Market Overview:
The global finance data fusion market is expected to grow at a CAGR of 10.8% during the forecast period from 2018 to 2030. The growth in this market can be attributed to the increasing demand for big data and analytics solutions, rising need for fraud prevention and risk management, and growing adoption of cloud-based solutions. The finance data fusion market is segmented on the basis of type into managed services and professional services. The managed services segment is expected to grow at a higher CAGR than the professional services segment during the forecast period from 2018 to 2030. This can be attributed to the growing demand for outsourcing of big data and analytics solutions by enterprises across different industries. On the basis of application, the finance data fusion market is divided into large enterprises and small and medium enterprises (SMEs). The large enterprises segment is expected to hold a larger share in terms of revenue in this market during the forecast period from 2018 to 2030.
Product Definition:
Finance data fusion is the process of combining different financial datasets to create a more comprehensive view of an organization's financial health. This can be used to help make better decisions about where to allocate resources, identify potential areas of risk, and make other strategic decisions. The importance of finance data fusion lies in its ability to provide a more holistic view of an organization's finances that can help inform better decision-making.
Managed Services:
Managed services are the set of practices and technologies used to provide support, maintenance, consulting and other related activities for IT infrastructure. It helps organizations reduce their operational costs by focusing on core competencies. The primary benefit of managed services is that they help companies avoid managing certain tasks which would normally be handled by IT staff; this frees up resources that can be allocated to focus on strategic initiatives such as new product development or mergers & acquisitions.
Professional Services:
Professional services are the set of tools and techniques that help in deriving business insights from data. It helps organizations to increase their operational efficiency, customer satisfaction, and profitability. The major benefit of professional services is that it reduces the time required to derive insights by eliminating redundant steps in analyzing data.
Data Fusion is a process where multiple sources of information are combined using statistical algorithms to produce new information with higher accuracy and reliability than individual inputs.
Application Insights:
The large enterprises segment accounted for the largest revenue share of over 60% in 2017. The segment is further subdivided into medium and large enterprises. Large enterprise includes companies having more than 500 employees. Medium enterprise has fewer than 500 employees and large enterprise is inclusive of both SMEs as well as MNCs. Finance data fusion solutions are gaining traction among medium to small-sized businesses, which lack the resources to handle complex financial applications but need critical information from various sources, such as bank statements, accounts receivable systems etc., at a reasonable cost and time frame feasible for them without depending on third-party providers or internal IT teams with limited resources at their disposal.
Regional Analysis:
North America dominated the market in 2017. The region is expected to continue its dominance over the forecast period as well, owing to factors such as technological advancements and high demand for automation. Moreover, increasing adoption of cloud-based technologies is also likely to drive regional growth.
Asia Pacific is anticipated to be the fastest-growing region during the forecast period due to rising investments by various governments in developing countries such as India and China. These countries are home to a large number of small enterprises that would benefit from advanced finance tools provided by data fusion providers. Furthermore, these economies are also home several large enterprises that require sophisticated financial analysis tools for strategic decision making purposes or compliance with regulatory requirements (for instance: Know Your Customer (KYC) & Anti Money Laundering (AML) norms). Such factors are expected contribute towards regional growth over the next eight years (2030).
Growth Factors:
- Increasing demand for big data and analytics services
- Proliferation of cloud-based solutions and services
- Emergence of new technologies, such as artificial intelligence (AI) and machine learning (ML)
- Growing number of finance data fusion startups
- Rising demand from SMBs
Scope Of The Report
Report Attributes
Report Details
Report Title
Finance Data Fusion Market Research Report
By Type
Managed Services, Professional Services
By Application
Large enterprises, Small and Medium Enterprises (SMEs)
By Companies
Thomson Reuters, AGT International, ESRI, Lexisnexis, Palantir Technologies, Cogint, Invensense, Clarivate Analytics, Merrick & Company, Lexisnexis, Palantir Technologies
Regions Covered
North America, Europe, APAC, Latin America, MEA
Base Year
2021
Historical Year
2019 to 2020 (Data from 2010 can be provided as per availability)
Forecast Year
2030
Number of Pages
230
Number of Tables & Figures
161
Customization Available
Yes, the report can be customized as per your need.
Global Finance Data Fusion Market Report Segments:
The global Finance Data Fusion market is segmented on the basis of:
Types
Managed Services, Professional Services
The product segment provides information about the market share of each product and the respective CAGR during the forecast period. It lays out information about the product pricing parameters, trends, and profits that provides in-depth insights of the market. Furthermore, it discusses latest product developments & innovation in the market.
Applications
Large enterprises, Small and Medium Enterprises (SMEs)
The application segment fragments various applications of the product and provides information on the market share and growth rate of each application segment. It discusses the potential future applications of the products and driving and restraining factors of each application segment.
Some of the companies that are profiled in this report are:
- Thomson Reuters
- AGT International
- ESRI
- Lexisnexis
- Palantir Technologies
- Cogint
- Invensense
- Clarivate Analytics
- Merrick & Company
- Lexisnexis
- Palantir Technologies
Highlights of The Finance Data Fusion Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of market.
- Historical data and forecast.
- Estimations for the forecast period 2030.
- Developments and trends in the market.
- By Type:
- Managed Services
- Professional Services
- By Application:
- Large enterprises
- Small and Medium Enterprises (SMEs)
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Finance Data Fusion Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2030.
