表紙:医療業界向け不正アナリティクスの世界市場 - COVID-19の影響、2026年までの予測:ソリューションタイプ別 (記述的、予測的、処方的)、用途別 (保険請求、支払整合性)、提供モデル別、エンドユーザー別
市場調査レポート
商品コード
1033052

医療業界向け不正アナリティクスの世界市場 - COVID-19の影響、2026年までの予測:ソリューションタイプ別 (記述的、予測的、処方的)、用途別 (保険請求、支払整合性)、提供モデル別、エンドユーザー別

Healthcare Fraud Analytics Market by Solution Type (Descriptive, Predictive, Prescriptive), Application (Insurance Claim, Payment Integrity), Delivery(On-premise, Cloud), End User(Government, Employers, Payers), COVID-19 Impact - Global Forecast -2026

出版日: | 発行: MarketsandMarkets | ページ情報: 英文 173 Pages | 納期: 即納可能 即納可能とは

価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=115.72円
医療業界向け不正アナリティクスの世界市場 - COVID-19の影響、2026年までの予測:ソリューションタイプ別 (記述的、予測的、処方的)、用途別 (保険請求、支払整合性)、提供モデル別、エンドユーザー別
出版日: 2021年10月15日
発行: MarketsandMarkets
ページ情報: 英文 173 Pages
納期: 即納可能 即納可能とは
  • 全表示
  • 概要
  • 目次
概要

世界の医療業界向け不正アナリティクスの市場規模は、2021年の15億米ドルから、2026年までに50億米ドルに達し、予測期間中のCAGRで26.7%の成長が予測されています。

市場の成長は、医療における多数の不正行為、健康保険を求める患者数の増加、高い投資収益率、薬局請求に関連する不正の増加などに起因しています。しかし、熟練した人材が少ないことが、この市場の成長を抑制すると予想されます。

当レポートでは、世界の医療業界向け不正アナリティクス市場について調査分析し、市場概要、業界動向、地域別の動向、主要企業などについて、体系的な情報を提供しています。

目次

第1章 イントロダクション

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 重要考察

第5章 市場概要

  • 市場力学
    • 促進要因
    • 抑制要因
    • 機会
    • 課題

第6章 業界考察

  • 業界動向

第7章 医療業界向け不正アナリティクス市場:ソリューションタイプ別

  • 記述的アナリティクス
  • 予測的アナリティクス
  • 処方的アナリティクス

第8章 医療業界向け不正アナリティクス市場:提供モデル別

  • オンプレミス
  • オンデマンド

第9章 医療業界向け不正アナリティクス市場:用途別

  • 保険請求のレビュー
  • 薬局請求の誤用
  • 支払整合性
  • その他

第10章 医療業界向け不正アナリティクス市場:エンドユーザー別

  • 公的機関・政府機関
  • 民間保険企業
  • サードパーティのサービスプロバイダー
  • 雇用主

第11章 医療業界向け不正アナリティクス市場:地域別

  • 北米
    • 米国
    • カナダ
  • 欧州
    • ドイツ
    • 英国
    • フランス
    • イタリア
    • スペイン
    • その他の欧州
  • アジア
    • 日本
    • 中国
    • その他のアジア
  • 太平洋地域
  • ラテンアメリカ
  • 中東・アフリカ

第12章 競合情勢

  • 競合状況と動向
  • 競合リーダーシップマッピング

第13章 企業プロファイル

  • 主要企業
    • IBM CORPORATION
    • OPTUM, INC. (A PART OF UNITEDHEALTH GROUP)
    • COTIVITI, INC.
    • FAIR ISAAC CORPORATION
    • SAS INSTITUTE INC.
    • CHANGE HEALTHCARE
    • PONDERA SOLUTIONS, INC. (A SUBSIDIARY OF THOMSON REUTERS CORPORATION)
    • EXLSERVICE HOLDINGS, INC.
    • WIPRO LIMITED
    • CONDUENT INCORPORATED
    • HCL TECHNOLOGIES LIMITED
    • CGI INC.
    • DXC TECHNOLOGY
    • NORTHROP GRUMMAN CORPORATION
    • LEXISNEXIS (A PART OF RELX GROUP)
    • QLARANT, INC.
    • H2O.AI
    • MULTIPLAN
    • FRISS
    • OSP LABS
  • その他の企業
    • SHARECARE, INC. (A SUBSIDIARY OF FALCON CAPITAL ACQUISITION CORP.)
    • HEALTHCARE FRAUD SHIELD
    • FRAUDLENS, INC.
    • HMS HOLDINGS CORP.
    • CODOXO

