USD Million)
5.1 Solution Type Market Share Analysis, 2021 & 2030
5.2 Healthcare Fraud Analytics market, by Solution Type, 2017 to 2030
5.3 Descriptive Analytics
5.3.1 Descriptive Analytics market, 2017-2030 (USD Million)
5.4 Prescriptive Analytics
5.4.1 Prescriptive Analytics market, 2017-2030 (USD Million)
5.5 Predictive Analytics
5.5.1 Predictive Analytics market, 2017-2030 (USD Million)
Chapter 6 Healthcare Fraud Analytics Market: Segment Analysis, by Application, 2017-2030 (USD Million)
6.1 Application Market Share Analysis, 2021 & 2030
6.2 Healthcare Fraud Analytics market, by Application, 2017 to 2030
6.3 Insurance Claims Review
6.3.1 Insurance Claims Review market, 2017-2030 (USD Million)
6.3.2 Postpayment Review
6.3.2.1 Postpayment Review market, 2017-2030 (USD Million)
6.3.3 Prepayment Review
6.3.3.1 Prepayment Review market, 2017-2030 (USD Million)
6.4 Pharmacy Billing Issue
6.4.1 Pharmacy Billing Issue market, 2017-2030 (USD Million)
6.5 Payment Integrity
6.5.1 Payment Integrity market, 2017-2030 (USD Million)
6.6 Others
6.6.1 Others market, 2017-2030 (USD Million)
Chapter 7 Healthcare Fraud Analytics Market: Segment Analysis, by Delivery Model, 2017-2030 (USD Million)
7.1 Delivery Model Market Share Analysis, 2021 & 2030
7.2 Healthcare Fraud Analytics Market, by delivery model, 2017 to 2030
7.3 On-Premises
7.3.1 On-Premises market, 2017-2030 (USD Million)
7.4 Cloud-Based
7.4.1 Cloud-Based market, 2017-2030 (USD Million)
Chapter 8 Healthcare Fraud Analytics Market: Segment Analysis, by End User, 2017-2030 (USD Million)
8.1 End User Market Share Analysis, 2021 & 2030
8.2 Healthcare Fraud Analytics Market, by End User, 2017 to 2030
8.3 Public & Government Agencies
8.3.1 Public & Government Agencies market, 2017-2030 (USD Million)
8.4 Private Insurance Payers
8.4.1 Private Insurance Payers market, 2017-2030 (USD million)
8.5 Third Party Service Providers
8.5.1 Third Party Service Providers market, 2017-2030 (USD Million)
8.6 Employers
8.6.1 Employers market, 2017-2030 (USD Million)
Chapter 9 Healthcare Fraud Analytics Market: Regional Market Analysis 2017-2030 (USD Million)
9.1 Definition & Scope
9.2 Regional Movement Analysis, 2021 & 2030
9.3 Regional Market Snapshot
9.4 North America
9.4.1 North America Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.4.2. U.S.
9.4.2.1 U.S. Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.4.3 Canada
9.4.3.1 Canada Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.5 Europe
9.5.1 Europe Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.5.2 U.K.
9.5.2.1 U.K. Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.5.3 Germany
9.5.3.1 Germany Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.5.4 France
9.5.4.1 France Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.5.5 Italy
9.5.5.1 Italy Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.5.6 Spain
9.5.6.1 Spain Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.6 Asia Pacific
9.6.1 Asia Pacific Healthcare Fraud Analytics market, 2017-2030 (USD Million)
9.6.2 Japan
9.6.2.1 Japan Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.6.3 China
9.6.3.1 China Healthcare Fraud Analytics Market, 2017-2030 (USD million)
9.6.4 India
9.6.4.1 India Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.6.5 Australia
9.6.5.1 Australia Healthcare Fraud Analytics Market, 2017-2030 (USD million)
9.6.6 South Korea
9.6.6.1 South Korea Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.7 Latin America
9.7.1 Latin America Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.7.2 Brazil
9.7.2.1 Brazil Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.7.3 Mexico
9.7.3.1 Mexico Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.7.4 Argentina
9.7.4.1 Argentina Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.8 MEA
9.8.1 MEA Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.8.2 South Africa
9.8.2.1 South Africa Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.8.3 Saudi Arabia
9.8.3.1 Saudi Arabia Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
9.8.4 UAE
9.8.4.1 UAE Healthcare Fraud Analytics Market, 2017-2030 (USD Million)
Chapter 10 Healthcare Fraud Analytics Market-Competitive Analysis
10.1 Market Participant Categorization
10.2 Company Dashboard Analysis
10.3 Public Companies
10.3.1. Company Market Position Analysis
10.3.2. Synergy Analysis: Major Deals & Strategic Alliances
10.4. Detailed List of Market Players
Chapter 11 Healthcare Fraud Analytics Market-Company Profiles
11.1 IBM
11.1.1 Company overview
11.1.2 FINANCIAL PERFORMANCE
11.1.3 Product benchmarking
11.1.4 Strategic initiatives
11.2 Optum Inc.
11.2.1 Company overview
11.2.2 Financial performance
11.2.3 Product benchmarking
11.2.4 Strategic initiatives
11.3 Cotiviti Inc.
11.3.1 Company overview
11.3.2 Financial performance
11.3.3 Product benchmarking
11.3.4 Strategic initiatives
11.4 DXC Technology
11.4.1 Company overview
11.4.2 Financial performance
11.4.3 Product benchmarking
11.4.4 Strategic initiatives
11.5 SAS Institute Inc.
11.5.1 Company overview
11.5.2 Financial performance
11.5.3 Product benchmarking
11.5.4 Strategic initiatives
11.6 Exlservice Holdings, Inc.
11.6.1 Company overview
11.6.2 Financial performance
11.6.3 Product benchmarking
11.6.4 Strategic initiatives
11.7 Wipro Limited
11.7.1 Company overview
11.7.2 Financial performance
11.7.3 Product benchmarking
11.7.4 Strategic initiatives
11.8 Conduent Inc.
11.8.1 Company overview
11.8.2 Financial performance
11.8.3 Product benchmarking
11.8.4 Strategic initiatives
11.9 HCL Technologies Limited
11.9.1 Company overview
11.9.2 Financial performance
11.9.3 Product benchmarking
11.9.4 Strategic initiatives
11.10 OSP Labs
11.10.1 Company overview
11.10.2 Financial performance
11.10.3 Product benchmarking
11.10.4 Strategic initiatives

Companies Mentioned

  • Ibm
  • Optum Inc.
  • Cotiviti Inc.
  • Dxc Technology
  • Sas Institute Inc.
  • Exlservice Holdings, Inc.
  • Wipro Limited
  • Conduent Inc.
  • Hcl Technologies Limited
  • Osp Labs

Methodology

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Table Information