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ヘルスケア産業向け不正アナリティクス：世界の展望・予測 (2023-2028年)

Healthcare Fraud Analytics Market - Global Outlook & Forecast 2023-2028

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ヘルスケア産業向け不正アナリティクス：世界の展望・予測 (2023-2028年)
出版日: 2023年05月17日
発行: Arizton Advisory & Intelligence
ページ情報: 英文
納期: 即納可能 即納可能とは
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  • 概要
  • 目次
概要

世界のヘルスケア産業向け不正アナリティクスの市場規模は、2022年から2028年にかけて20.45%のCAGRで成長すると予測されています。

ヘルスケア産業における不正行為の増加、医療保険の恩恵を受ける患者数の増加、薬局での請求関連の不正行為の増加、ICTへの投資などの要因が同市場の成長を推進しています。

当レポートでは、世界のヘルスケア産業向け不正アナリティクスの市場を調査し、市場の定義と概要、市場機会・市場動向、市場影響因子の分析、市場規模の推移・予測、各種区分・地域別の詳細分析、競合情勢、主要企業のプロファイルなどをまとめています。

目次

第1章 調査手法

第2章 調査の目的

第3章 調査プロセス

第4章 調査対象・調査範囲

第5章 レポートの前提・注記

第6章 市場概要

第7章 重要考察

第8章 イントロダクション

第9章 市場機会・市場動向

  • ICTへの投資
  • 先進技術が不正から守る大きな可能性を提供
  • ヘルスケア産業での不正検出におけるAI

第10章 市場成長の実現因子

  • ヘルスケア産業での不正の増加
  • 医療保険の恩恵を受ける患者数の増加
  • 薬局の請求関連の不正件数の増加

第11章 市場抑制要因

  • 不正パターンの変化
  • 不正アナリティクスソリューションによるセキュリティ&プライバシー上のリスク
  • 導入の所要時間と頻繁なアップグレードの必要性

第12章 市場情勢

  • 市場概要
  • 市場規模・予測
  • ファイブフォース分析

第13章 ソリューションタイプ

  • 市場スナップショット・成長エンジン
  • 市場概要
  • 記述的分析
  • 予測的分析
  • 処方的分析

第14章 デリバリーモード

  • 市場スナップショット・成長エンジン
  • 市場概要
  • オンプレミス
  • クラウド

第15章 用途

  • 市場スナップショット・成長エンジン
  • 市場概要
  • 医療提供者による不正
  • 患者による不正
  • 処方に関する不正
  • ヘルスケア関連の一般的不正

第16章 エンドユーザー

  • 市場スナップショット・成長エンジン
  • 市場概要
  • 公的健康保険会社
  • 民間医療保険会社
  • サードパーティサービスプロバイダー
  • その他

第17章 地域

  • 市場スナップショット・成長エンジン
  • 地理的な概要

第18章 北米

第19章 欧州

第20章 アジア太平洋

第21章 ラテンアメリカ

第22章 中東・アフリカ

第23章 競合情勢

  • 競合概要
  • 市場シェア分析

第24章 主要企業プロファイル

  • IBM
  • LEXISNEXIS RISK SOLUTIONS
  • OPTUM
  • SAS INSTITUTE
  • VERISK ANALYTICS
  • WIPRO

第25章 その他の有力ベンダー

  • ALIVIA ANALYTICS
  • CGI
  • CODOXO
  • CONDUENT
  • COTIVITI
  • FRAUDLENS
  • FRISS
  • HEALTHCARE FRAUD SHIELD
  • NORTHROP GRUMMAN CORPORATION
  • OSP
  • QLARANT
  • QUALETICS DATA MACHINES
  • SHARECARE

第26章 レポート概要

  • 重要ポイント
  • 戦略的提言

第27章 定量的サマリー

第28章 付録

目次
Product Code: ARZ230326

The global healthcare fraud analytics market is expected to grow at a CAGR of 20.45% from 2022-2028.

