ヘルスケア不正利用検知の世界市場予測(~2022年):種類別(記述的、規定的)、用途別(保険給付、前払い、後払い)、構成要素別(サービス、ソフトウェア)、デリバリー別(オンプレミス、クラウド)、エンドユーザー別(保険支払人、私的、公的)

【英語タイトル】Healthcare Fraud Detection Market by Type (Descriptive, Prescriptive), Application (Insurance Claim, Prepay, Post payment), Component (Service, Software), Delivery (On-premise, Cloud), End user (Insurance Payer, Private, Public) - Global Forecast to 2022

MarketsandMarketsが出版した調査資料(MAM-HIT-5868)・商品コード:MAM-HIT-5868
・発行会社(調査会社):MarketsandMarkets
・発行日:2018年1月8日
・ページ数:162
・レポート言語:英語
・レポート形式:PDF
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・調査対象地域:グローバル
・産業分野:医療IT
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・イントロダクション
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・ヘルスケア不正利用検知市場:構成要素別
・ヘルスケア不正利用検知市場:モデル別
・ヘルスケア不正利用検知市場:種類別
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・地域別分析
・競争状況
・企業プロファイル
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【レポートの概要】

“Global healthcare fraud detection market projected to grow at a CAGR of 28.9%”
The healthcare fraud detection market is expected to reach USD 2,242.7 million by 2022 from USD 631.0 million in 2017, at a CAGR of 28.9%. Factors such as the large number of fraudulent activities in healthcare; increasing number of patients seeking health insurance; the prepayment review model; growing pressure of fraud, waste, and abuse on healthcare spending; and high returns on investments are driving the growth of the healthcare fraud detection market. On the other hand, market growth is likely to be negatively affected by the dearth of skilled personnel and reluctance to adopt healthcare fraud analytics in emerging countries, are expected to limit the growth of this market to a certain extent.

“The prescriptive analytics segment is expected to grow at the highest CAGR during the forecast period”
By type, the healthcare fraud detection market is segmented into descriptive, predictive, and prescriptive analytics. The prescriptive analytics segment is expected grow at a highest CAGR during the forecast period. The high growth of this segment is attributed to the ability of prescriptive analytics to ensure the synergistic integration of predictions and prescriptions.

“The services segment is expected to dominate the market during the forecast period”
Based on component, the healthcare fraud detection market is segmented into services, software, and hardware. The services segment accounted for the largest share of the healthcare fraud detection market in 2016. With the increasing need for business analytics services and the introduction of technologically advanced healthcare fraud detection software, which requires extensive training to use as well as regular upgrades, the services segment is expected to grow at the highest CAGR during the forecast period.
“North America to witness high growth during the forecast period”
In 2017, North America is expected to account for the largest share of the market followed by Europe. This regional segment is expected to register the highest CAGR during the forecast period. Factors such as increase in the number of people seeking health insurance, increasing cases of healthcare fraud, favorable government initiatives to combat healthcare fraud, rising pressure to reduce healthcare costs, technological advancements, and greater product and service availability in this region are expected to drive market growth in North America.
The primary interviews conducted for this report can be categorized as follows:
? By Company Type: Tier 1 ? 33%; Tier 2 – 45%; Tier 3 – 22%.
? By Designation (Supply Side): C-level- 22%; D-level- 27%; others- 51%.
? By Region: North America-62%; Europe-13%; Asia-21%; South America- 3%, and Middle East & Africa- 1%.

List of companies profiled in the report
? IBM (US)
? Optum (US)
? SAS (US)
? McKesson (US)
? SCIO (US)
? Verscend (US)
? Wipro (India)
? Conduent (US)
? HCL (India)
? CGI (Canada)
? DXC (US)
? Northrop Grumman (US)
? LexisNexis (US)
? Pondera (US)
Research Coverage:
The report provides an overview of the healthcare fraud detection market. It aims at estimating the market size and future growth potential of this market across different segments such as type, application, component, delivery model, end user, and region. Furthermore, the report also includes an in-depth competitive analysis of the key players in the market along with their company profiles, recent developments, and key market strategies.