第14章 付録

目次
Product Code: HIT 5868

The global healthcare fraud analytics market is projected to reach USD 5.0 billion by 2026 from USD 1.5 billion in 2021, at a CAGR of 26.7% during the forecast period. Market growth can be attributed to a large number of fraudulent activities in healthcare, increasing number of patients seeking health insurance, high returns on investment, and the rising number of pharmacy claims-related frauds. However, the dearth of skilled personnel is expected to restrain the growth of this market.

The on-demand segment is expected to grow at the highest CAGR 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 segment 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 postpayment 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.

North America accounted for the largest share of the healthcare fraud analytics market

The healthcare fraud analytics market is segmented into five major regions, namely, North America, Europe, Asia, Pacific, Latin America, and the Middle East & Africa. North America accounted for the largest share of this market in 2020 majorly due to the high penetration of health insurance in the region, high number of healthcare fraud cases, favorable government initiatives to combat healthcare fraud, and wider product and service availability in this region. Moreover, a majority of leading players in the healthcare fraud analytics market have their headquarters in North America

Break of primary participants was as 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%, Europe-22%, Asia-13%, Latin America- 3%, Middle East and Africa-2%

Key players in the Healthcare Fraud Analytics market

Major players in this market include IBM Corporation (US), Optum, Inc. (US), Cotiviti, Inc. (US), Change Healthcare (US), Fair Isaac Corporation (US), SAS Institute Inc. (US), EXLService Holdings, Inc. (US), Wipro Limited (India), Conduent, Incorporated (US), CGI Inc. (Canada), HCL Technologies Limited (India), Qlarant, Inc. (US), DXC Technology (US), Northrop Grumman Corporation (US), LexisNexis (US), Healthcare Fraud Shield (US), Sharecare, Inc. (US), FraudLens, Inc. (US), HMS Holding Corp. (US), Codoxo (US), H20.ai (US), Pondera Solutions, Inc. (US), FRISS (The Netherlands), Multiplan (US), FraudScope (US), and OSP Labs (US).

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 segments such as solution type, application, delivery model, end user, and region. The report also includes a product portfolio matrix of various healthcare fraud analytic solutions available in the market. The report also provides a competitive analysis of the key players in this market, along with their company profiles, product & service offerings, 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, which in turn would help them, garner a more significant 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 product portfolios offered by the top players in the global healthcare fraud analytics market. The report analyzes this market by solution type, application, delivery model, and end user
  • Solution Enhancement/Innovation: Detailed insights on upcoming trends and solution launches in the global healthcare fraud analytics market
  • Market Development: Comprehensive information on the lucrative emerging markets by products and services, and end user
  • Market Diversification: Exhaustive information about new solutions or service enhancements, growing geographies, recent developments, and investments in the global healthcare fraud analytics market
  • Competitive Assessment: In-depth assessment of market shares, growth strategies, solution offerings, competitive leadership mapping, and capabilities of leading players in the global healthcare fraud analytics market.