MARKET TRENDS AND DRIVERS

Increasing Healthcare Fraudulent Activities

Healthcare fraud has been an ongoing problem in the healthcare industry for a long time. The increase in healthcare costs, the rise in technological advances, and a greater reliance on electronic data have all contributed to an increase in healthcare fraud. The healthcare fraud analytics market helps combat this issue by identifying fraudulent activities and helping organizations take proactive measures to prevent future fraud. Healthcare fraud analytics uses various analytic techniques to analyze large datasets and detect suspicious behavior patterns. These techniques can detect billing and coding errors, improper payments, and other forms of fraud. Healthcare fraud analytics also helps organizations identify trends in healthcare fraud and proactively address areas of risk. The increasing prevalence of healthcare fraud is driving the demand for healthcare fraud analytics solutions. Organizations increasingly invest in healthcare fraud analytics solutions to detect and prevent fraudulent activities and protect their financial and reputational interests.

The Increasing Number of Patients Benefiting From Healthcare Insurance

Healthcare fraud analytics uses data analytics and artificial intelligence to detect fraud and patterns in healthcare claims and other activities related to healthcare fraud. With the increasing number of patients receiving healthcare insurance, the potential amount of fraud increases, making it essential to have a reliable fraud detection system. The healthcare fraud analytics market helps to detect fraudulent activities such as billing for services not rendered and incorrect coding. With the increasing number of healthcare policies, fraudulent activities also increase, making identifying and preventing them difficult. Healthcare fraud analytics helps to identify these activities quickly and accurately, thus reducing the risk of fraud.

The Increasing Number of Pharmacy Claims-Related Frauds

With the growth of the healthcare industry, fraud & abuse have become increasingly serious problems. Fraudsters are taking advantage of the complexity of the healthcare system and the lack of oversight to commit fraud. As a result, healthcare organizations are facing increasing pressure to protect their finances from fraudulent activities. The healthcare fraud analytics market is growing as healthcare organizations begin recognizing the need for advanced analytics solutions to detect and prevent fraud. Healthcare analytics solutions are used to identify suspicious transactions and activities that could indicate fraudulent behavior. These solutions help detect and prevent fraud by providing insights into fraud patterns, allowing organizations to take corrective action.

Investment in ICT

Investment in ICT is a new opportunity for the healthcare fraud analytics market. ICT solutions such as Artificial Intelligence (AI) and Machine Learning (ML) can be used to detect and prevent fraud in the healthcare industry. By leveraging these technologies, healthcare organizations can develop and deploy predictive analytics models to detect suspicious transactions, identity theft, and other fraudulent activities. This can help organizations reduce the risk of fraud, save money, and improve operational efficiency.

Advanced Technologies Offer Greater Potential to Secure Against Fraud

Advanced technologies offer greater potential to secure against fraud, and this is a new opportunity for the healthcare fraud analytics market. With the increasing sophistication of fraud attempts, the need for advanced analytics tools to detect, prevent, and investigate fraud is becoming more important. Advanced analytics tools can help detect and prevent fraud more quickly and efficiently while providing more detailed insights into fraud patterns. This can help healthcare organizations identify potential areas of fraud and take steps to reduce the risk. In addition, advanced analytics can help healthcare organizations detect and investigate fraud more effectively, which can help reduce the financial losses associated with fraudulent activities.

AI in Healthcare Fraud Detection

AI in healthcare fraud detection is a new opportunity for the healthcare fraud analytics market. AI can detect and prevent fraud more quickly and accurately than traditional methods, reducing financial and administrative costs. AI can identify patterns in large amounts of data that would be impossible to find using manual methods and identify suspicious behavior that would be difficult to detect using traditional methods. AI can also help organizations identify and address fraud risk areas more quickly, as well as help them develop strategies to prevent future fraud from occurring.