Key Benefits of Buying the Report:
The report will help the market leaders/new entrants in this market by providing them with the closest approximations of revenues for the overall healthcare fraud detection market and its subsegments. This report will help stakeholders to understand the competitive landscape better and gain insights to position their businesses and help companies make suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provide them with information regarding key market drivers and opportunities.

【レポートの目次】

TABLE OF CONTENTS

1 INTRODUCTION 15
1.1 OBJECTIVES OF THE STUDY 15
1.2 MARKET DEFINITION 15
1.3 MARKET SCOPE 16
1.3.1 MARKETS COVERED 16
1.3.2 YEARS CONSIDERED FOR THE STUDY 16
1.4 CURRENCY 17
1.5 LIMITATIONS 17
1.6 STAKEHOLDERS 17
2 RESEARCH METHODOLOGY 18
2.1 RESEARCH DATA 18
2.1.1 SECONDARY DATA 19
2.1.1.1 Secondary sources 19
2.1.2 PRIMARY DATA 20
2.1.2.1 Primary sources 20
2.1.2.2 Key industry insights 21
2.2 MARKET SIZE ESTIMATION 21
2.2.1 BOTTOM-UP APPROACH 22
2.2.2 TOP-DOWN APPROACH 22
2.3 MARKET BREAKDOWN AND DATA TRIANGULATION 24
2.4 ASSUMPTIONS FOR THE STUDY 25
3 EXECUTIVE SUMMARY 26
4 PREMIUM INSIGHTS 30
4.1 HEALTHCARE FRAUD DETECTION: MARKET OVERVIEW 30
4.2 HEALTHCARE FRAUD DETECTION, BY PRODUCT AND SERVICE 31
4.3 HEALTHCARE FRAUD DETECTION, BY TYPE 31
4.4 HEALTHCARE FRAUD DETECTION, BY DELIVERY MODEL 32
5 MARKET OVERVIEW 33
5.1 INTRODUCTION 33
5.2 MARKET DYNAMICS 33
5.2.1 DRIVERS 34
5.2.1.1 Large number of fraudulent activities in healthcare 34
5.2.1.2 Increasing number of patients seeking health insurance 34
5.2.1.3 Prepayment review model 34
5.2.1.4 Growing pressure of fraud, waste, and abuse on healthcare spending 35
5.2.1.5 High returns on investment 36
5.2.2 RESTRAINT 36
5.2.2.1 Reluctance to adopt healthcare fraud analytics in emerging countries 36
5.2.3 OPPORTUNITIES 37
5.2.3.1 Cloud-based analytics 37
5.2.3.2 Emergence of social media and its impact on the healthcare industry 37
5.2.3.3 AI in healthcare fraud detection 37
5.2.4 CHALLENGES 38
5.2.4.1 Dearth of skilled personnel 38
5.2.4.2 Time-consuming deployment and need for frequent upgrades 38
6 HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT 39
6.1 INTRODUCTION 40
6.2 SERVICES 41
6.3 SOFTWARE 43
7 FRAUD DETECTION MARKET, BY DELIVERY MODEL 46
7.1 INTRODUCTION 47
7.2 ON-PREMISE DELIVERY MODELS 48
7.3 ON-DEMAND DELIVERY MODELS 51
8 HEALTHCARE FRAUD DETECTION MARKET, BY TYPE 53
8.1 INTRODUCTION 54
8.2 DESCRIPTIVE ANALYTICS 55
8.3 PREDICTIVE ANALYTICS 58
8.4 PRESCRIPTIVE ANALYTICS 60
9 HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION 63
9.1 INTRODUCTION 64
9.2 INSURANCE CLAIMS REVIEW 65
9.2.1 POSTPAYMENT REVIEW 66
9.2.2 PREPAYMENT REVIEW 67
9.3 PAYMENT INTEGRITY 68
9.4 OTHER APPLICATIONS 69
10 HEALTHCARE FRAUD DETECTION MARKET, BY END USER 71
10.1 INTRODUCTION 72
10.2 PRIVATE INSURANCE PAYERS 73
10.3 PUBLIC/GOVERNMENT AGENCIES 74
10.4 THIRD-PARTY SERVICE PROVIDERS 76
10.5 EMPLOYERS 77
11 HEALTHCARE FRAUD DETECTION MARKET, BY REGION 78
11.1 INTRODUCTION 79
11.2 NORTH AMERICA 80
11.2.1 US 85
11.2.2 CANADA 88
11.3 EUROPE 91
11.3.1 GERMANY 95
11.3.2 UK 98
11.3.3 FRANCE 100
11.3.4 REST OF EUROPE 102
11.4 ASIA 104
11.5 REST OF THE WORLD (ROW) 108
12 COMPETITIVE LANDSCAPE 112
12.1 OVERVIEW 112
12.2 MARKET PLAYER RANKING, 2016 113
12.3 COMPETITIVE SCENARIO 115
12.3.1 AGREEMENTS, PARTNERSHIPS, COLLABORATIONS, AND CONTRACTS 115
12.3.2 EXPANSIONS 116
12.3.3 ACQUISITIONS 116
12.3.4 PRODUCT LAUNCHES 117
13 COMPANY PROFILES 118
(Overview, Products Offered, Product Offering Scorecard, Business Strategy Scorecard, Recent Developments)*