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 OBJECTIVES OF THE STUDY
  • 1.2 MARKET DEFINITION & SCOPE
    • 1.2.1 INCLUSIONS & EXCLUSIONS OF THE STUDY
    • 1.2.2 MARKET SEGMENTATION
    • FIGURE 1 HEALTHCARE FRAUD ANALYTICS MARKET SEGMENTATION
    • 1.2.3 YEARS CONSIDERED FOR THE STUDY
  • 1.3 CURRENCY
    • TABLE 1 EXCHANGE RATES UTILIZED FOR CONVERSION TO USD
  • 1.4 LIMITATIONS
  • 1.5 STAKEHOLDERS

2 RESEARCH METHODOLOGY

  • 2.1 RESEARCH APPROACH
    • FIGURE 2 RESEARCH DESIGN
    • 2.1.1 SECONDARY SOURCES
      • 2.1.1.1 Key data from secondary sources
    • 2.1.2 PRIMARY SOURCES
    • TABLE 2 LIST OF STAKEHOLDERS INTERVIEWED FOR THE STUDY
      • 2.1.2.1 Key data from primary sources
    • FIGURE 3 BREAKDOWN OF PRIMARY INTERVIEWS: BY COMPANY TYPE, DESIGNATION, AND REGION
  • 2.2 MARKET SIZE ESTIMATION
  • 2.3 MARKET BREAKDOWN AND DATA TRIANGULATION
    • FIGURE 4 DATA TRIANGULATION METHODOLOGY
  • 2.4 ASSUMPTIONS FOR THE STUDY

3 EXECUTIVE SUMMARY

    • FIGURE 5 HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2021 VS. 2026 (USD MILLION)
    • FIGURE 6 HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2021 VS. 2026 (USD MILLION)
    • FIGURE 7 HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2021 VS. 2026 (USD MILLION)
    • FIGURE 8 HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2021 VS. 2026 (USD MILLION)
    • FIGURE 9 GEOGRAPHICAL SNAPSHOT OF THE HEALTHCARE FRAUD ANALYTICS MARKET

4 PREMIUM INSIGHTS

  • 4.1 HEALTHCARE FRAUD ANALYTICS MARKET OVERVIEW
    • FIGURE 10 LARGE NUMBER OF FRAUDULENT ACTIVITIES IN HEALTHCARE TO DRIVE MARKET GROWTH
  • 4.2 ASIA: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE AND COUNTRY
    • FIGURE 11 DESCRIPTIVE ANALYTICS SEGMENT ACCOUNTED FOR THE LARGEST SHARE OF THE ASIAN HEALTHCARE FRAUD ANALYTICS MARKET IN 2020
  • 4.3 HEALTHCARE FRAUD ANALYTICS MARKET: GEOGRAPHIC GROWTH OPPORTUNITIES
    • FIGURE 12 US TO REGISTER THE HIGHEST REVENUE GROWTH DURING FORECAST PERIOD
  • 4.4 HEALTHCARE FRAUD ANALYTICS MARKET: REGIONAL MIX
    • FIGURE 13 NORTH AMERICA WILL CONTINUE TO DOMINATE THE MARKET IN 2026
  • 4.5 HEALTHCARE FRAUD ANALYTICS MARKET: DEVELOPING VS. DEVELOPED REGIONS
    • FIGURE 14 DEVELOPED MARKETS TO REGISTER HIGHER GROWTH DURING FORECAST PERIOD

