Global Big Data Analytics in Banking Market Research Report 2024

Publication ID:

PB503244810

Publication Date:

March 15, 2024

Pages:

Publisher:

MRRPB5

Countries:

Global [1]

USD 2,900.00

IT Services [2]

Computing & Electronics [3]

Description:

Big data analytics refers to the strategy of analyzing large volumes of data, or big data.
The global Big Data Analytics in Banking market was valued at US$ million in 2023 and is anticipated to reach US$ million by 2030, witnessing a CAGR of % during the forecast period 2024-2030.
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.
This report aims to provide a comprehensive presentation of the global market for Big Data Analytics in Banking, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Big Data Analytics in Banking.
Report Scope
The Big Data Analytics in Banking market size, estimations, and forecasts are provided in terms of revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Big Data Analytics in Banking market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Big Data Analytics in Banking companies, new entrants, and industry chain related companies in this market with information on the revenues, sales volume, and average price for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
IBM
Oracle
SAP SE
Microsoft
HP
Amazon AWS
Google
Hitachi Data Systems
Tableau
New Relic
Alation
Teradata
VMware
Splice Machine
Splunk Enterprise
Alteryx
Segment by Type
On-Premise
Cloud
Segment by Application
Feedback Management
Customer Analytics
Social Media Analytics
Fraud Detection and Management
Others
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Big Data Analytics in Banking companies鈥� competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.

Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.

Table Of Contents:

