Big Data in Global Financial Services Market 2021
The global big data market in financial services is expected to grow in the future due to increasing technological disruptions in the financial services space. Increase in the number of banking related frauds, rising bad loans, loan defaults etc. calls for better risk management as well as rise of new age Fintech companies offering specialized technical solutions in the financial domain have given serious competition to the existing financial firms. Thus, the big data analytics market is expected to witness a surge in demand as more banks and other financial institutions adopt big data analytics solutions to stay relevant in the fast-changing industry.
The objective of this research study is to understand the current big data market in financial services across the world and to estimate the growth rate for the next 5 years. The report covers detailed analysis of companies - value chain, financial performance, forecast, business strategy and SWOT analysis, which are involved in providing big data analytics solutions in the financial services domain and have presence across different regions of the world.
The global big data market in financial services is currently valued at USD XX billion. It is expected that the market will grow at a CAGR of 18.57% and will reach USD XX billion by the year 2021.
The end users of big data analytics in financial services are banks, brokerages, central institutions, government agencies, independent rating agencies and other financial institutions etc. Fraud detection, risk management and marketing insights are some of the major use cases for big data analytics in the financial services industry. Rising fraudulent activities, problem of bad loans (non-performing assets), rising competition from Fintech firms and digital disruption are the key factors which will drive the growth of this industry.
This report concludes by analyzing the industry through PESTLE, porter’s 5 forces and SWOT analysis, discusses the challenges faced by the new players entering the industry and present and future trends observed. Strategic recommendations are also discussed separately and in detail for policy maker, end users, service providers and investors in the report.
Scope of Report
The objective of this research study is to understand the current big data market in financial services across the world and to estimate the growth rate for the next 5 years. The report covers detailed analysis of companies - value chain, financial performance, forecast, business strategy and SWOT analysis, which are involved in providing big data analytics solutions in the financial services domain and have presence across different regions of the world.
The global big data market in financial services is currently valued at USD XX billion. It is expected that the market will grow at a CAGR of 18.57% and will reach USD XX billion by the year 2021.
The end users of big data analytics in financial services are banks, brokerages, central institutions, government agencies, independent rating agencies and other financial institutions etc. Fraud detection, risk management and marketing insights are some of the major use cases for big data analytics in the financial services industry. Rising fraudulent activities, problem of bad loans (non-performing assets), rising competition from Fintech firms and digital disruption are the key factors which will drive the growth of this industry.
This report concludes by analyzing the industry through PESTLE, porter’s 5 forces and SWOT analysis, discusses the challenges faced by the new players entering the industry and present and future trends observed. Strategic recommendations are also discussed separately and in detail for policy maker, end users, service providers and investors in the report.
Scope of Report
- This report provides a detailed view of global big data market with the current market value as well as projections for future market potential and growth rate.
- This report identifies the need for big data analytics in financial services.
- This report provides detailed information on the value chain as well as the different market segments and their segment wise market share and growth potential.
- This report provides detailed information on region wise growth forecasts for big data market in financial services globally by 2021.
- This report identifies the growth drivers and inhibitors for big data market in financial services globally.
- This study also identifies policies related to big data in financial services market globally.
- This report identifies various credit, policy and technical risks associated with big data in financial services market globally.
- This report has detailed profiles of 4 key players in the world in big data analytics industry covering their business strategy, financial performance, future forecasts and SWOT analysis
- This report covers in detail the competitive landscape in detail of global big data in financial services market.
- This report provides PESTLE (political, economic, social, technological, legal and environmental) analysis for global big data in financial services market.