SEGMENTATION INSIGHTS

INSIGHTS BY SOLUTION TYPE

The global healthcare fraud analytics market by solution type is segmented into descriptive, predictive, and prescriptive analytics. Descriptive analytics is a form of data analysis that seeks to summarize past events and identify patterns in data. It is a process that involves collecting, organizing, and analyzing data to gain insights that can be used to inform future decisions or strategies. This type of analytics is especially useful for businesses, as it can better understand customer behaviors, sales trends, and performance metrics. Descriptive fraud analytics is the process of analyzing data to detect patterns of fraud and other suspicious activities. It is a type of analytics that helps organizations identify and understand fraud-related activities and detect fraud before it occurs.

However, predictive analytics is expected to grow at a CAGR in the global healthcare fraud analytics market during the forecast period. Predictive analytics can also be used to detect trends in healthcare fraud. By analyzing the data from various sources, such as patient records, medical records, and healthcare billing systems, the predictive model can identify patterns of fraud that may not be easily visible.

Segmentation by Solution Type

  • Descriptive Analytics
  • Predictive Analytics
  • Prescriptive Analytics

INSIGHTS BY DELIVERY MODE

The global healthcare fraud analytics market by delivery mode is segmented into on-premises and cloud-based. The on-premises segment dominated the market, accounting for over 52% share in 2022, and is anticipated to retain its dominance during the forecast period. On-premises service allows companies to verify customers and store data on their servers. No third party can access the customers' data, the service provider, or vendors. This service ensures that their customer onboarding process is secure and the information collected stays safe from criminal activities. Several on-premises benefits also significantly contribute to why healthcare organizations are still hesitant to embrace the cloud. The biggest benefit to on-premises applications is that the IT department has full control over the data stored on them.

Segmentation by Delivery Mode

  • On-premises
  • Cloud-based

INSIGHTS BY APPLICATIONS

The medical provider fraud application segment holds the largest global healthcare fraud analytics market share. Medical provider fraud occurs when a health care provider, such as a doctor, nurse, or therapist, defrauds a medical insurance provider for reimbursement for services that were never provided or for services of a lower quality than what was promised. Both individuals and organizations can perpetrate this type of fraud, which can be difficult to detect due to the complexity of medical billing systems. The most common form of medical provider fraud is billing for never provided services. This may include billing for an office visit that never occurred or for procedures that were not done. This type of fraud can also occur when providers bill for services at a higher rate than what was performed or for more expensive treatments than what was actually given.

Segmentation by Application

  • Medical Provider Fraud
  • Patient Fraud
  • Prescription Fraud
  • General Healthcare Fraud

INSIGHTS BY END-USER

The global healthcare fraud analytics market by end-user is segmented into public health insurance companies, private health insurance companies, third-party service providers, and other end users. The public health insurance companies segment accounted for a major share in 2022. Public health insurance companies play an integral role in the health and well-being of individuals and the country. By providing financial coverage for medical costs and preventive care, these companies can help keep individuals healthy while reducing healthcare costs. Public health insurance companies have a key role in the global healthcare fraud analytics market. They are responsible for providing healthcare coverage to citizens and are the main funding source for healthcare services. With the rising healthcare costs and the prevalence of fraud and abuse, public health insurance companies must take a proactive approach to combat fraud and abuse. Public health insurance companies can help reduce fraud and abuse by using healthcare fraud analytics tools to identify suspicious activity and detect fraud.

Segmentation by End-user

  • Public Health Insurance Companies
  • Private Health Insurance Companies
  • Third-party Service Providers
  • Others

GEOGRAPHICAL ANALYSIS

North America accounted for a major share of the global healthcare fraud analytics market in 2022, accounting for nearly 43%. The presence of a large patient population and better adoption of digital healthcare with the latest advancements in artificial intelligence (AI) is the primary factor for its high market share. The presence of key healthcare IT players is another reason for the high uptake of healthcare fraud analytics in North America. The use of healthcare fraud analytics is becoming increasingly common in the United States and Canada. In the United States, the Department of Health and Human Services (HHS) uses healthcare fraud analytics to identify fraud in Medicare and Medicaid.

