Global Big Data in the Financial Service Market
Global Big Data in the Financial Service Market

Big Data in the Financial Service Comprehensive Study by Application (Banks, Insurers, Asset Management Firms, Other), Organization Size (SMEs, Large Enterprises), Component (Hardware, Software, Service) Players and Region - Global Market Outlook to 2025

Big Data in the Financial Service Market Segmented into XX Submarkets. | Forecast Years: 2020- 2025  

Aug 2020 Edition 216 Pages 214 Tables & Figures
  • Summary
  • Market Segments
  • Table of Content
  • List of Tables & Figures
  • Companies Mentioned
Big Data in the Financial Service Market Scope
Big data in finance refers to the petabytes of structured and unstructured data that can be used to anticipate customer behaviors and create strategies for banks and financial institutions. There are several uses of big data in the financial industry. Most significantly, big data is used for risk management. Big data helps analyze customer behavior and provide deep insights. It assesses the risks of identity frauds, card frauds, and insurance frauds and reacts to them instantaneously. Big data technologies monitor customer behavior and identify fraudulent transactions as soon as they stray away from the customers’ pattern. Big data is also used in credit risk and liquidity risk management. The analysis of data provides insights on cash flow to manage the liquidity more efficiently, while the data regarding customer’s transaction history, payments history, public information, and IoT data helps to manage credit risk for the lending organizations.

The market study is segmented, by Application (Banks, Insurers, Asset Management Firms and Other) and major geographies with country level break-up.

Research Analyst at AMA estimates that United States Players will contribute to the maximum growth of Global Big Data in the Financial Service market throughout the predicted period.

Microsoft (United States), Google (United States), SAP (Germany), Teradata (United States), Accenture (Pragsis Bidoop) (Ireland), IBM (United States), Cisco (United States), Oracle (United States), Amazon (AWS) (United States), Adobe (United States), e-Zest Solutions (India) and Datameer (United States) are some of the key players that are part of study coverage. Additionally, the Players which are also part of the research are Clairvoyant (United States), HP Enterprise (United States), Dell EMC (United States), VMware (United States) and Cogito (United States).

About Approach
The research aims to propose a patent-based approach in searching for potential technology partners as a supporting tool for enabling open innovation. The study also proposes a systematic searching process of technology partners as a
preliminary step to select the emerging and key players that are involved in implementing market estimations. While patent analysis is employed to overcome the aforementioned data- and process-related limitations, as expenses occurred in that technology allows us to estimate the market size by evolving segments as target market from total available market.

Segmentation Overview
AdvanceMarketAnalytics has segmented the market of Global Big Data in the Financial Service market by Type, Application and Region.

On the basis of geography, the market of Big Data in the Financial Service has been segmented into South America (Brazil, Argentina, Rest of South America), Asia Pacific (China, Japan, India, South Korea, Taiwan, Australia, Rest of Asia-Pacific), Europe (Germany, France, Italy, United Kingdom, Netherlands, Rest of Europe), MEA (Middle East, Africa), North America (United States, Canada, Mexico).

On 27 Nov 2018, Hewlett Packard Enterprise, announced a definitive agreement to purchase BlueData, a leading provider of software that transforms how enterprises deploy artificial intelligence and big data analytics, expanding HPE's offerings in these rapidly growing markets.


Market Trend
  • Financial Services Turning To IoT and Streaming
  • Big Data and Blockchain Move Forward In Financial Services
  • Customer Analytics Are Driving Big Data Initiatives

Market Drivers
  • Change in customer behavior and expectations
  • Technological evolutions leading to larger amounts of input data
  • Competition of Fintech players using already Big Data techniques for new financial services
  • Increased Regulatory Pressure Driving the Adoption of Big Data Technologies in the Financial Sector
  • Technological Evolutions to Support the Processing Of Huge Amounts of Complex and Diverse Data in Real-Time

Opportunities
  • The Growing Demand from Emerging Economies

Restraints
  • Regulatory Requirements
  • Data Security Hampers the Adoption of the Big Data

Challenges
  • Complexity to Manage Big Data in the Financial Services
  • High Cost of the Big Data Technologies