5 MARKET OVERVIEW

  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
    • FIGURE 15 HEALTHCARE FRAUD ANALYTICS MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
    • 5.2.1 DRIVERS
      • 5.2.1.1 Large number of fraudulent activities in healthcare
    • FIGURE 16 US NATIONAL HEALTHCARE FRAUD AND OPIOID TAKEDOWN TRENDS
    • FIGURE 17 INCIDENCE OF FRAUDULENT CLAIMS-GLOBAL SCENARIO (2019)
      • 5.2.1.2 Increased number of patients seeking health insurance
      • 5.2.1.3 Prepayment review model
      • 5.2.1.4 High returns on investment
      • 5.2.1.5 Rise in pharmacy claims-related fraud
    • 5.2.2 RESTRAINTS
      • 5.2.2.1 Limitations in the data capturing process in Medicaid services
    • 5.2.3 OPPORTUNITIES
      • 5.2.3.1 Adoption of healthcare fraud analytics in developing countries
      • 5.2.3.2 Emergence of social media and its impact on the healthcare industry
      • 5.2.3.3 Role of AI in healthcare fraud detection
    • 5.2.4 CHALLENGES
      • 5.2.4.1 Dearth of skilled personnel
      • 5.2.4.2 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
    • FIGURE 18 MAJOR MERGERS AND ACQUISITIONS IN THE HEALTHCARE FRAUD ANALYTICS MARKET
    • 6.1.3 TECHNOLOGICAL ADVANCEMENTS
    • TABLE 3 COMPANIES OFFERING INNOVATIVE FRAUD ANALYTICS SOLUTIONS
    • 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
    • TABLE 4 HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
  • 7.2 DESCRIPTIVE ANALYTICS
    • 7.2.1 DESCRIPTIVE ANALYTICS SEGMENT ACCOUNTED FOR THE LARGEST MARKET SHARE
    • TABLE 5 DESCRIPTIVE ANALYTICS SOLUTIONS FOR HEALTHCARE FRAUD DETECTION
    • TABLE 6 DESCRIPTIVE ANALYTICS MARKET, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 7 DESCRIPTIVE ANALYTICS MARKET, BY COUNTRY, 2019-2026 (USD MILLION)
  • 7.3 PREDICTIVE ANALYTICS
    • 7.3.1 PREDICTIVE ANALYTICS HELPS IN SIMULATING FUTURE EVENTS AND TRENDS THAT CAN ENABLE PAYERS TO PREDICT PREVENTABLE EVENTS
    • TABLE 8 PREDICTIVE ANALYTICS SOLUTIONS FOR HEALTHCARE FRAUD DETECTION
    • TABLE 9 PREDICTIVE ANALYTICS MARKET, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 10 PREDICTIVE ANALYTICS MARKET, BY COUNTRY, 2019-2026 (USD MILLION)
  • 7.4 PRESCRIPTIVE ANALYTICS
    • 7.4.1 PRESCRIPTIVE MODELS OFFER ADDITIONAL ADVANTAGES RELATING TO THE INVESTIGATION OF SUSPICIOUS BEHAVIOR TO GENERATE COMPREHENSIVE INSIGHTS
    • TABLE 11 PRESCRIPTIVE ANALYTICS SOLUTIONS FOR HEALTHCARE FRAUD DETECTION
    • TABLE 12 PRESCRIPTIVE ANALYTICS MARKET, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 13 PRESCRIPTIVE ANALYTICS MARKET, BY COUNTRY, 2019-2026 (USD MILLION)

8 HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL

  • 8.1 INTRODUCTION
    • TABLE 14 HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
  • 8.2 ON-PREMISE DELIVERY MODELS
    • 8.2.1 ON-PREMISE MODELS ACCOUNT FOR THE LARGEST SHARE OF THE MARKET
    • TABLE 15 KEY VENDORS OFFERING ON-PREMISE SOLUTIONS IN THE MARKET
    • TABLE 16 HEALTHCARE FRAUD ANALYTICS MARKET FOR ON-PREMISE DELIVERY MODEL, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 17 HEALTHCARE FRAUD ANALYTICS MARKET FOR ON-PREMISE DELIVERY MODEL, BY COUNTRY, 2019-2026 (USD MILLION)
  • 8.3 ON-DEMAND DELIVERY MODELS
    • 8.3.1 CLOUD-BASED DELIVERY MODELS OFFER ORGANIZATIONS INCREASED SCALABILITY AND SPEED
    • TABLE 18 KEY VENDORS PROVIDING ON-DEMAND SOLUTIONS
    • TABLE 19 HEALTHCARE FRAUD ANALYTICS MARKET FOR ON-DEMAND DELIVERY MODEL, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 20 HEALTHCARE FRAUD ANALYTICS MARKET FOR ON-DEMAND DELIVERY MODEL, BY COUNTRY, 2019-2026 (USD MILLION)