Segmentation by Geography

  • North America
    • US
    • Canada
  • Europe
    • Germany
    • UK
    • France
    • Italy
    • Spain
  • APAC
    • China
    • Japan
    • South Korea
    • India
    • Australia
  • Latin America
    • Brazil
    • Mexico
    • Argentina
  • Middle East & Africa
    • Turkey
    • Saudi Arabia
    • South Africa

VENDOR LANDSCAPE

The global healthcare fraud analytics market is a rapidly growing industry since fraud and abuse in the healthcare system is an ongoing problem resulting in billions of dollars in losses to insurers and patients. The market is driven by rising healthcare costs, increasing consumer demand for transparency and accountability, and the need to reduce fraud and abuse. The global healthcare fraud analytics market is emerging, with global, regional, and local players recommending a broad range of conventional and latest-generation artificial intelligence (AI) technologies for end-users. The key vendors in the global healthcare fraud analytics market include IBM, LexisNexis Risk Solution, Optum, SAS Institute, Verisk Analytics, and Wipro, based on factors such as digital healthcare platforms, patient management, and clinical advancements. These companies have a broad geographic presence, diverse product portfolios, and a strong focus on product innovation, R&D, and business expansion activities.

Key Company Profiles

  • IBM
  • LexisNexis Risk Solutions
  • Optum
  • SAS Institute
  • Verisk Analytics
  • Wipro

Other Prominent Vendors

  • Alivia Analytics
  • CGI
  • Codoxo
  • Conduent
  • COTIVITI
  • FraudLens
  • FRISS
  • Healthcare Fraud Shield
  • Northrop Grumman Corporation
  • OSP
  • Qlarant
  • Qualetics Data Machines
  • Sharecare

KEY QUESTIONS ANSWERED:

  • 1. How big is the global healthcare fraud analytics market?
  • 2. What is the growth rate of the healthcare fraud analytics market?
  • 3. What are the growing trends in the healthcare fraud analytics market?
  • 4. Which region holds the most significant global healthcare fraud analytics market share?
  • 5. Who are the key players in the global healthcare fraud analytics market?

TABLE OF CONTENTS

1 RESEARCH METHODOLOGY

2 RESEARCH OBJECTIVES

3 RESEARCH PROCESS

4 SCOPE & COVERAGE

  • 4.1 MARKET DEFINITION
    • 4.1.1 INCLUSIONS
    • 4.1.2 EXCLUSIONS
    • 4.1.3 MARKET ESTIMATION CAVEATS
  • 4.2 BASE YEAR
  • 4.3 SCOPE OF THE STUDY
    • 4.3.1 MARKET SEGMENTATION BY SOLUTION TYPE
    • 4.3.2 MARKET SEGMENTATION BY DELIVERY MODE
    • 4.3.3 MARKET SEGMENTATION BY APPLICATION
    • 4.3.4 MARKET SEGMENTATION BY END-USER
    • 4.3.5 MARKET SEGMENTATION BY GEOGRAPHY

5 REPORT ASSUMPTIONS & CAVEATS

  • 5.1 KEY CAVEATS
  • 5.2 CURRENCY CONVERSION
  • 5.3 MARKET DERIVATION

6 MARKET AT A GLANCE

7 PREMIUM INSIGHTS

  • 7.1 OVERVIEW

8 INTRODUCTION

  • 8.1 OVERVIEW

9 MARKET OPPORTUNITIES & TRENDS

  • 9.1 INVESTMENT IN INFORMATION & COMMUNICATION TECHNOLOGY (ICT)
  • 9.2 ADVANCED TECHNOLOGIES OFFER GREAT POTENTIAL TO SECURE AGAINST FRAUD
  • 9.3 AI IN HEALTHCARE FRAUD DETECTION