- This report provides porters five forces analysis for global big data in financial services market
- This report provides SWOT (strength, weaknesses, opportunities, threats) analysis for global big data in financial services market
1. EXECUTIVE SUMMARY
1.1 Research Objectives
1.2 Research Methodology
1.3 Key Findings
1.4 Scope of Report
2. NEED FOR BIG DATA IN FINANCIAL SERVICES INDUSTRY
2.1 Commercial Banking
2.2 Marketing
2.3 Fraud and Operations
2.4 Governance, Risk & Compliance
2.5 Capital Markets
2.6 Payments & Transactions
3. BIG DATA INDUSTRY VALUE CHAIN
3.1 Big Data Consultants
3.2 Infrastructure Providers (Sensors, Storage, H/W, Network Providers etc.)
3.3 Technology Enablers (Data Warehousing and Database Providers)
3.4 Big Data Analytics Providers
3.5 End Users
4. GLOBAL BIG DATA MARKET FORECAST TILL 2021
4.1 Overall Forecast for Global Big Data Market till 2021
4.2 Overall Forecast for Global Big Data Market in Financial Services till 2021
4.3 Asia Pacific Big Data Market in Financial Services Industry till 2021
4.4 North America Big Data Market in Financial Services Industry till 2021
4.5 Europe Big Data Market in Financial Services Industry till 2021
4.6 Latin & South America Big Data Market in Financial Services Industry till 2021
4.7 Middle East & Africa Big Data Market in Financial Services Industry till 2021
5. GROWTH DRIVERS AND INHIBITORS FOR GLOBAL BIG DATA MARKET IN FINANCIAL SERVICES
5.1 Growth Drivers
5.1.1 Greater need to assess credit risk, fraud detection & prevention
5.1.2 Increased regulatory and compliance requirements
5.1.3 Rising cost of data systems as a percentage of IT spending
5.1.4 Competition from new age Fintech firms
5.1.5 Consumer demand for customized services
5.2 Growth Inhibitors
5.2.1 Data Silos – Data is not pooled for the benefit of the organization
5.2.2 Unstructured data, high cost of data storage & analysis
5.2.3 Lack of Strategic Focus
5.2.4 Legacy Infrastructure
5.2.5 Shortage of skilled workforce
6. PROFILE OF KEY BIG DATA PLAYERS IN FINANCIAL SERVICES
6.1 Teradata
6.1.1 Company Profile
6.1.2 Teradata in Big Data Value Chain
6.1.3 Financial Performance of Teradata
6.1.4 Business Strategy
6.1.5 SWOT Analysis for Teradata
Strengths
Weaknesses
Opportunities
Threats
6.2 Informatica
6.2.1 Company Profile
6.2.2. Informatica Value Chain
6.2.3 Financial Performance of Informatica
6.2.4 Business Strategy
6.2.5 SWOT Analysis for Informatica
Strengths
Weaknesses
Opportunities
Threats
6.3 Hortonworks
6.3.1 Company Profile
6.3.2 Hortonworks in the Big Data Industry Value Chain
6.3.3 Financial Performance of Hortonworks
6.3.4 Business Strategy
6.3.5 SWOT Analysis for Hortonworks
Strengths
Weaknesses
Opportunities
Threats
6.4 SAS
6.4.1 Company Profile
6.4.2 SAS in Big Data Industry Value Chain
6.4.3 Financial Performance of SAS
6.4.4 Business Strategy
6.4.5 SWOT Analysis for SAS
Strengths
Weaknesses
Opportunities
Threats
7. CASE STUDY
7.1 How Big Data Analytics is revolutionizing the Financial Services
8. ANALYSIS MODELS
8.1 PESTLE Analysis
8.1.1 Political
8.1.2 Economic
8.1.3 Social
8.1.4 Technological
8.1.5 Legal
8.1.6 Environmental
8.2 Porter’s Five Forces
Threat of New Entrants
Bargaining Power of Suppliers
Bargaining Power of Buyers
Rivalry among Existing Firms
Threat of Substitutes
8.3 SWOT Analysis
Strengths
Weaknesses
Opportunities