9 HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION

  • 9.1 INTRODUCTION
    • TABLE 21 HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
  • 9.2 INSURANCE CLAIMS REVIEW
    • TABLE 22 DEPLOYMENT OF PREPAYMENT VS. POSTPAYMENT ANALYTICS SYSTEMS
    • TABLE 23 HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 24 HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 25 HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY COUNTRY, 2019-2026 (USD MILLION)
    • 9.2.1 POSTPAYMENT REVIEW
      • 9.2.1.1 Postpayment review dominates the healthcare fraud analytics insurance claims review market
    • TABLE 26 HEALTHCARE FRAUD ANALYTICS MARKET FOR POSTPAYMENT CLAIMS REVIEW, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 27 HEALTHCARE FRAUD ANALYTICS MARKET FOR POSTPAYMENT CLAIMS REVIEW, BY COUNTRY, 2019-2026 (USD MILLION)
    • 9.2.2 PREPAYMENT REVIEW
      • 9.2.2.1 The majority of prepayment models use predictive analytics to detect fraud and stop fraudulent claims payments
    • TABLE 28 HEALTHCARE FRAUD ANALYTICS MARKET FOR PREPAYMENT CLAIMS REVIEW, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 29 HEALTHCARE FRAUD ANALYTICS MARKET FOR PREPAYMENT CLAIMS REVIEW, BY COUNTRY, 2019-2026 (USD MILLION)
  • 9.3 PHARMACY BILLING MISUSE
    • 9.3.1 FRAUD, WASTE, AND ABUSE CASES IN PHARMACY AND PRESCRIPTION DRUG AREAS TO DRIVE THE DEMAND FOR ANALYTICS
    • TABLE 30 HEALTHCARE FRAUD ANALYTICS MARKET FOR PHARMACY BILLING MISUSE APPLICATION, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 31 HEALTHCARE FRAUD ANALYTICS MARKET FOR PHARMACY BILLING MISUSE APPLICATION, BY COUNTRY, 2019-2026 (USD MILLION)
  • 9.4 PAYMENT INTEGRITY
    • 9.4.1 CHANGES IN REGULATORY GUIDELINES HAVE AIDED THE ADOPTION OF PAYMENT INTEGRITY SOFTWARE
    • TABLE 32 HEALTHCARE FRAUD ANALYTICS MARKET FOR PAYMENT INTEGRITY APPLICATION, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 33 HEALTHCARE FRAUD ANALYTICS MARKET FOR PAYMENT INTEGRITY APPLICATION, BY COUNTRY, 2019-2026 (USD MILLION)
  • 9.5 OTHER APPLICATIONS
    • TABLE 34 HEALTHCARE FRAUD ANALYTICS MARKET FOR OTHER APPLICATION, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 35 HEALTHCARE FRAUD ANALYTICS MARKET FOR OTHER APPLICATIONS, BY COUNTRY, 2019-2026 (USD MILLION)

10 HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER

  • 10.1 INTRODUCTION
    • TABLE 36 HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
  • 10.2 PUBLIC & GOVERNMENT AGENCIES
    • 10.2.1 PUBLIC & GOVERNMENT AGENCIES DOMINATE THE HEALTHCARE FRAUD ANALYTICS MARKET
    • TABLE 37 HEALTHCARE FRAUD ANALYTICS MARKET FOR PUBLIC & GOVERNMENT AGENCIES, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 38 HEALTHCARE FRAUD ANALYTICS MARKET FOR PUBLIC & GOVERNMENT AGENCIES, BY COUNTRY, 2019-2026 (USD MILLION)
  • 10.3 PRIVATE INSURANCE PAYERS
    • 10.3.1 PRIVATE INSURANCE PAYERS ARE FOCUSED ON DEPLOYING ANALYTICS TO COMBAT INCREASING MONETARY LOSSES
    • TABLE 39 HEALTHCARE FRAUD ANALYTICS MARKET FOR PRIVATE INSURANCE PAYERS, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 40 HEALTHCARE FRAUD ANALYTICS MARKET FOR PRIVATE INSURANCE PAYERS, BY COUNTRY, 2019-2026 (USD MILLION)
  • 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
    • TABLE 41 HEALTHCARE FRAUD ANALYTICS MARKET FOR THIRD-PARTY SERVICE PROVIDERS, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 42 HEALTHCARE FRAUD ANALYTICS MARKET FOR THIRD-PARTY SERVICE PROVIDERS, BY COUNTRY, 2019-2026 (USD MILLION)
  • 10.5 EMPLOYERS
    • 10.5.1 EMPLOYERS ARE CONSIDERING FRAUD ANALYTICS SOLUTIONS AS A STEP TOWARD BETTER COST MANAGEMENT
    • TABLE 43 HEALTHCARE FRAUD ANALYTICS MARKET FOR EMPLOYERS, BY REGION, 2019-2026 (USD MILLION)
    • TABLE 44 HEALTHCARE FRAUD ANALYTICS MARKET FOR EMPLOYERS, BY COUNTRY, 2019-2026 (USD MILLION)