10 MARKET GROWTH ENABLERS

  • 10.1 INCREASING HEALTHCARE FRAUDULENT ACTIVITIES
  • 10.2 INCREASING NUMBER OF PATIENTS BENEFITING FROM HEALTHCARE INSURANCE
  • 10.3 RISING NUMBER OF PHARMACY CLAIM-RELATED FRAUDS

11 MARKET RESTRAINTS

  • 11.1 CHANGE IN FRAUD PATTERNS
  • 11.2 SECURITY & PRIVACY RISKS WITH FRAUD ANALYTICS SOLUTIONS
  • 11.3 TIME-CONSUMING DEPLOYMENT AND NEED FOR FREQUENT UPGRADES

12 MARKET LANDSCAPE

  • 12.1 MARKET OVERVIEW
  • 12.2 MARKET SIZE & FORECAST
    • 12.2.1 GEOGRAPHY INSIGHTS
    • 12.2.2 SOLUTION TYPE INSIGHTS
    • 12.2.3 DELIVERY MODE INSIGHTS
    • 12.2.4 APPLICATION INSIGHTS
    • 12.2.5 END-USER INSIGHTS
  • 12.3 FIVE FORCES ANALYSIS
    • 12.3.1 THREAT OF NEW ENTRANTS
    • 12.3.2 BARGAINING POWER OF SUPPLIERS
    • 12.3.3 BARGAINING POWER OF BUYERS
    • 12.3.4 THREAT OF SUBSTITUTES
    • 12.3.5 COMPETITIVE RIVALRY

13 SOLUTION TYPE

  • 13.1 MARKET SNAPSHOT & GROWTH ENGINE
  • 13.2 MARKET OVERVIEW
  • 13.3 DESCRIPTIVE ANALYTICS
    • 13.3.1 MARKET OVERVIEW
    • 13.3.2 MARKET SIZE & FORECAST
    • 13.3.3 MARKET BY GEOGRAPHY
  • 13.4 PREDICTIVE ANALYTICS
    • 13.4.1 MARKET OVERVIEW
    • 13.4.2 MARKET SIZE & FORECAST
    • 13.4.3 MARKET BY GEOGRAPHY
  • 13.5 PRESCRIPTIVE ANALYTICS
    • 13.5.1 MARKET OVERVIEW
    • 13.5.2 MARKET SIZE & FORECAST
    • 13.5.3 MARKET BY GEOGRAPHY

14 DELIVERY MODE

  • 14.1 MARKET SNAPSHOT & GROWTH ENGINE
  • 14.2 MARKET OVERVIEW
  • 14.3 ON-PREMISES
    • 14.3.1 MARKET OVERVIEW
    • 14.3.2 MARKET SIZE & FORECAST
    • 14.3.3 MARKET BY GEOGRAPHY
  • 14.4 CLOUD-BASED
    • 14.4.1 MARKET OVERVIEW
    • 14.4.2 MARKET SIZE & FORECAST
    • 14.4.3 MARKET BY GEOGRAPHY

15 APPLICATION

  • 15.1 MARKET SNAPSHOT & GROWTH ENGINE
  • 15.2 MARKET OVERVIEW
  • 15.3 MEDICAL PROVIDER FRAUD
    • 15.3.1 MARKET OVERVIEW
    • 15.3.2 MARKET SIZE & FORECAST
    • 15.3.3 MARKET BY GEOGRAPHY
  • 15.4 PATIENT FRAUD
    • 15.4.1 MARKET OVERVIEW
    • 15.4.2 MARKET SIZE & FORECAST
    • 15.4.3 MARKET BY GEOGRAPHY
  • 15.5 PRESCRIPTION FRAUD
    • 15.5.1 MARKET OVERVIEW
    • 15.5.2 MARKET SIZE & FORECAST
    • 15.5.3 MARKET BY GEOGRAPHY
  • 15.6 GENERAL HEALTHCARE FRAUD
    • 15.6.1 MARKET OVERVIEW
    • 15.6.2 MARKET SIZE & FORECAST
    • 15.6.3 MARKET BY GEOGRAPHY