13.1 IBM 118
13.2 OPTUM (A PART OF UNITEDHEALTH GROUP) 122
13.3 VERSCEND TECHNOLOGIES 124
13.4 MCKESSON 126
13.5 FAIR ISAAC (FICO) 129
13.6 SAS INSTITUTE 132
13.7 SCIO HEALTH ANALYTICS 134
13.8 WIPRO 136
13.9 CONDUENT 138
13.10 HCL TECHNOLOGIES 140
13.11 CGI GROUP 142
13.12 DXC TECHNOLOGY 144
13.13 NORTHROP GRUMMAN 146
?
13.14 LEXINEXIS (A PART OF RELX GROUP) 148
13.15 PONDERA SOLUTIONS 150

*Details on MarketsandMarkets view, Overview, Products Offered, Product Offering Scorecard, Business Strategy Scorecard, and Recent Developments might not be captured in case of unlisted companies.
14 APPENDIX 151
14.1 INSIGHTS FROM INDUSTRY EXPERTS 151
14.2 DISCUSSION GUIDE 152
14.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 155
14.4 INTRODUCING RT: REAL-TIME MARKET INTELLIGENCE 157
14.5 AVAILABLE CUSTOMIZATIONS 158
14.6 RELATED REPORTS 159
14.7 AUTHOR DETAILS 160