Threats
9. MARKET OPPORTUNITY
9.1 Big Data Analytics in Financial Services
9.2 Fraud Detection and Management in Financial Services
9.3 Risk Management in Financial Services
9.4 Improving Customer Engagement
10. STRATEGIC RECOMMENDATIONS
10.1 For Financial Services Firms
10.2 For Big Data Service Providers
11. APPENDIX
Questionnaire design
1.1 Research Objectives
1.2 Research Methodology
1.3 Key Findings
1.4 Scope of Report
2. NEED FOR BIG DATA IN FINANCIAL SERVICES INDUSTRY
2.1 Commercial Banking
2.2 Marketing
2.3 Fraud and Operations
2.4 Governance, Risk & Compliance
2.5 Capital Markets
2.6 Payments & Transactions
3. BIG DATA INDUSTRY VALUE CHAIN
3.1 Big Data Consultants
3.2 Infrastructure Providers (Sensors, Storage, H/W, Network Providers etc.)
3.3 Technology Enablers (Data Warehousing and Database Providers)
3.4 Big Data Analytics Providers
3.5 End Users
4. GLOBAL BIG DATA MARKET FORECAST TILL 2021
4.1 Overall Forecast for Global Big Data Market till 2021
4.2 Overall Forecast for Global Big Data Market in Financial Services till 2021
4.3 Asia Pacific Big Data Market in Financial Services Industry till 2021
4.4 North America Big Data Market in Financial Services Industry till 2021
4.5 Europe Big Data Market in Financial Services Industry till 2021
4.6 Latin & South America Big Data Market in Financial Services Industry till 2021
4.7 Middle East & Africa Big Data Market in Financial Services Industry till 2021
5. GROWTH DRIVERS AND INHIBITORS FOR GLOBAL BIG DATA MARKET IN FINANCIAL SERVICES
5.1 Growth Drivers
5.1.1 Greater need to assess credit risk, fraud detection & prevention
5.1.2 Increased regulatory and compliance requirements
5.1.3 Rising cost of data systems as a percentage of IT spending
5.1.4 Competition from new age Fintech firms
5.1.5 Consumer demand for customized services
5.2 Growth Inhibitors
5.2.1 Data Silos – Data is not pooled for the benefit of the organization
5.2.2 Unstructured data, high cost of data storage & analysis
5.2.3 Lack of Strategic Focus
5.2.4 Legacy Infrastructure
5.2.5 Shortage of skilled workforce
6. PROFILE OF KEY BIG DATA PLAYERS IN FINANCIAL SERVICES
6.1 Teradata
6.1.1 Company Profile
6.1.2 Teradata in Big Data Value Chain
6.1.3 Financial Performance of Teradata
6.1.4 Business Strategy
6.1.5 SWOT Analysis for Teradata
Strengths
Weaknesses
Opportunities
Threats
6.2 Informatica
6.2.1 Company Profile
6.2.2. Informatica Value Chain
6.2.3 Financial Performance of Informatica
6.2.4 Business Strategy
6.2.5 SWOT Analysis for Informatica
Strengths
Weaknesses
Opportunities
Threats
6.3 Hortonworks
6.3.1 Company Profile
6.3.2 Hortonworks in the Big Data Industry Value Chain
6.3.3 Financial Performance of Hortonworks
6.3.4 Business Strategy
6.3.5 SWOT Analysis for Hortonworks
Strengths
Weaknesses
Opportunities
Threats
6.4 SAS
6.4.1 Company Profile
6.4.2 SAS in Big Data Industry Value Chain
6.4.3 Financial Performance of SAS
6.4.4 Business Strategy
6.4.5 SWOT Analysis for SAS
Strengths
Weaknesses
Opportunities
Threats
7. CASE STUDY
7.1 How Big Data Analytics is revolutionizing the Financial Services
8. ANALYSIS MODELS
8.1 PESTLE Analysis
8.1.1 Political
8.1.2 Economic
8.1.3 Social
8.1.4 Technological
8.1.5 Legal
8.1.6 Environmental
8.2 Porter’s Five Forces
Threat of New Entrants
Bargaining Power of Suppliers
Bargaining Power of Buyers
Rivalry among Existing Firms