Key Target Audience
Big Data in the Financial Service Companies, Potential Investors, Regulatory & Government Bodies, End Users and Others

Customization available in this Study:
The Study can be customized to meet your requirements. Please connect with our representative, who will ensure you get a report that suits your needs.
Data related to EXIM [Export- Import], production & consumption by country or regional level break-up can be provided based on client request**
** Confirmation on availability of data would be informed prior purchase
Report Objectives / Segmentation Covered
By Application
  • Banks
  • Insurers
  • Asset Management Firms
  • Other
By Organization Size
  • SMEs
  • Large Enterprises

By Component
  • Hardware
  • Software
  • Service

By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Taiwan
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • Italy
    • United Kingdom
    • Netherlands
    • Rest of Europe
  • MEA
    • Middle East
    • Africa
  • North America
    • United States
    • Canada
    • Mexico
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. Change in customer behavior and expectations
      • 3.2.2. Technological evolutions leading to larger amounts of input data
      • 3.2.3. Competition of Fintech players using already Big Data techniques for new financial services
      • 3.2.4. Increased Regulatory Pressure Driving the Adoption of Big Data Technologies in the Financial Sector
      • 3.2.5. Technological Evolutions to Support the Processing Of Huge Amounts of Complex and Diverse Data in Real-Time
    • 3.3. Market Challenges
      • 3.3.1. Complexity to Manage Big Data in the Financial Services
      • 3.3.2. High Cost of the Big Data Technologies
    • 3.4. Market Trends
      • 3.4.1. Financial Services Turning To IoT and Streaming
      • 3.4.2. Big Data and Blockchain Move Forward In Financial Services
      • 3.4.3. Customer Analytics Are Driving Big Data Initiatives
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global Big Data in the Financial Service, by Application, Organization Size, Component and Region (value) (2014-2019)
    • 5.1. Introduction
    • 5.2. Global Big Data in the Financial Service (Value)
      • 5.2.1. Global Big Data in the Financial Service by: Application (Value)
        • 5.2.1.1. Banks
        • 5.2.1.2. Insurers
        • 5.2.1.3. Asset Management Firms
        • 5.2.1.4. Other
      • 5.2.2. Global Big Data in the Financial Service by: Organization Size (Value)
        • 5.2.2.1. SMEs
        • 5.2.2.2. Large Enterprises
      • 5.2.3. Global Big Data in the Financial Service by: Component (Value)
        • 5.2.3.1. Hardware
        • 5.2.3.2. Software
        • 5.2.3.3. Service
      • 5.2.4. Global Big Data in the Financial Service Region
        • 5.2.4.1. South America
          • 5.2.4.1.1. Brazil
          • 5.2.4.1.2. Argentina
          • 5.2.4.1.3. Rest of South America
        • 5.2.4.2. Asia Pacific
          • 5.2.4.2.1. China
          • 5.2.4.2.2. Japan
          • 5.2.4.2.3. India
          • 5.2.4.2.4. South Korea
          • 5.2.4.2.5. Taiwan
          • 5.2.4.2.6. Australia
          • 5.2.4.2.7. Rest of Asia-Pacific
        • 5.2.4.3. Europe
          • 5.2.4.3.1. Germany
          • 5.2.4.3.2. France
          • 5.2.4.3.3. Italy
          • 5.2.4.3.4. United Kingdom
          • 5.2.4.3.5. Netherlands
          • 5.2.4.3.6. Rest of Europe
        • 5.2.4.4. MEA
          • 5.2.4.4.1. Middle East
          • 5.2.4.4.2. Africa
        • 5.2.4.5. North America
          • 5.2.4.5.1. United States
          • 5.2.4.5.2. Canada
          • 5.2.4.5.3. Mexico
  • 6. Big Data in the Financial Service: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
        • 6.1.1.1. Top 3
        • 6.1.1.2. Top 5
    • 6.2. Peer Group Analysis (2019)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Microsoft (United States)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
      • 6.4.2. Google (United States)
        • 6.4.2.1. Business Overview
        • 6.4.2.2. Products/Services Offerings
        • 6.4.2.3. Financial Analysis
        • 6.4.2.4. SWOT Analysis
      • 6.4.3. SAP (Germany)
        • 6.4.3.1. Business Overview
        • 6.4.3.2. Products/Services Offerings
        • 6.4.3.3. Financial Analysis
        • 6.4.3.4. SWOT Analysis
      • 6.4.4. Teradata (United States)
        • 6.4.4.1. Business Overview
        • 6.4.4.2. Products/Services Offerings
        • 6.4.4.3. Financial Analysis
        • 6.4.4.4. SWOT Analysis
      • 6.4.5. Accenture (Pragsis Bidoop) (Ireland)
        • 6.4.5.1. Business Overview
        • 6.4.5.2. Products/Services Offerings
        • 6.4.5.3. Financial Analysis
        • 6.4.5.4. SWOT Analysis
      • 6.4.6. IBM (United States)
        • 6.4.6.1. Business Overview
        • 6.4.6.2. Products/Services Offerings
        • 6.4.6.3. Financial Analysis
        • 6.4.6.4. SWOT Analysis
      • 6.4.7. Cisco (United States)
        • 6.4.7.1. Business Overview
        • 6.4.7.2. Products/Services Offerings
        • 6.4.7.3. Financial Analysis
        • 6.4.7.4. SWOT Analysis
      • 6.4.8. Oracle (United States)
        • 6.4.8.1. Business Overview
        • 6.4.8.2. Products/Services Offerings
        • 6.4.8.3. Financial Analysis
        • 6.4.8.4. SWOT Analysis
      • 6.4.9. Amazon (AWS) (United States)
