Big Data Analytics in Banking 2018 Global Market Key Players – IBM, Oracle, SAP SE, Microsoft, HP, Amazon AWS, Google – Analysis and Forecast to 2023

WiseGuyRerports.com Presents “Global Big Data Analytics in Banking Market 2018 by Manufacturers, Countries, Type and Application, Forecast to 2023” New Document to its Studies Database

Big data analytics refers to the strategy of analyzing large volumes of data, or big data.

Scope of the Report: 
This report studies the Big Data Analytics in Banking market status and outlook of Global and major regions, from angles of players, countries, product types and end industries; this report analyzes the top players in global market, and splits the Big Data Analytics in Banking market by product type and applications/end industries. 
APAC is expected to have High Adoption Rate Owing to Large Potential. Rapid technological developments in the information technology sector and increasing business operations mark Asia-Pacific (APAC) as the most important market for Big Data in banking during the forecast period. The biggest contributors to this market are China and India that account for most of the revenue in the APAC region. Many organizations in the APAC region are increasingly depending on digital systems to realize their goals. Several vendors, such as SAP and IBM provide wide -range of Big Data analytics services to banks in the region. Some of the core capabilities of these services include real-time monitoring, big cloud services, and other customized dashboards for easier retrieval of data, to ease the workflows. These tools enable organizations for on-the-resource planning and offer modified plans to aid decision-making. 
Customer Analytics is expected to be One of the Prime Software Application. A number of categories, such as defecting customers, loyal customers etc. can be identified through big data analytics and the required reward for each category can be decided. Through such applications, the retention of customers is possible, and the detection of disloyal customers helps the company to reduce the focus on such customers. The buying habits of customers can also be identified, and the sales for each customer can be customized. This customization results in the high response rate for customers and better customer experienced. 
The global Big Data Analytics in Banking market is valued at xx million USD in 2017 and is expected to reach xx million USD by the end of 2023, growing at a CAGR of xx% between 2017 and 2023. 
The Asia-Pacific will occupy for more market share in following years, especially in China, also fast growing India and Southeast Asia regions. 
North America, especially The United States, will still play an important role which cannot be ignored. Any changes from United States might affect the development trend of Big Data Analytics in Banking. 
Europe also play important roles in global market, with market size of xx million USD in 2017 and will be xx million USD in 2023, with a CAGR of xx%.

Market Segment by Companies, this report covers 
IBM 
Oracle 
SAP SE 
Microsoft 
HP 
Amazon AWS 
Google 
Hitachi Data Systems 
Tableau 
New Relic 
Alation 
Teradata 
VMware 
Splice Machine 
Splunk Enterprise 
Alteryx

 

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Market Segment by Regions, regional analysis covers 
North America (United States, Canada and Mexico) 
Europe (Germany, France, UK, Russia and Italy) 
Asia-Pacific (China, Japan, Korea, India and Southeast Asia) 
South America (Brazil, Argentina, Colombia) 
Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Market Segment by Type, covers 
On-Premise 
Cloud

Market Segment by Applications, can be divided into 
Feedback Management 
Customer Analytics 
Social Media Analytics 
Fraud Detection and Management 
Others

 

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Table Of Contents:      

1 Big Data Analytics in Banking Market Overview 
1.1 Product Overview and Scope of Big Data Analytics in Banking 
1.2 Classification of Big Data Analytics in Banking by Types 
1.2.1 Global Big Data Analytics in Banking Revenue Comparison by Types (2017-2023) 
1.2.2 Global Big Data Analytics in Banking Revenue Market Share by Types in 2017 
1.2.3 On-Premise 
1.2.4 Cloud 
1.3 Global Big Data Analytics in Banking Market by Application 
1.3.1 Global Big Data Analytics in Banking Market Size and Market Share Comparison by Applications (2013-2023) 
1.3.2 Feedback Management 
1.3.3 Customer Analytics 
1.3.4 Social Media Analytics 
1.3.5 Fraud Detection and Management 
1.3.6 Others 
1.4 Global Big Data Analytics in Banking Market by Regions 
1.4.1 Global Big Data Analytics in Banking Market Size (Million USD) Comparison by Regions (2013-2023) 
1.4.1 North America (USA, Canada and Mexico) Big Data Analytics in Banking Status and Prospect (2013-2023) 
1.4.2 Europe (Germany, France, UK, Russia and Italy) Big Data Analytics in Banking Status and Prospect (2013-2023) 
1.4.3 Asia-Pacific (China, Japan, Korea, India and Southeast Asia) Big Data Analytics in Banking Status and Prospect (2013-2023) 
1.4.4 South America (Brazil, Argentina, Colombia) Big Data Analytics in Banking Status and Prospect (2013-2023) 
1.4.5 Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa) Big Data Analytics in Banking Status and Prospect (2013-2023) 
1.5 Global Market Size of Big Data Analytics in Banking (2013-2023) 

2 Manufacturers Profiles 
2.1 IBM 
2.1.1 Business Overview 
2.1.2 Big Data Analytics in Banking Type and Applications 
2.1.2.1 Product A 
2.1.2.2 Product B 
2.1.3 IBM Big Data Analytics in Banking Revenue, Gross Margin and Market Share (2016-2017) 
2.2 Oracle 
2.2.1 Business Overview 
2.2.2 Big Data Analytics in Banking Type and Applications 
2.2.2.1 Product A 
2.2.2.2 Product B 
2.2.3 Oracle Big Data Analytics in Banking Revenue, Gross Margin and Market Share (2016-2017) 
2.3 SAP SE 
2.3.1 Business Overview 
2.3.2 Big Data Analytics in Banking Type and Applications 
2.3.2.1 Product A 
2.3.2.2 Product B 
2.3.3 SAP SE Big Data Analytics in Banking Revenue, Gross Margin and Market Share (2016-2017) 
2.4 Microsoft 
2.4.1 Business Overview 
2.4.2 Big Data Analytics in Banking Type and Applications 
2.4.2.1 Product A 
2.4.2.2 Product B 
2.4.3 Microsoft Big Data Analytics in Banking Revenue, Gross Margin and Market Share (2016-2017) 
2.5 HP 
2.5.1 Business Overview 
2.5.2 Big Data Analytics in Banking Type and Applications 
2.5.2.1 Product A 
2.5.2.2 Product B 
2.5.3 HP Big Data Analytics in Banking Revenue, Gross Margin and Market Share (2016-2017) 
2.6 Amazon AWS 
2.6.1 Business Overview 
2.6.2 Big Data Analytics in Banking Type and Applications 
2.6.2.1 Product A 
2.6.2.2 Product B 
2.6.3 Amazon AWS Big Data Analytics in Banking Revenue, Gross Margin and Market Share (2016-2017) 
2.7 Google 
2.7.1 Business Overview 
2.7.2 Big Data Analytics in Banking Type and Applications 
2.7.2.1 Product A 
2.7.2.2 Product B 
2.7.3 Google Big Data Analytics in Banking Revenue, Gross Margin and Market Share (2016-2017) 

 Continued…….                                                      

 

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