16 END-USER

  • 16.1 MARKET SNAPSHOT & GROWTH ENGINE
  • 16.2 MARKET OVERVIEW
  • 16.3 PUBLIC HEALTH INSURANCE COMPANIES
    • 16.3.1 MARKET OVERVIEW
    • 16.3.2 MARKET SIZE & FORECAST
    • 16.3.3 MARKET BY GEOGRAPHY
  • 16.4 PRIVATE HEALTH INSURANCE COMPANIES
    • 16.4.1 MARKET OVERVIEW
    • 16.4.2 MARKET SIZE & FORECAST
    • 16.4.3 MARKET BY GEOGRAPHY
  • 16.5 THIRD-PARTY SERVICE PROVIDERS
    • 16.5.1 MARKET OVERVIEW
    • 16.5.2 MARKET SIZE & FORECAST
    • 16.5.3 MARKET BY GEOGRAPHY
  • 16.6 OTHERS
    • 16.6.1 MARKET OVERVIEW
    • 16.6.2 MARKET SIZE & FORECAST
    • 16.6.3 MARKET BY GEOGRAPHY

17 GEOGRAPHY

  • 17.1 MARKET SNAPSHOT & GROWTH ENGINE
  • 17.2 GEOGRAPHIC OVERVIEW

18 NORTH AMERICA

  • 18.1 MARKET OVERVIEW
  • 18.2 MARKET SIZE & FORECAST
    • 18.2.1 MARKET BY SOLUTION TYPE
    • 18.2.2 MARKET BY DELIVERY MODE
    • 18.2.3 MARKET BY APPLICATION
    • 18.2.4 MARKET BY END-USER
  • 18.3 KEY COUNTRIES
    • 18.3.1 US: MARKET SIZE & FORECAST
    • 18.3.2 CANADA: MARKET SIZE & FORECAST

19 EUROPE

  • 19.1 MARKET OVERVIEW
  • 19.2 MARKET SIZE & FORECAST
    • 19.2.1 MARKET BY SOLUTION TYPE
    • 19.2.2 MARKET BY DELIVERY MODE
    • 19.2.3 MARKET BY APPLICATION
    • 19.2.4 MARKET BY END-USER
  • 19.3 KEY COUNTRIES
    • 19.3.1 GERMANY: MARKET SIZE & FORECAST
    • 19.3.2 UK: MARKET SIZE & FORECAST
    • 19.3.3 FRANCE: MARKET SIZE & FORECAST
    • 19.3.4 ITALY: MARKET SIZE & FORECAST
    • 19.3.5 SPAIN: MARKET SIZE & FORECAST

20 APAC

  • 20.1 MARKET OVERVIEW
  • 20.2 MARKET SIZE & FORECAST
    • 20.2.1 MARKET BY SOLUTION TYPE
    • 20.2.2 MARKET BY DELIVERY MODE
    • 20.2.3 MARKET BY APPLICATION
    • 20.2.4 MARKET BY END-USER
  • 20.3 KEY COUNTRIES
    • 20.3.1 CHINA: MARKET SIZE & FORECAST
    • 20.3.2 JAPAN: MARKET SIZE & FORECAST
    • 20.3.3 SOUTH KOREA: MARKET SIZE & FORECAST
    • 20.3.4 INDIA: MARKET SIZE & FORECAST
    • 20.3.5 AUSTRALIA: MARKET SIZE & FORECAST