11 HEALTHCARE FRAUD ANALYTICS MARKET, BY REGION

  • 11.1 INTRODUCTION
    • TABLE 45 HEALTHCARE FRAUD ANALYTICS MARKET, BY REGION, 2019-2026 (USD MILLION)
  • 11.2 NORTH AMERICA
    • FIGURE 19 NORTH AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET SNAPSHOT
    • TABLE 46 NORTH AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET, BY COUNTRY, 2019-2026 (USD MILLION)
    • TABLE 47 NORTH AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 48 NORTH AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 49 NORTH AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 50 NORTH AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 51 NORTH AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
    • 11.2.1 US
      • 11.2.1.1 US dominates the global healthcare fraud analytics market
    • TABLE 52 US: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 53 US: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 54 US: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 55 US: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 56 US: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
    • 11.2.2 CANADA
      • 11.2.2.1 Growing adoption of data-crunching technologies like predictive analytics to drive market growth
    • TABLE 57 CANADA: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 58 CANADA: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 59 CANADA: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 60 CANADA: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 61 CANADA: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
  • 11.3 EUROPE
    • TABLE 62 LIST OF SOME OF THE EHFCN MEMBER ORGANIZATIONS ACROSS EUROPE
    • TABLE 63 EUROPE: HEALTHCARE FRAUD ANALYTICS MARKET, BY COUNTRY, 2019-2026 (USD MILLION)
    • TABLE 64 EUROPE: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 65 EUROPE: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 66 EUROPE: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 67 EUROPE: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 68 EUROPE: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
    • 11.3.1 GERMANY
      • 11.3.1.1 Germany is the fastest-growing market for healthcare fraud analytics solutions in Europe
    • TABLE 69 GERMANY: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 70 GERMANY: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 71 GERMANY: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 72 GERMANY: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 73 GERMANY: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
    • 11.3.2 UK
      • 11.3.2.1 Launch of initiatives such as NHSCFA will support the market for fraud analytics solutions in the UK
    • TABLE 74 UK: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 75 UK: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 76 UK: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 77 UK: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 78 UK: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
    • 11.3.3 FRANCE
      • 11.3.3.1 Increasing adoption of information technology for the detection of healthcare fraud-a key factor driving market growth
    • TABLE 79 FRANCE: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 80 FRANCE: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 81 FRANCE: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 82 FRANCE: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 83 FRANCE: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
    • 11.3.4 ITALY
      • 11.3.4.1 Increasing government support for the adoption of fraud analytics solutions
    • TABLE 84 ITALY: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 85 ITALY: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 86 ITALY: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 87 ITALY: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 88 ITALY: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
    • 11.3.5 SPAIN
      • 11.3.5.1 Advanced healthcare infrastructure to propel the adoption of innovative technologies like fraud analytics