        • 6.4.9.1. Business Overview
        • 6.4.9.2. Products/Services Offerings
        • 6.4.9.3. Financial Analysis
        • 6.4.9.4. SWOT Analysis
      • 6.4.10. Adobe (United States)
        • 6.4.10.1. Business Overview
        • 6.4.10.2. Products/Services Offerings
        • 6.4.10.3. Financial Analysis
        • 6.4.10.4. SWOT Analysis
      • 6.4.11. E-Zest Solutions (India)
        • 6.4.11.1. Business Overview
        • 6.4.11.2. Products/Services Offerings
        • 6.4.11.3. Financial Analysis
        • 6.4.11.4. SWOT Analysis
      • 6.4.12. Datameer (United States)
        • 6.4.12.1. Business Overview
        • 6.4.12.2. Products/Services Offerings
        • 6.4.12.3. Financial Analysis
        • 6.4.12.4. SWOT Analysis
  • 7. Global Big Data in the Financial Service Sale, by Application, Organization Size, Component and Region (value) (2020-2025)
    • 7.1. Introduction
    • 7.2. Global Big Data in the Financial Service (Value)
      • 7.2.1. Global Big Data in the Financial Service by: Application (Value)
        • 7.2.1.1. Banks
        • 7.2.1.2. Insurers
        • 7.2.1.3. Asset Management Firms
        • 7.2.1.4. Other
      • 7.2.2. Global Big Data in the Financial Service by: Organization Size (Value)
        • 7.2.2.1. SMEs
        • 7.2.2.2. Large Enterprises
      • 7.2.3. Global Big Data in the Financial Service by: Component (Value)
        • 7.2.3.1. Hardware
        • 7.2.3.2. Software
        • 7.2.3.3. Service
      • 7.2.4. Global Big Data in the Financial Service Region
        • 7.2.4.1. South America
          • 7.2.4.1.1. Brazil
          • 7.2.4.1.2. Argentina
          • 7.2.4.1.3. Rest of South America
        • 7.2.4.2. Asia Pacific
          • 7.2.4.2.1. China
          • 7.2.4.2.2. Japan
          • 7.2.4.2.3. India
          • 7.2.4.2.4. South Korea
          • 7.2.4.2.5. Taiwan
          • 7.2.4.2.6. Australia
          • 7.2.4.2.7. Rest of Asia-Pacific
        • 7.2.4.3. Europe
          • 7.2.4.3.1. Germany
          • 7.2.4.3.2. France
          • 7.2.4.3.3. Italy
          • 7.2.4.3.4. United Kingdom
          • 7.2.4.3.5. Netherlands
          • 7.2.4.3.6. Rest of Europe
        • 7.2.4.4. MEA
          • 7.2.4.4.1. Middle East
          • 7.2.4.4.2. Africa
        • 7.2.4.5. North America
          • 7.2.4.5.1. United States
          • 7.2.4.5.2. Canada
          • 7.2.4.5.3. Mexico
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. Big Data in the Financial Service: by Application(USD Million)
  • Table 2. Big Data in the Financial Service Banks , by Region USD Million (2014-2019)
  • Table 3. Big Data in the Financial Service Insurers , by Region USD Million (2014-2019)
  • Table 4. Big Data in the Financial Service Asset Management Firms , by Region USD Million (2014-2019)
  • Table 5. Big Data in the Financial Service Other , by Region USD Million (2014-2019)
  • Table 6. Big Data in the Financial Service: by Organization Size(USD Million)
  • Table 7. Big Data in the Financial Service SMEs , by Region USD Million (2014-2019)
  • Table 8. Big Data in the Financial Service Large Enterprises , by Region USD Million (2014-2019)
  • Table 9. Big Data in the Financial Service: by Component(USD Million)
  • Table 10. Big Data in the Financial Service Hardware , by Region USD Million (2014-2019)
  • Table 11. Big Data in the Financial Service Software , by Region USD Million (2014-2019)
  • Table 12. Big Data in the Financial Service Service , by Region USD Million (2014-2019)
  • Table 13. South America Big Data in the Financial Service, by Country USD Million (2014-2019)
  • Table 14. South America Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 15. South America Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 16. South America Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 17. Brazil Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 18. Brazil Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 19. Brazil Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 20. Argentina Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 21. Argentina Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 22. Argentina Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 23. Rest of South America Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 24. Rest of South America Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 25. Rest of South America Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 26. Asia Pacific Big Data in the Financial Service, by Country USD Million (2014-2019)
  • Table 27. Asia Pacific Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 28. Asia Pacific Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 29. Asia Pacific Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 30. China Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 31. China Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 32. China Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 33. Japan Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 34. Japan Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 35. Japan Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 36. India Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 37. India Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 38. India Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 39. South