Threat of Substitutes
8.3 SWOT Analysis
Strengths
Weaknesses
Opportunities
Threats
9. MARKET OPPORTUNITY
9.1 Big Data Analytics in Financial Services
9.2 Fraud Detection and Management in Financial Services
9.3 Risk Management in Financial Services
9.4 Improving Customer Engagement
10. STRATEGIC RECOMMENDATIONS
10.1 For Financial Services Firms
10.2 For Big Data Service Providers
11. APPENDIX
Questionnaire design
LIST OF EXHIBITS
Notes
Company Information
LIST OF EXHIBITS
Exhibit 3.2.1 Global Big Data Industry Value Chain
Exhibit 4.1 Forecast of global big data market 2017-21
Exhibit 4.2 Forecast of global big data market in financial services 2017-21
Exhibit 4.3 Percentage share of various geographies in global big data market in financial
Exhibit 4.4 Geography wise growth forecast in global big data market in financial services
Exhibit 4.5 Forecast of Asia Pacific big data market in financial services (Billion Dollar)
Exhibit 4.6 Forecast of North American big data Market in financial services 2017-21(Billion Dollar)
Exhibit 4.7 Forecast of European big data market in financial services 2017-21(Billion Dollar)
Exhibit 4.8 Forecast of LASA big data market in financial services 2017-21 (Billion Dollar)
Exhibit 4.9 Forecast of MENA big data market in financial services 2017-21 (Billion Dollar)
Exhibit 5.1 Growth Drivers and Inhibitors for Global Big Data Market in Financial Services
Exhibit 6.1.1 Company Profile – Teradata
Exhibit 6.1.2 Contact Details – Teradata
Exhibit 6.1.3 Teradata in Big Data Industry Value Chain
Exhibit 6.1.4 Teradata Revenue from 2011-12 to 2015-16 (in Million Dollar)
Exhibit 6.1.5 Year-wise Teradata Revenue Growth from 2011-12 to 2015-16 (in %)
Exhibit 6.1.6 Estimated Teradata in Revenue from 2016-17 to 2020-21 (in Million Dollar)
Exhibit 6.1.7 Estimated Year-wise Teradata Revenue Growth from 2016-17 to 2020-21 (in %)
Exhibit 6.1.8 SWOT Analysis of Teradata
Exhibit 6.2.1 Company Profile – Informatica
Exhibit 6.2.2 Contact Details – Informatica
Exhibit 6.2.3 Informatica in Big Data Industry Value Chain
Exhibit 6.2.4 Informatica Revenue from 2011-12 to 2015-16 (in Million Dollar)
Exhibit 6.2.5 Year-wise Informatica Revenue Growth from 2011-12 to 2015-16 (in %)
Exhibit 6.2.6 Estimated Informatica in Revenue from 2016-17 to 2020-21 (in Million Dollar)
Exhibit 6.2.7 Estimated Year-wise Informatica Revenue Growth from 2016-17 to 2020-21 (in %)
Exhibit 6.2.8 SWOT Analysis of Informatica
Exhibit 6.3.1 Company Profile – Hortonworks
Exhibit 6.3.2 Contact Details – Hortonworks
Exhibit 6.3.3 Hortonworks in Big Data Industry Value Chain
Exhibit 6.3.4 Hortonworks Revenue from 2011-12 to 2015-16 (in Million Dollar)
Exhibit 6.3.5 Year-wise Hortonworks Revenue Growth from 2011-12 to 2015-16 (in %)
Exhibit 6.3.6 Estimated Hortonworks in Revenue from 2016-17 to 2020-21 (in Million Dollar)
Exhibit 6.3.7 Estimated Year-wise Hortonworks Revenue Growth from 2016-17 to 2020-21 (in %)
Exhibit 6.3.8 SWOT Analysis of Hortonworks
Exhibit 6.4.1 Company Profile – SAS
Exhibit 6.4.2 Contact Details – SAS
Exhibit 6.4.3 SAS in Big Data Industry Value Chain
Exhibit 6.4.4 SAS Revenue from 2011-12 to 2015-16 (in Million Dollar)
Exhibit 6.4.5 Year-wise SAS Revenue Growth from 2011-12 to 2015-16 (in %)
Exhibit 64.6 Estimated SAS in Revenue from 2016-17 to 2020-21 (in Million Dollar)