    • TABLE 89 SPAIN: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 90 SPAIN: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 91 SPAIN: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 92 SPAIN: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 93 SPAIN: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
    • 11.3.6 REST OF EUROPE
    • TABLE 94 ROE: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 95 ROE: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 96 ROE: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 97 ROE: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 98 ROE: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
  • 11.4 ASIA
    • FIGURE 20 ASIA PACIFIC: HEALTHCARE FRAUD ANALYTICS MARKET SNAPSHOT
    • TABLE 99 ASIA: HEALTHCARE FRAUD ANALYTICS MARKET, BY COUNTRY, 2019-2026 (USD MILLION)
    • TABLE 100 ASIA: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 101 ASIA: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 102 ASIA: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 103 ASIA: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 104 ASIA: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
    • 11.4.1 JAPAN
      • 11.4.1.1 Increasing fraud cases in medical billing to drive market growth
    • TABLE 105 JAPAN: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 106 JAPAN: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 107 JAPAN: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 108 JAPAN: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 109 JAPAN: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
    • 11.4.2 CHINA
      • 11.4.2.1 Growing need for advanced healthcare systems for a better outcome to drive the demand for fraud analytics solutions
    • TABLE 110 CHINA: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 111 CHINA: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 112 CHINA: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 113 CHINA: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 114 CHINA: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
    • 11.4.3 ROA
      • 11.4.3.1 Increasing initiatives for establishing healthcare IT solutions to support market growth
    • TABLE 115 ROA: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 116 ROA: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 117 ROA: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 118 ROA: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 119 ROA: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
  • 11.5 PACIFIC
    • 11.5.1 GROWING NEED FOR INSURANCE COVERAGES AND MEDICAL CLAIMS TO DRIVE MARKET GROWTH
    • TABLE 120 PACIFIC: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 121 PACIFIC: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 122 PACIFIC: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 123 PACIFIC: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 124 PACIFIC: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
  • 11.6 LATIN AMERICA
    • 11.6.1 INCREASING PENETRATION OF HEALTH INSURANCE TO DRIVE VOLUME OF CLAIMS PROCESSING IN LATIN AMERICAN COUNTRIES
    • TABLE 125 LATIN AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 126 LATIN AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 127 LATIN AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 128 LATIN AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 129 LATIN AMERICA: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)
  • 11.7 MIDDLE EAST & AFRICA
    • 11.7.1 HEALTHCARE FRAUD IS ONE OF THE LEADING CRIMES IN SOUTH AFRICA
    • TABLE 130 MEA: HEALTHCARE FRAUD ANALYTICS MARKET, BY DELIVERY MODEL, 2019-2026 (USD MILLION)
    • TABLE 131 MEA: HEALTHCARE FRAUD ANALYTICS MARKET, BY SOLUTION TYPE, 2019-2026 (USD MILLION)
    • TABLE 132 MEA: HEALTHCARE FRAUD ANALYTICS MARKET, BY APPLICATION, 2019-2026 (USD MILLION)
    • TABLE 133 MEA: HEALTHCARE FRAUD ANALYTICS MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2019-2026 (USD MILLION)
    • TABLE 134 MEA: HEALTHCARE FRAUD ANALYTICS MARKET, BY END USER, 2019-2026 (USD MILLION)