21 LATIN AMERICA

  • 21.1 MARKET OVERVIEW
  • 21.2 MARKET SIZE & FORECAST
    • 21.2.1 MARKET BY SOLUTION TYPE
    • 21.2.2 MARKET BY DELIVERY MODE
    • 21.2.3 MARKET BY APPLICATION
    • 21.2.4 MARKET BY END-USER
  • 21.3 KEY COUNTRIES
    • 21.3.1 BRAZIL: MARKET SIZE & FORECAST
    • 21.3.2 MEXICO: MARKET SIZE & FORECAST
    • 21.3.3 ARGENTINA: MARKET SIZE & FORECAST

22 MIDDLE EAST & AFRICA

  • 22.1 MARKET OVERVIEW
  • 22.2 MARKET SIZE & FORECAST
    • 22.2.1 MARKET BY SOLUTION TYPE
    • 22.2.2 MARKET BY DELIVERY MODE
    • 22.2.3 MARKET BY APPLICATION
    • 22.2.4 MARKET BY END-USER
  • 22.3 KEY COUNTRIES
    • 22.3.1 TURKEY: MARKET SIZE & FORECAST
    • 22.3.2 SAUDI ARABIA: MARKET SIZE & FORECAST
    • 22.3.3 SOUTH AFRICA: MARKET SIZE & FORECAST

23 COMPETITIVE LANDSCAPE

  • 23.1 COMPETITION OVERVIEW
  • 23.2 MARKET SHARE ANALYSIS
    • 23.2.1 IBM
    • 23.2.2 LEXISNEXIS RISK SOLUTIONS
    • 23.2.3 OPTUM
    • 23.2.4 SAS INSTITUTE
    • 23.2.5 VERISK ANALYTICS
    • 23.2.6 WIPRO

24 KEY COMPANY PROFILES

  • 24.1 IBM
    • 24.1.1 BUSINESS OVERVIEW
    • 24.1.2 PRODUCT OFFERINGS
    • 24.1.3 KEY STRATEGIES
    • 24.1.4 KEY STRENGTHS
    • 24.1.5 KEY OPPORTUNITIES
  • 24.2 LEXISNEXIS RISK SOLUTIONS
    • 24.2.1 BUSINESS OVERVIEW
    • 24.2.2 PRODUCT OFFERINGS
    • 24.2.3 KEY STRATEGIES
    • 24.2.4 KEY STRENGTHS
    • 24.2.5 KEY OPPORTUNITIES
  • 24.3 OPTUM
    • 24.3.1 BUSINESS OVERVIEW
    • 24.3.2 PRODUCT OFFERINGS
    • 24.3.3 KEY STRATEGIES
    • 24.3.4 KEY STRENGTHS
    • 24.3.5 KEY OPPORTUNITIES
  • 24.4 SAS INSTITUTE
    • 24.4.1 BUSINESS OVERVIEW
    • 24.4.2 PRODUCT OFFERINGS
    • 24.4.3 KEY STRATEGIES
    • 24.4.4 KEY STRENGTHS
    • 24.4.5 KEY OPPORTUNITIES
  • 24.5 VERISK ANALYTICS
    • 24.5.1 BUSINESS OVERVIEW
    • 24.5.2 PRODUCT OFFERINGS
    • 24.5.3 KEY STRATEGIES
    • 24.5.4 KEY STRENGTHS
    • 24.5.5 KEY OPPORTUNITIES
  • 24.6 WIPRO
    • 24.6.1 BUSINESS OVERVIEW
    • 24.6.2 PRODUCT OFFERINGS
    • 24.6.3 KEY STRATEGIES
    • 24.6.4 KEY STRENGTHS
    • 24.6.5 KEY OPPORTUNITIES