Regional Analysis
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Note: A country of choice can be added in the report at no extra cost. If more than one country needs to be added, the research quote will vary accordingly.
The geographical analysis part of the report provides information about the product sales in terms of volume and revenue in regions. It lays out potential opportunities for the new entrants, emerging players, and major players in the region. The regional analysis is done after considering the socio-economic factors and government regulations of the countries in the regions.
How you may use our products:
- Correctly Positioning New Products
- Market Entry Strategies
- Business Expansion Strategies
- Consumer Insights
- Understanding Competition Scenario
- Product & Brand Management
- Channel & Customer Management
- Identifying Appropriate Advertising Appeals
8 Reasons to Buy This Report
- Includes a Chapter on the Impact of COVID-19 Pandemic On the Market
- Report Prepared After Conducting Interviews with Industry Experts & Top Designates of the Companies in the Market
- Implemented Robust Methodology to Prepare the Report
- Includes Graphs, Statistics, Flowcharts, and Infographics to Save Time
- Industry Growth Insights Provides 24/5 Assistance Regarding the Doubts in the Report
- Provides Information About the Top-winning Strategies Implemented by Industry Players.
- In-depth Insights On the Market Drivers, Restraints, Opportunities, and Threats
- Customization of the Report Available
Frequently Asked Questions?
Finance Data Fusion is a process of combining data from different sources to create a more complete picture of financial performance. This can include, but is not limited to, data from accounting systems, investment databases, and market research reports. By understanding how all the pieces of this complex puzzle fit together, financiers can make better decisions that will improve their company's bottom line.
Some of the key players operating in the finance data fusion market are Thomson Reuters, AGT International, ESRI, Lexisnexis, Palantir Technologies, Cogint, Invensense, Clarivate Analytics, Merrick & Company, Lexisnexis, Palantir Technologies.
The finance data fusion market is expected to register a CAGR of 10.8%.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Finance Data Fusion Market Overview
4.1 Introduction
4.1.1 Market Taxonomy
4.1.2 Market Definition
4.1.3 Macro-Economic Factors Impacting the Market Growth
4.2 Finance Data Fusion Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Finance Data Fusion Market - Supply Chain Analysis
4.3.1 List of Key Suppliers
4.3.2 List of Key Distributors
4.3.3 List of Key Consumers
4.4 Key Forces Shaping the Finance Data Fusion Market
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers
4.4.3 Threat of Substitution
4.4.4 Threat of New Entrants
4.4.5 Competitive Rivalry
4.5 Global Finance Data Fusion Market Size & Forecast, 2018-2028
4.5.1 Finance Data Fusion Market Size and Y-o-Y Growth
4.5.2 Finance Data Fusion Market Absolute $ Opportunity
Chapter 5 Global Finance Data Fusion Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Finance Data Fusion Market Size Forecast by Type
5.2.1 Managed Services
5.2.2 Professional Services
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Finance Data Fusion Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Finance Data Fusion Market Size Forecast by Applications
6.2.1 Large enterprises
6.2.2 Small and Medium Enterprises (SMEs)
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Finance Data Fusion Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Finance Data Fusion Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Finance Data Fusion Analysis and Forecast
9.1 Introduction
9.2 North America Finance Data Fusion Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Finance Data Fusion Market Size Forecast by Type
9.6.1 Managed Services
9.6.2 Professional Services
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Finance Data Fusion Market Size Forecast by Applications
9.10.1 Large enterprises
9.10.2 Small and Medium Enterprises (SMEs)
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Finance Data Fusion Analysis and Forecast
10.1 Introduction
10.2 Europe Finance Data Fusion Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Finance Data Fusion Market Size Forecast by Type
10.6.1 Managed Services
10.6.2 Professional Services
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Finance Data Fusion Market Size Forecast by Applications
10.10.1 Large enterprises
10.10.2 Small and Medium Enterprises (SMEs)
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Finance Data Fusion Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Finance Data Fusion Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Finance Data Fusion Market Size Forecast by Type
11.6.1 Managed Services
11.6.2 Professional Services
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Finance Data Fusion Market Size Forecast by Applications
11.10.1 Large enterprises
11.10.2 Small and Medium Enterprises (SMEs)
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Finance Data Fusion Analysis and Forecast
12.1 Introduction
12.2 Latin America Finance Data Fusion Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Finance Data Fusion Market Size Forecast by Type
12.6.1 Managed Services
12.6.2 Professional Services
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Finance Data Fusion Market Size Forecast by Applications
12.10.1 Large enterprises
12.10.2 Small and Medium Enterprises (SMEs)
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Finance Data Fusion Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Finance Data Fusion Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Finance Data Fusion Market Size Forecast by Type
13.6.1 Managed Services
13.6.2 Professional Services
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Finance Data Fusion Market Size Forecast by Applications
13.10.1 Large enterprises
13.10.2 Small and Medium Enterprises (SMEs)
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Finance Data Fusion Market: Competitive Dashboard
14.2 Global Finance Data Fusion Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 Thomson Reuters
14.3.2 AGT International
14.3.3 ESRI
14.3.4 Lexisnexis
14.3.5 Palantir Technologies
14.3.6 Cogint
14.3.7 Invensense
14.3.8 Clarivate Analytics
14.3.9 Merrick & Company
14.3.10 Lexisnexis
14.3.11 Palantir Technologies