LIST OF TABLES

TABLE 1 HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT,
2015?2022 (USD MILLION) 40
TABLE 2 HEALTHCARE FRAUD DETECTION SERVICES MARKET, BY REGION,
2015?2022 (USD MILLION) 41
TABLE 3 NORTH AMERICA: HEALTHCARE FRAUD DETECTION SERVICES MARKET,
BY COUNTRY, 2015?2022 (USD MILLION) 42
TABLE 4 EUROPE: HEALTHCARE FRAUD DETECTION SERVICES MARKET,
BY COUNTRY, 2015?2022 (USD MILLION) 42
TABLE 5 HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY REGION,
2015?2022 (USD MILLION) 44
TABLE 6 NORTH AMERICA: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY COUNTRY, 2015?2022 (USD MILLION) 44
TABLE 7 EUROPE: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY COUNTRY, 2015?2022 (USD MILLION) 45
TABLE 8 HEALTHCARE FRAUD DETECTION MARKET, BY DELIVERY MODEL,
2015?2022 (USD MILLION) 47
TABLE 9 HEALTHCARE FRAUD DETECTION MARKET FOR ON-PREMISE DELIVERY MODELS, BY REGION, 2015?2022 (USD MILLION) 49
TABLE 10 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR ON-PREMISE DELIVERY MODELS, BY COUNTRY, 2015?2022 (USD MILLION) 50
TABLE 11 EUROPE: HEALTHCARE FRAUD DETECTION MARKET FOR ON-PREMISE DELIVERY MODELS, BY COUNTRY, 2015?2022 (USD MILLION) 50
TABLE 12 HEALTHCARE FRAUD DETECTION MARKET FOR ON-DEMAND DELIVERY MODELS, BY REGION, 2015?2022 (USD MILLION) 51
TABLE 13 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR ON-DEMAND DELIVERY MODELS, BY COUNTRY, 2015?2022 (USD MILLION) 52
TABLE 14 EUROPE: HEALTHCARE FRAUD DETECTION MARKET FOR ON-DEMAND DELIVERY MODELS, BY COUNTRY, 2015?2022 (USD MILLION) 52
TABLE 15 HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015?2022 (USD MILLION) 54
TABLE 16 DESCRIPTIVE ANALYTICS MARKET, BY REGION, 2015?2022 (USD MILLION) 56
TABLE 17 NORTH AMERICA: DESCRIPTIVE ANALYTICS MARKET, BY COUNTRY,
2015?2022 (USD MILLION) 57
TABLE 18 EUROPE: DESCRIPTIVE ANALYTICS MARKET, BY COUNTRY,
2015?2022 (USD MILLION) 57
TABLE 19 PREDICTIVE ANALYTICS MARKET, BY REGION, 2015?2022 (USD MILLION) 59
TABLE 20 NORTH AMERICA: PREDICTIVE ANALYTICS MARKET, BY COUNTRY,
2015?2022 (USD MILLION) 59
TABLE 21 EUROPE: PREDICTIVE ANALYTICS MARKET, BY COUNTRY,
2015?2022 (USD MILLION) 60
TABLE 22 PRESCRIPTIVE ANALYTICS MARKET, BY REGION, 2015?2022 (USD MILLION) 61
TABLE 23 NORTH AMERICA: PRESCRIPTIVE ANALYTICS MARKET, BY COUNTRY,
2015?2022 (USD MILLION) 61
TABLE 24 EUROPE: PRESCRIPTIVE ANALYTICS MARKET, BY COUNTRY,
2015?2022 (USD MILLION) 62
TABLE 25 HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION,
2015?2022 (USD MILLION) 64
TABLE 26 HEALTHCARE FRAUD DETECTION MARKET FOR INSURANCE CLAIMS REVIEW,
BY TYPE, 2015?2022 (USD MILLION) 65
TABLE 27 HEALTHCARE FRAUD DETECTION MARKET FOR INSURANCE CLAIMS REVIEW,
BY REGION, 2015?2022 (USD MILLION) 66
TABLE 28 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR INSURANCE CLAIMS REVIEW, BY COUNTRY, 2015?2022 (USD MILLION) 66
TABLE 29 HEALTHCARE FRAUD DETECTION MARKET FOR POSTPAYMENT REVIEW,
BY REGION, 2015?2022 (USD MILLION) 67
TABLE 30 HEALTHCARE FRAUD DETECTION MARKET FOR PREPAYMENT REVIEW,
BY REGION, 2015?2022 (USD MILLION) 68
TABLE 31 HEALTHCARE FRAUD DETECTION MARKET FOR PAYMENT INTEGRITY,