Korea Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 40. South Korea Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 41. South Korea Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 42. Taiwan Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 43. Taiwan Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 44. Taiwan Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 45. Australia Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 46. Australia Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 47. Australia Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 48. Rest of Asia-Pacific Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 49. Rest of Asia-Pacific Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 50. Rest of Asia-Pacific Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 51. Europe Big Data in the Financial Service, by Country USD Million (2014-2019)
  • Table 52. Europe Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 53. Europe Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 54. Europe Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 55. Germany Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 56. Germany Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 57. Germany Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 58. France Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 59. France Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 60. France Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 61. Italy Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 62. Italy Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 63. Italy Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 64. United Kingdom Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 65. United Kingdom Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 66. United Kingdom Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 67. Netherlands Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 68. Netherlands Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 69. Netherlands Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 70. Rest of Europe Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 71. Rest of Europe Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 72. Rest of Europe Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 73. MEA Big Data in the Financial Service, by Country USD Million (2014-2019)
  • Table 74. MEA Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 75. MEA Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 76. MEA Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 77. Middle East Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 78. Middle East Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 79. Middle East Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 80. Africa Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 81. Africa Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 82. Africa Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 83. North America Big Data in the Financial Service, by Country USD Million (2014-2019)
  • Table 84. North America Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 85. North America Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 86. North America Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 87. United States Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 88. United States Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 89. United States Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 90. Canada Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 91. Canada Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 92. Canada Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 93. Mexico Big Data in the Financial Service, by Application USD Million (2014-2019)
  • Table 94. Mexico Big Data in the Financial Service, by Organization Size USD Million (2014-2019)
  • Table 95. Mexico Big Data in the Financial Service, by Component USD Million (2014-2019)
  • Table 96. Company Basic Information, Sales Area and Its Competitors
  • Table 97. Company Basic Information, Sales Area and Its Competitors
  • Table 98. Company Basic Information, Sales Area and Its Competitors
  • Table 99. Company Basic Information, Sales Area and Its Competitors
  • Table 100. Company Basic Information, Sales Area and Its Competitors
  • Table 101. Company Basic Information, Sales Area and Its Competitors
  • Table 102. Company Basic Information, Sales Area and Its Competitors
  • Table 103. Company Basic Information, Sales Area and Its Competitors
  • Table 104. Company Basic Information, Sales Area and Its Competitors
  • Table 105. Company Basic Information, Sales Area and Its Competitors
  • Table 106. Company Basic Information, Sales Area and Its Competitors
  • Table 107. Company Basic Information, Sales Area and Its Competitors
  • Table 108. Big Data in the Financial Service: by Application(USD Million)
  • Table 109. Big Data in the Financial Service Banks , by Region USD Million (2020-2025)
  • Table 110. Big Data in the Financial Service Insurers , by Region USD Million (2020-2025)
  • Table 111. Big Data in the Financial Service Asset Management Firms , by Region USD Million (2020-2025)
  • Table 112. Big Data in the Financial Service Other , by Region USD Million (2020-2025)
  • Table 113. Big Data in the Financial Service: by Organization Size(USD Million)