12 COMPETITIVE LANDSCAPE

  • 12.1 INTRODUCTION
    • FIGURE 21 KEY DEVELOPMENTS IN THE HEALTHCARE FRAUD ANALYTICS MARKET BETWEEN JANUARY 2018 AND AUGUST 2021
  • 12.2 COMPETITIVE SITUATION AND TRENDS
    • 12.2.1 DEALS
    • TABLE 135 DEALS, 2018-2021
  • 12.3 COMPETITIVE LEADERSHIP MAPPING
    • 12.3.1 STARS
    • 12.3.2 EMERGING LEADERS
    • 12.3.3 PERVASIVE PLAYERS
    • 12.3.4 PARTICIPANTS
    • FIGURE 22 HEALTHCARE FRAUD ANALYTICS MARKET: COMPETITIVE LEADERSHIP MAPPING, 2020

13 COMPANY PROFILES

  • (Business Overview, Products Offered, Recent Developments, SWOT Analysis, MnM View)**
  • 13.1 KEY PLAYERS
    • 13.1.1 IBM CORPORATION
    • TABLE 136 IBM CORPORATION: BUSINESS OVERVIEW
    • FIGURE 23 IBM CORPORATION: COMPANY SNAPSHOT (2020)
    • 13.1.2 OPTUM, INC. (A PART OF UNITEDHEALTH GROUP)
    • TABLE 137 OPTUM, INC.: BUSINESS OVERVIEW
    • 13.1.3 COTIVITI, INC.
    • TABLE 138 COTIVITI, INC.: BUSINESS OVERVIEW
    • 13.1.4 FAIR ISAAC CORPORATION
    • TABLE 139 FAIR ISAAC CORPORATION: BUSINESS OVERVIEW
    • FIGURE 24 FAIR ISAAC CORPORATION: COMPANY SNAPSHOT (2020)
    • 13.1.5 SAS INSTITUTE INC.
    • TABLE 140 SAS INSTITUTE INC.: BUSINESS OVERVIEW
    • 13.1.6 CHANGE HEALTHCARE
    • TABLE 141 CHANGE HEALTHCARE: BUSINESS OVERVIEW
    • 13.1.7 PONDERA SOLUTIONS, INC. (A SUBSIDIARY OF THOMSON REUTERS CORPORATION)
    • TABLE 142 PONDERA SOLUTIONS, INC.: BUSINESS OVERVIEW
    • 13.1.8 EXLSERVICE HOLDINGS, INC.
    • TABLE 143 EXLSERVICE HOLDINGS, INC.: BUSINESS OVERVIEW
    • FIGURE 25 EXLSERVICE HOLDINGS, INC.: COMPANY SNAPSHOT (2020)
    • 13.1.9 WIPRO LIMITED
    • TABLE 144 WIPRO LIMITED: BUSINESS OVERVIEW
    • FIGURE 26 WIPRO LIMITED: COMPANY SNAPSHOT (2021)
    • 13.1.10 CONDUENT INCORPORATED
    • TABLE 145 CONDUENT INCORPORATED: BUSINESS OVERVIEW
    • FIGURE 27 CONDUENT INCORPORATED: COMPANY SNAPSHOT (2020)
    • 13.1.11 HCL TECHNOLOGIES LIMITED
    • TABLE 146 HCL TECHNOLOGIES LIMITED.: BUSINESS OVERVIEW
    • FIGURE 28 HCL TECHNOLOGIES LIMITED.: COMPANY SNAPSHOT (2021)
    • 13.1.12 CGI INC.
    • TABLE 147 CGI INC.: BUSINESS OVERVIEW
    • FIGURE 29 CGI INC.: COMPANY SNAPSHOT (2020)
    • 13.1.13 DXC TECHNOLOGY
    • TABLE 148 DXC TECHNOLOGY COMPANY: BUSINESS OVERVIEW
    • FIGURE 30 DXC TECHNOLOGY COMPANY: COMPANY SNAPSHOT (2021)
    • 13.1.14 NORTHROP GRUMMAN CORPORATION
    • TABLE 149 NORTHROP GRUMMAN CORPORATION: BUSINESS OVERVIEW
    • FIGURE 31 NORTHROP GRUMMAN CORPORATION: COMPANY SNAPSHOT (2020)
    • 13.1.15 LEXISNEXIS (A PART OF RELX GROUP)
    • TABLE 150 LEXISNEXIS: BUSINESS OVERVIEW
    • FIGURE 32 RELX GROUP: COMPANY SNAPSHOT (2020)
    • 13.1.16 QLARANT, INC.
    • TABLE 151 QLARANT, INC.: BUSINESS OVERVIEW
    • 13.1.17 H2O.AI
    • TABLE 152 H2O.AI: BUSINESS OVERVIEW
    • 13.1.18 MULTIPLAN
    • TABLE 153 MULTIPLAN: BUSINESS OVERVIEW
    • 13.1.19 FRISS
    • TABLE 154 FRISS: BUSINESS OVERVIEW
    • 13.1.20 OSP LABS
    • TABLE 155 OSP LABS: BUSINESS OVERVIEW
  • 13.2 OTHER PLAYERS
    • 13.2.1 SHARECARE, INC. (A SUBSIDIARY OF FALCON CAPITAL ACQUISITION CORP.)
    • 13.2.2 HEALTHCARE FRAUD SHIELD
    • 13.2.3 FRAUDLENS, INC.
    • 13.2.4 HMS HOLDINGS CORP.
    • 13.2.5 CODOXO
  • *Details on Business Overview, Products Offered, Recent Developments, SWOT Analysis, 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