Exhibit 6.4.7 Estimated Year-wise SAS Revenue Growth from 2016-17 to 2020-21 (in %)
Exhibit 6.4.8 SWOT Analysis of SAS
Exhibit 8.2 Porters Five forces
Exhibit 8.3 SWOT Analysis for Global Big Data Industry in Financial Services
Notes
Company Information
LIST OF EXHIBITS
Exhibit 3.2.1 Global Big Data Industry Value Chain
Exhibit 4.1 Forecast of global big data market 2017-21
Exhibit 4.2 Forecast of global big data market in financial services 2017-21
Exhibit 4.3 Percentage share of various geographies in global big data market in financial
Exhibit 4.4 Geography wise growth forecast in global big data market in financial services
Exhibit 4.5 Forecast of Asia Pacific big data market in financial services (Billion Dollar)
Exhibit 4.6 Forecast of North American big data Market in financial services 2017-21(Billion Dollar)
Exhibit 4.7 Forecast of European big data market in financial services 2017-21(Billion Dollar)
Exhibit 4.8 Forecast of LASA big data market in financial services 2017-21 (Billion Dollar)
Exhibit 4.9 Forecast of MENA big data market in financial services 2017-21 (Billion Dollar)
Exhibit 5.1 Growth Drivers and Inhibitors for Global Big Data Market in Financial Services
Exhibit 6.1.1 Company Profile – Teradata
Exhibit 6.1.2 Contact Details – Teradata
Exhibit 6.1.3 Teradata in Big Data Industry Value Chain
Exhibit 6.1.4 Teradata Revenue from 2011-12 to 2015-16 (in Million Dollar)
Exhibit 6.1.5 Year-wise Teradata Revenue Growth from 2011-12 to 2015-16 (in %)
Exhibit 6.1.6 Estimated Teradata in Revenue from 2016-17 to 2020-21 (in Million Dollar)
Exhibit 6.1.7 Estimated Year-wise Teradata Revenue Growth from 2016-17 to 2020-21 (in %)
Exhibit 6.1.8 SWOT Analysis of Teradata
Exhibit 6.2.1 Company Profile – Informatica
Exhibit 6.2.2 Contact Details – Informatica
Exhibit 6.2.3 Informatica in Big Data Industry Value Chain
Exhibit 6.2.4 Informatica Revenue from 2011-12 to 2015-16 (in Million Dollar)
Exhibit 6.2.5 Year-wise Informatica Revenue Growth from 2011-12 to 2015-16 (in %)
Exhibit 6.2.6 Estimated Informatica in Revenue from 2016-17 to 2020-21 (in Million Dollar)
Exhibit 6.2.7 Estimated Year-wise Informatica Revenue Growth from 2016-17 to 2020-21 (in %)
Exhibit 6.2.8 SWOT Analysis of Informatica
Exhibit 6.3.1 Company Profile – Hortonworks
Exhibit 6.3.2 Contact Details – Hortonworks
Exhibit 6.3.3 Hortonworks in Big Data Industry Value Chain
Exhibit 6.3.4 Hortonworks Revenue from 2011-12 to 2015-16 (in Million Dollar)
Exhibit 6.3.5 Year-wise Hortonworks Revenue Growth from 2011-12 to 2015-16 (in %)
Exhibit 6.3.6 Estimated Hortonworks in Revenue from 2016-17 to 2020-21 (in Million Dollar)
Exhibit 6.3.7 Estimated Year-wise Hortonworks Revenue Growth from 2016-17 to 2020-21 (in %)
Exhibit 6.3.8 SWOT Analysis of Hortonworks
Exhibit 6.4.1 Company Profile – SAS
Exhibit 6.4.2 Contact Details – SAS
Exhibit 6.4.3 SAS in Big Data Industry Value Chain
Exhibit 6.4.4 SAS Revenue from 2011-12 to 2015-16 (in Million Dollar)
Exhibit 6.4.5 Year-wise SAS Revenue Growth from 2011-12 to 2015-16 (in %)
Exhibit 64.6 Estimated SAS in Revenue from 2016-17 to 2020-21 (in Million Dollar)
Exhibit 6.4.7 Estimated Year-wise SAS Revenue Growth from 2016-17 to 2020-21 (in %)
Exhibit 6.4.8 SWOT Analysis of SAS
Exhibit 8.2 Porters Five forces
Exhibit 8.3 SWOT Analysis for Global Big Data Industry in Financial Services