  • Table 114. Big Data in the Financial Service SMEs , by Region USD Million (2020-2025)
  • Table 115. Big Data in the Financial Service Large Enterprises , by Region USD Million (2020-2025)
  • Table 116. Big Data in the Financial Service: by Component(USD Million)
  • Table 117. Big Data in the Financial Service Hardware , by Region USD Million (2020-2025)
  • Table 118. Big Data in the Financial Service Software , by Region USD Million (2020-2025)
  • Table 119. Big Data in the Financial Service Service , by Region USD Million (2020-2025)
  • Table 120. South America Big Data in the Financial Service, by Country USD Million (2020-2025)
  • Table 121. South America Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 122. South America Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 123. South America Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 124. Brazil Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 125. Brazil Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 126. Brazil Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 127. Argentina Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 128. Argentina Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 129. Argentina Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 130. Rest of South America Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 131. Rest of South America Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 132. Rest of South America Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 133. Asia Pacific Big Data in the Financial Service, by Country USD Million (2020-2025)
  • Table 134. Asia Pacific Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 135. Asia Pacific Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 136. Asia Pacific Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 137. China Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 138. China Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 139. China Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 140. Japan Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 141. Japan Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 142. Japan Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 143. India Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 144. India Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 145. India Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 146. South Korea Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 147. South Korea Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 148. South Korea Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 149. Taiwan Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 150. Taiwan Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 151. Taiwan Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 152. Australia Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 153. Australia Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 154. Australia Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 155. Rest of Asia-Pacific Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 156. Rest of Asia-Pacific Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 157. Rest of Asia-Pacific Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 158. Europe Big Data in the Financial Service, by Country USD Million (2020-2025)
  • Table 159. Europe Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 160. Europe Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 161. Europe Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 162. Germany Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 163. Germany Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 164. Germany Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 165. France Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 166. France Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 167. France Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 168. Italy Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 169. Italy Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 170. Italy Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 171. United Kingdom Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 172. United Kingdom Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 173. United Kingdom Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 174. Netherlands Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 175. Netherlands Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 176. Netherlands Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 177. Rest of Europe Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 178. Rest of Europe Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 179. Rest of Europe Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 180. MEA Big Data in the Financial Service, by Country USD Million (2020-2025)
  • Table 181. MEA Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 182. MEA Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 183. MEA Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 184. Middle East Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 185. Middle East Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 186. Middle East Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 187. Africa Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 188. Africa Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 189. Africa Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 190. North America Big Data in the Financial Service, by Country USD Million (2020-2025)