BY REGION, 2015?2022 (USD MILLION) 69
TABLE 32 HEALTHCARE FRAUD DETECTION MARKET FOR OTHER APPLICATIONS,
BY REGION, 2015?2022 (USD MILLION) 70
TABLE 33 HEALTHCARE FRAUD DETECTION MARKET, BY END USER,
2015?2022 (USD MILLION) 72
TABLE 34 HEALTHCARE FRAUD DETECTION MARKET FOR PRIVATE INSURANCE PAYERS,
BY REGION, 2015?2022 (USD MILLION) 73
TABLE 35 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR PRIVATE INSURANCE PAYERS, BY COUNTRY, 2015?2022 (USD MILLION) 74
TABLE 36 HEALTHCARE FRAUD DETECTION MARKET FOR PUBLIC/GOVERNMENT AGENCIES, BY REGION, 2015?2022 (USD MILLION) 75
TABLE 37 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR PUBLIC/GOVERNMENT AGENCIES, BY COUNTRY, 2015?2022 (USD MILLION) 75
TABLE 38 HEALTHCARE FRAUD DETECTION MARKET FOR THIRD-PARTY SERVICE PROVIDERS, BY REGION, 2015?2022 (USD MILLION) 76
TABLE 39 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR THIRD-PARTY SERVICE PROVIDERS, BY COUNTRY, 2015?2022 (USD MILLION) 76
TABLE 40 HEALTHCARE FRAUD DETECTION MARKET FOR EMPLOYERS, BY REGION,
2015?2022 (USD MILLION) 77
TABLE 41 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR EMPLOYERS,
BY COUNTRY, 2015?2022 (USD MILLION) 77
TABLE 42 HEALTHCARE FRAUD DETECTION MARKET, BY REGION,
2015?2022 (USD MILLION) 79
TABLE 43 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET, BY COUNTRY,
2015?2022 (USD MILLION) 82
TABLE 44 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015?2022 (USD MILLION) 82
TABLE 45 NORTH AMERICA: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY DELIVERY MODEL, 2015?2022 (USD MILLION) 82
TABLE 46 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE,
2015?2022 (USD MILLION) 83
TABLE 47 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2015?2022 (USD MILLION) 83
TABLE 48 NORTH AMERICA: INSURANCE CLAIMS REVIEW MARKET, BY TYPE,
2015?2022 (USD MILLION) 84
TABLE 49 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET,
BY END USER, 2015?2022 (USD MILLION) 84
TABLE 50 US: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT,
2015?2022 (USD MILLION) 86
TABLE 51 US: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY DELIVERY MODEL, 2015?2022 (USD MILLION) 86
TABLE 52 US: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE,
2015?2022 (USD MILLION) 87
TABLE 53 US: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION,
2015?2022 (USD MILLION) 87
TABLE 54 US: INSURANCE CLAIMS REVIEW MARKET, BY TYPE, 2015?2022 (USD MILLION) 87
TABLE 55 US: HEALTHCARE FRAUD DETECTION MARKET, BY END USER,
2015?2022 (USD MILLION) 88
TABLE 56 CANADA: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT,
2015?2022 (USD MILLION) 89
TABLE 57 CANADA: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY DELIVERY MODEL, 2015?2022 (USD MILLION) 89
TABLE 58 CANADA: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE,
2015?2022 (USD MILLION) 89
TABLE 59 CANADA: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION,
2015?2022 (USD MILLION) 90
TABLE 60 CANADA: HEALTHCARE FRAUD DETECTION MARKET, BY END USER,
2015?2022 (USD MILLION) 90
TABLE 61 EUROPE: HEALTHCARE FRAUD DETECTION MARKET, BY COUNTRY,