25 OTHER PROMINENT VENDORS

  • 25.1 ALIVIA ANALYTICS
    • 25.1.1 BUSINESS OVERVIEW
    • 25.1.2 PRODUCT OFFERINGS
  • 25.2 CGI
    • 25.2.1 BUSINESS OVERVIEW
    • 25.2.2 PRODUCT OFFERINGS
  • 25.3 CODOXO
    • 25.3.1 BUSINESS OVERVIEW
    • 25.3.2 PRODUCT OFFERINGS
  • 25.4 CONDUENT
    • 25.4.1 BUSINESS OVERVIEW
    • 25.4.2 PRODUCT OFFERINGS
  • 25.5 COTIVITI
    • 25.5.1 BUSINESS OVERVIEW
    • 25.5.2 PRODUCT OFFERINGS
  • 25.6 FRAUDLENS
    • 25.6.1 BUSINESS OVERVIEW
    • 25.6.2 PRODUCT OFFERINGS
  • 25.7 FRISS
    • 25.7.1 BUSINESS OVERVIEW
    • 25.7.2 PRODUCT OFFERINGS
  • 25.8 HEALTHCARE FRAUD SHIELD
    • 25.8.1 BUSINESS OVERVIEW
    • 25.8.2 PRODUCT OFFERINGS
  • 25.9 NORTHROP GRUMMAN CORPORATION
    • 25.9.1 BUSINESS OVERVIEW
    • 25.9.2 PRODUCT OFFERINGS
  • 25.10 OSP
    • 25.10.1 BUSINESS OVERVIEW
    • 25.10.2 PRODUCT OFFERINGS
  • 25.11 QLARANT
    • 25.11.1 BUSINESS OVERVIEW
    • 25.11.2 PRODUCT OFFERINGS
  • 25.12 QUALETICS DATA MACHINES
    • 25.12.1 BUSINESS OVERVIEW
    • 25.12.2 PRODUCT OFFERINGS
  • 25.13 SHARECARE
    • 25.13.1 BUSINESS OVERVIEW
    • 25.13.2 PRODUCT OFFERINGS

26 REPORT SUMMARY

  • 26.1 KEY TAKEAWAYS
  • 26.2 STRATEGIC RECOMMENDATIONS

27 QUANTITATIVE SUMMARY

  • 27.1 MARKET BY SOLUTION TYPE
    • 27.1.1 NORTH AMERICA: MARKET BY SOLUTION TYPE
    • 27.1.2 EUROPE: MARKET BY SOLUTION TYPE
    • 27.1.3 APAC: MARKET BY SOLUTION TYPE
    • 27.1.4 LATIN AMERICA: MARKET BY SOLUTION TYPE
    • 27.1.5 MIDDLE EAST & AFRICA: MARKET BY SOLUTION TYPE
  • 27.2 MARKET BY DELIVERY MODE
    • 27.2.1 NORTH AMERICA: MARKET BY DELIVERY MODE
    • 27.2.2 EUROPE: MARKET BY DELIVERY MODE
    • 27.2.3 APAC: MARKET BY DELIVERY MODE
    • 27.2.4 LATIN AMERICA: MARKET BY DELIVERY MODE
    • 27.2.5 MIDDLE EAST & AFRICA: MARKET BY DELIVERY MODE
  • 27.3 MARKET BY APPLICATION
    • 27.3.1 NORTH AMERICA: MARKET BY APPLICATION
    • 27.3.2 EUROPE: MARKET BY APPLICATION
    • 27.3.3 APAC: MARKET BY APPLICATION
    • 27.3.4 LATIN AMERICA: MARKET BY APPLICATION
    • 27.3.5 MIDDLE EAST & AFRICA: MARKET BY APPLICATION
  • 27.4 MARKET BY END-USER
    • 27.4.1 NORTH AMERICA: MARKET BY END-USER
    • 27.4.2 EUROPE: MARKET BY END-USER
    • 27.4.3 APAC: MARKET BY END-USER
    • 27.4.4 LATIN AMERICA: MARKET BY END-USER
    • 27.4.5 MIDDLE EAST & AFRICA: MARKET BY END-USER

28 APPENDIX

  • 28.1 ABBREVIATIONS