  • Table 191. North America Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 192. North America Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 193. North America Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 194. United States Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 195. United States Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 196. United States Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 197. Canada Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 198. Canada Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 199. Canada Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 200. Mexico Big Data in the Financial Service, by Application USD Million (2020-2025)
  • Table 201. Mexico Big Data in the Financial Service, by Organization Size USD Million (2020-2025)
  • Table 202. Mexico Big Data in the Financial Service, by Component USD Million (2020-2025)
  • Table 203. Research Programs/Design for This Report
  • Table 204. Key Data Information from Secondary Sources
  • Table 205. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global Big Data in the Financial Service: by Application USD Million (2014-2019)
  • Figure 5. Global Big Data in the Financial Service: by Organization Size USD Million (2014-2019)
  • Figure 6. Global Big Data in the Financial Service: by Component USD Million (2014-2019)
  • Figure 7. South America Big Data in the Financial Service Share (%), by Country
  • Figure 8. Asia Pacific Big Data in the Financial Service Share (%), by Country
  • Figure 9. Europe Big Data in the Financial Service Share (%), by Country
  • Figure 10. MEA Big Data in the Financial Service Share (%), by Country
  • Figure 11. North America Big Data in the Financial Service Share (%), by Country
  • Figure 12. Global Big Data in the Financial Service share by Players 2019 (%)
  • Figure 13. Global Big Data in the Financial Service share by Players (Top 3) 2019(%)
  • Figure 14. Global Big Data in the Financial Service share by Players (Top 5) 2019(%)
  • Figure 15. BCG Matrix for key Companies
  • Figure 16. Microsoft (United States) Revenue, Net Income and Gross profit
  • Figure 17. Microsoft (United States) Revenue: by Geography 2019
  • Figure 18. Google (United States) Revenue, Net Income and Gross profit
  • Figure 19. Google (United States) Revenue: by Geography 2019
  • Figure 20. SAP (Germany) Revenue, Net Income and Gross profit
  • Figure 21. SAP (Germany) Revenue: by Geography 2019
  • Figure 22. Teradata (United States) Revenue, Net Income and Gross profit
  • Figure 23. Teradata (United States) Revenue: by Geography 2019
  • Figure 24. Accenture (Pragsis Bidoop) (Ireland) Revenue, Net Income and Gross profit
  • Figure 25. Accenture (Pragsis Bidoop) (Ireland) Revenue: by Geography 2019
  • Figure 26. IBM (United States) Revenue, Net Income and Gross profit
  • Figure 27. IBM (United States) Revenue: by Geography 2019
  • Figure 28. Cisco (United States) Revenue, Net Income and Gross profit
  • Figure 29. Cisco (United States) Revenue: by Geography 2019
  • Figure 30. Oracle (United States) Revenue, Net Income and Gross profit
  • Figure 31. Oracle (United States) Revenue: by Geography 2019
  • Figure 32. Amazon (AWS) (United States) Revenue, Net Income and Gross profit
  • Figure 33. Amazon (AWS) (United States) Revenue: by Geography 2019
  • Figure 34. Adobe (United States) Revenue, Net Income and Gross profit
  • Figure 35. Adobe (United States) Revenue: by Geography 2019
  • Figure 36. E-Zest Solutions (India) Revenue, Net Income and Gross profit
  • Figure 37. E-Zest Solutions (India) Revenue: by Geography 2019
  • Figure 38. Datameer (United States) Revenue, Net Income and Gross profit
  • Figure 39. Datameer (United States) Revenue: by Geography 2019
  • Figure 40. Global Big Data in the Financial Service: by Application USD Million (2020-2025)
  • Figure 41. Global Big Data in the Financial Service: by Organization Size USD Million (2020-2025)
  • Figure 42. Global Big Data in the Financial Service: by Component USD Million (2020-2025)
  • Figure 43. South America Big Data in the Financial Service Share (%), by Country
  • Figure 44. Asia Pacific Big Data in the Financial Service Share (%), by Country
  • Figure 45. Europe Big Data in the Financial Service Share (%), by Country
  • Figure 46. MEA Big Data in the Financial Service Share (%), by Country
  • Figure 47. North America Big Data in the Financial Service Share (%), by Country
Some of the key companies/manufacturers profiled in the report
  • Microsoft (United States)
  • Google (United States)
  • SAP (Germany)
  • Teradata (United States)
  • Accenture (Pragsis Bidoop) (Ireland)
  • IBM (United States)
  • Cisco (United States)
  • Oracle (United States)
  • Amazon (AWS) (United States)
  • Adobe (United States)
  • e-Zest Solutions (India)
  • Datameer (United States)
Additional players considered in the study are as follows:
Clairvoyant (United States) , HP Enterprise (United States) , Dell EMC (United States) , VMware (United States) , Cogito (United States)
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