2015?2022 (USD MILLION) 93
TABLE 62 EUROPE: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT,
2015?2022 (USD MILLION) 93
TABLE 63 EUROPE: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY DELIVERY MODEL, 2015?2022 (USD MILLION) 94
TABLE 64 EUROPE: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE,
2015?2022 (USD MILLION) 94
TABLE 65 EUROPE: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION,
2015?2022 (USD MILLION) 94
TABLE 66 EUROPE: HEALTHCARE FRAUD DETECTION MARKET, BY END USER,
2015?2022 (USD MILLION) 95
TABLE 67 GERMANY: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT,
2015?2022 (USD MILLION) 96
TABLE 68 GERMANY: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY DELIVERY MODEL, 2015?2022 (USD MILLION) 96
TABLE 69 GERMANY: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE,
2015?2022 (USD MILLION) 97
TABLE 70 GERMANY: HEALTHCARE FRAUD DETECTION MARKET, BY END USER,
2015?2022 (USD MILLION) 97
TABLE 71 UK: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT,
2015?2022 (USD MILLION) 98
TABLE 72 UK: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY DELIVERY MODEL, 2015?2022 (USD MILLION) 99
TABLE 73 UK: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE,
2015?2022 (USD MILLION) 99
TABLE 74 UK: HEALTHCARE FRAUD DETECTION MARKET, BY END USER,
2015?2022 (USD MILLION) 99
TABLE 75 FRANCE: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT,
2015?2022 (USD MILLION) 100
TABLE 76 FRANCE: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY DELIVERY MODEL, 2015?2022 (USD MILLION) 101
TABLE 77 FRANCE: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE,
2015?2022 (USD MILLION) 101
TABLE 78 FRANCE: HEALTHCARE FRAUD DETECTION MARKET, BY END USER,
2015?2022 (USD MILLION) 101
TABLE 79 ROE: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT,
2015?2022 (USD MILLION) 102
TABLE 80 ROE: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY DELIVERY MODEL, 2015?2022 (USD MILLION) 102
TABLE 81 ROE: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE,
2015?2022 (USD MILLION) 103
TABLE 82 ROE: HEALTHCARE FRAUD DETECTION MARKET, BY END USER,
2015?2022 (USD MILLION) 103
TABLE 83 ASIA: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT,
2015?2022 (USD MILLION) 106
TABLE 84 ASIA: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY DELIVERY MODEL, 2015?2022 (USD MILLION) 106
TABLE 85 ASIA: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE,
2015?2022 (USD MILLION) 106
TABLE 86 ASIA: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION,
2015?2022 (USD MILLION) 107
TABLE 87 ASIA: HEALTHCARE FRAUD DETECTION MARKET, BY END USER,
2015?2022 (USD MILLION) 107
TABLE 88 ROW: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT,
2015?2022 (USD MILLION) 110
TABLE 89 ROW: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET,
BY DELIVERY MODEL, 2015?2022 (USD MILLION) 110
TABLE 90 ROW: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE,
2015?2022 (USD MILLION) 110
TABLE 91 ROW: HEALTHCARE FRAUD DETECTION MARKET, BY END USER,
2015?2022 (USD MILLION) 111
TABLE 92 HEALTHCARE FRAUD DETECTION RANKING ANALYSIS, BY KEY PLAYER, 2016 113


