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.
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
The study have segmented the market of Global Big Data in the Financial Service market , by Application (Banks, Insurers, Asset Management Firms and Other) and Region with country level break-up.
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