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1275603

헬스케어 산업용 부정 애널리틱스 : 세계 전망과 예측(2023-2028년)

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

발행일: | 리서치사: Arizton Advisory & Intelligence | 페이지 정보: 영문 | 배송안내 : 즉시배송

※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

세계의 헬스케어 산업용 부정 애널리틱스 시장 규모는 2022-2028년 20.45%의 CAGR로 성장할 것으로 예측되고 있습니다.

헬스케어 산업에서 부정행위의 증가, 의료보험 혜택을 받는 환자 수의 증가, 약국에서 청구 관련 부정행위의 증가, ICT에 대한 투자 등의 요인이 이 시장의 성장을 촉진하고 있습니다.

세계의 헬스케어 산업용 부정 애널리틱스 시장을 조사했으며, 시장의 정의와 개요, 시장 기회·시장 동향, 시장 영향요인 분석, 시장 규모의 추이·예측, 각종 구분·지역별 상세 분석, 경쟁 구도, 주요 기업의 개요 등을 정리하여 전해드립니다.

목차

제1장 조사 방법

제2장 조사의 목적

제3장 조사 프로세스

제4장 조사 대상·조사 범위

제5장 리포트 전제·주기

제6장 시장 개요

제7장 중요 인사이트

제8장 서론

제9장 시장 기회·시장 동향

  • ICT에 대한 투자
  • 첨단 기술이 부정으로부터 지키는 큰 가능성을 제공
  • 헬스케어 산업 부정 탐지용 AI

제10장 시장 성장 실현 요인

  • 헬스케어 산업에서 부정의 증가
  • 의료보험 혜택을 받는 환자 수의 증가
  • 약국 청구 관련 부정 건수의 증가

제11장 시장 억제요인

  • 부정 패턴의 변화
  • 부정 애널리틱스 솔루션에 의한 보안 & 프라이버시상의 리스크
  • 도입 소요 시간과 빈번한 업그레이드의 필요성

제12장 시장 구도

  • 시장 개요
  • 시장 규모·예측
  • Five forces 분석

제13장 솔루션 유형

  • 시장 스냅숏·성장 엔진
  • 시장 개요
  • 기술적 분석
  • 예측적 분석
  • 처방적 분석

제14장 딜리버리 모드

  • 시장 스냅숏·성장 엔진
  • 시장 개요
  • 온프레미스
  • 클라우드

제15장 용도

  • 시장 스냅숏·성장 엔진
  • 시장 개요
  • 의료 제공자에 의한 부정
  • 환자에 의한 부정
  • 처방에 관한 부정
  • 헬스케어 관련 일반적 부정

제16장 최종사용자

  • 시장 스냅숏·성장 엔진
  • 시장 개요
  • 공적 건강보험 회사
  • 민간 의료보험 회사
  • 서드파티서비스프로바이다
  • 기타

제17장 지역

  • 시장 스냅숏·성장 엔진
  • 지역적 개요

제18장 북미

제19장 유럽

제20장 아시아태평양

제21장 라틴아메리카

제22장 중동 및 아프리카

제23장 경쟁 구도

  • 경쟁 개요
  • 시장 점유율 분석

제24장 주요 기업 개요

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

제25장 기타 유력 벤더

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

제26장 리포트 개요

  • 주요 포인트
  • 전략적 제안

제27장 정량적 요약

제28장 부록

KSA 23.05.25

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
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