LIST OF FIGURES

FIGURE 1 HEALTHCARE FRAUD DETECTION MARKET 16
FIGURE 2 RESEARCH DESIGN 18
FIGURE 3 BREAKDOWN OF PRIMARY INTERVIEWS: BY COMPANY TYPE, DESIGNATION, AND REGION 23
FIGURE 4 DATA TRIANGULATION 24
FIGURE 5 DESCRIPTIVE ANALYTICS SEGMENT TO DOMINATE THE MARKET, BY TYPE, DURING THE FORECAST PERIOD 26
FIGURE 6 SERVICES SEGMENT TO DOMINATE THE MARKET IN 2017 27
FIGURE 7 ON-DEMAND DELIVERY MODELS TO GROW AT THE HIGHEST RATE DURING THE FORECAST PERIOD 27
FIGURE 8 PRIVATE INSURANCE PAYERS SEGMENT TO HOLD THE LARGEST MARKET SHARE IN 2017 28
FIGURE 9 NORTH AMERICA TO HOLD THE LARGEST SHARE OF THE GLOBAL MARKET DURING 2017 TO 2022 29
FIGURE 10 LARGE NUMBER OF FRAUDULENT ACTIVITIES IN HEALTHCARE TO DRIVE THE GROWTH OF THE MARKET 30
FIGURE 11 SERVICES SEGMENT TO GROW AT THE HIGHEST CAGR OVER THE FORECAST PERIOD (2017 -2022) 31
FIGURE 12 PRESCRIPTIVE ANALYTICS TO WITNESS HIGH GROWTH RATE FROM 2017 TO 2022 31
FIGURE 13 ON-PREMISE MODELS TO ACCOUNT FOR THE LARGEST SHARE OF THE HEALTHCARE FRAUD DETECTION IN 2017 32
FIGURE 14 HEALTHCARE FRAUD DETECTION MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES 33
FIGURE 15 HEALTHCARE SPENDING AS A PERCENTAGE OF THE GDP, BY COUNTRY, 2015 35
FIGURE 16 SERVICES SEGMENT TO DOMINATE THE HEALTHCARE FRAUD DETECTION MARKET IN 2017 40
FIGURE 17 ON-DEMAND SEGMENT TO REGISTER HIGHEST GROWTH RATE DURING THE FORECAST PERIOD (2017?2022) 48
FIGURE 18 NORTH AMERICA TO DOMINATE THE GLOBAL HEALTHCARE FRAUD DETECTION MARKET FOR ON-PREMISE DELIVERY MODELS (2017?2022) 49
FIGURE 19 PRESCRIPTIVE ANALYTICS TO WITNESS HIGHEST GROWTH DURING THE FORECAST PERIOD 55
FIGURE 20 NORTH AMERICA IS EXPECTED TO DOMINATE THE GLOBAL DESCRIPTIVE ANALYTICS MARKET (2017?2022) 56
FIGURE 21 INSURANCE CLAIMS REVIEW SEGMENT TO DOMINATE THE HEALTHCARE FRAUD DETECTION MARKET IN 2017 64
FIGURE 22 PAYERS TO DOMINATE THE HEALTHCARE FRAUD DETECTION MARKET DURING THE FORECAST PERIOD 72
FIGURE 23 NORTH AMERICA TO WITNESS THE HIGHEST GROWTH IN THE HEALTHCARE FRAUD DETECTION MARKET DURING THE FORECAST PERIOD 79
FIGURE 24 NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET SNAPSHOT 81
FIGURE 25 EUROPE: HEALTHCARE FRAUD DETECTION MARKET SNAPSHOT 92
FIGURE 26 ASIA: HEALTHCARE FRAUD DETECTION MARKET SNAPSHOT 105
FIGURE 27 ROW: HEALTHCARE FRAUD DETECTION MARKET SNAPSHOT 109
FIGURE 28 MARKET EVOLUTION FRAMEWORK 113
FIGURE 29 IBM: COMPANY SNAPSHOT 118
FIGURE 30 MCKESSON: COMPANY SNAPSHOT 126
FIGURE 31 FICO: COMPANY SNAPSHOT 129
FIGURE 32 SAS INSTITUTE: COMPANY SNAPSHOT 132
FIGURE 33 WIPRO: COMPANY SNAPSHOT 136
FIGURE 34 CONDUENT: COMPANY SNAPSHOT 138
FIGURE 35 HCL: COMPANY SNAPSHOT 140
FIGURE 36 CGI GROUP: COMPANY SNAPSHOT 142
FIGURE 37 DXC TECHNOLOGY: COMPANY SNAPSHOT 144
FIGURE 38 NORTHROP GRUMMAN: COMPANY SNAPSHOT 146
FIGURE 39 RELX GROUP: COMPANY SNAPSHOT 148


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