1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Big Data Analytics in Banking Market Size Growth Rate by Type: 2019 VS 2023 VS 2030
1.2.2 On-Premise
1.2.3 Cloud
1.3 Market by Application
1.3.1 Global Big Data Analytics in Banking Market Growth by Application: 2019 VS 2023 VS 2030
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 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Big Data Analytics in Banking Market Perspective (2019-2030)
2.2 Big Data Analytics in Banking Growth Trends by Region
2.2.1 Global Big Data Analytics in Banking Market Size by Region: 2019 VS 2023 VS 2030
2.2.2 Big Data Analytics in Banking Historic Market Size by Region (2019-2024)
2.2.3 Big Data Analytics in Banking Forecasted Market Size by Region (2025-2030)
2.3 Big Data Analytics in Banking Market Dynamics
2.3.1 Big Data Analytics in Banking Industry Trends
2.3.2 Big Data Analytics in Banking Market Drivers
2.3.3 Big Data Analytics in Banking Market Challenges
2.3.4 Big Data Analytics in Banking Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Big Data Analytics in Banking Players by Revenue
3.1.1 Global Top Big Data Analytics in Banking Players by Revenue (2019-2024)
3.1.2 Global Big Data Analytics in Banking Revenue Market Share by Players (2019-2024)
3.2 Global Big Data Analytics in Banking Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Big Data Analytics in Banking Revenue
3.4 Global Big Data Analytics in Banking Market Concentration Ratio
3.4.1 Global Big Data Analytics in Banking Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Big Data Analytics in Banking Revenue in 2023
3.5 Big Data Analytics in Banking Key Players Head office and Area Served
3.6 Key Players Big Data Analytics in Banking Product Solution and Service
3.7 Date of Enter into Big Data Analytics in Banking Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Big Data Analytics in Banking Breakdown Data by Type
4.1 Global Big Data Analytics in Banking Historic Market Size by Type (2019-2024)
4.2 Global Big Data Analytics in Banking Forecasted Market Size by Type (2025-2030)
5 Big Data Analytics in Banking Breakdown Data by Application
5.1 Global Big Data Analytics in Banking Historic Market Size by Application (2019-2024)
5.2 Global Big Data Analytics in Banking Forecasted Market Size by Application (2025-2030)
6 North America
6.1 North America Big Data Analytics in Banking Market Size (2019-2030)
6.2 North America Big Data Analytics in Banking Market Growth Rate by Country: 2019 VS 2023 VS 2030
6.3 North America Big Data Analytics in Banking Market Size by Country (2019-2024)
6.4 North America Big Data Analytics in Banking Market Size by Country (2025-2030)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Big Data Analytics in Banking Market Size (2019-2030)
7.2 Europe Big Data Analytics in Banking Market Growth Rate by Country: 2019 VS 2023 VS 2030
7.3 Europe Big Data Analytics in Banking Market Size by Country (2019-2024)
7.4 Europe Big Data Analytics in Banking Market Size by Country (2025-2030)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Big Data Analytics in Banking Market Size (2019-2030)
8.2 Asia-Pacific Big Data Analytics in Banking Market Growth Rate by Region: 2019 VS 2023 VS 2030
8.3 Asia-Pacific Big Data Analytics in Banking Market Size by Region (2019-2024)
8.4 Asia-Pacific Big Data Analytics in Banking Market Size by Region (2025-2030)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Big Data Analytics in Banking Market Size (2019-2030)
9.2 Latin America Big Data Analytics in Banking Market Growth Rate by Country: 2019 VS 2023 VS 2030
9.3 Latin America Big Data Analytics in Banking Market Size by Country (2019-2024)
9.4 Latin America Big Data Analytics in Banking Market Size by Country (2025-2030)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Big Data Analytics in Banking Market Size (2019-2030)
10.2 Middle East & Africa Big Data Analytics in Banking Market Growth Rate by Country: 2019 VS 2023 VS 2030
10.3 Middle East & Africa Big Data Analytics in Banking Market Size by Country (2019-2024)
10.4 Middle East & Africa Big Data Analytics in Banking Market Size by Country (2025-2030)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 IBM
11.1.1 IBM Company Detail
11.1.2 IBM Business Overview
11.1.3 IBM Big Data Analytics in Banking Introduction
11.1.4 IBM Revenue in Big Data Analytics in Banking Business (2019-2024)
11.1.5 IBM Recent Development
11.2 Oracle
11.2.1 Oracle Company Detail
11.2.2 Oracle Business Overview
11.2.3 Oracle Big Data Analytics in Banking Introduction
11.2.4 Oracle Revenue in Big Data Analytics in Banking Business (2019-2024)
11.2.5 Oracle Recent Development
11.3 SAP SE
11.3.1 SAP SE Company Detail
11.3.2 SAP SE Business Overview
11.3.3 SAP SE Big Data Analytics in Banking Introduction
11.3.4 SAP SE Revenue in Big Data Analytics in Banking Business (2019-2024)
11.3.5 SAP SE Recent Development
11.4 Microsoft
11.4.1 Microsoft Company Detail
11.4.2 Microsoft Business Overview
11.4.3 Microsoft Big Data Analytics in Banking Introduction
11.4.4 Microsoft Revenue in Big Data Analytics in Banking Business (2019-2024)
11.4.5 Microsoft Recent Development
11.5 HP
11.5.1 HP Company Detail
11.5.2 HP Business Overview
11.5.3 HP Big Data Analytics in Banking Introduction
11.5.4 HP Revenue in Big Data Analytics in Banking Business (2019-2024)
11.5.5 HP Recent Development
11.6 Amazon AWS
11.6.1 Amazon AWS Company Detail
11.6.2 Amazon AWS Business Overview
11.6.3 Amazon AWS Big Data Analytics in Banking Introduction
11.6.4 Amazon AWS Revenue in Big Data Analytics in Banking Business (2019-2024)
11.6.5 Amazon AWS Recent Development
11.7 Google
11.7.1 Google Company Detail
11.7.2 Google Business Overview
11.7.3 Google Big Data Analytics in Banking Introduction
11.7.4 Google Revenue in Big Data Analytics in Banking Business (2019-2024)
11.7.5 Google Recent Development
11.8 Hitachi Data Systems
11.8.1 Hitachi Data Systems Company Detail
11.8.2 Hitachi Data Systems Business Overview
11.8.3 Hitachi Data Systems Big Data Analytics in Banking Introduction
11.8.4 Hitachi Data Systems Revenue in Big Data Analytics in Banking Business (2019-2024)
11.8.5 Hitachi Data Systems Recent Development
11.9 Tableau
11.9.1 Tableau Company Detail
11.9.2 Tableau Business Overview
11.9.3 Tableau Big Data Analytics in Banking Introduction
11.9.4 Tableau Revenue in Big Data Analytics in Banking Business (2019-2024)
11.9.5 Tableau Recent Development
11.10 New Relic
11.10.1 New Relic Company Detail
11.10.2 New Relic Business Overview
11.10.3 New Relic Big Data Analytics in Banking Introduction
11.10.4 New Relic Revenue in Big Data Analytics in Banking Business (2019-2024)
11.10.5 New Relic Recent Development
11.11 Alation
11.11.1 Alation Company Detail
11.11.2 Alation Business Overview
11.11.3 Alation Big Data Analytics in Banking Introduction
11.11.4 Alation Revenue in Big Data Analytics in Banking Business (2019-2024)
11.11.5 Alation Recent Development
11.12 Teradata
11.12.1 Teradata Company Detail
11.12.2 Teradata Business Overview
11.12.3 Teradata Big Data Analytics in Banking Introduction
11.12.4 Teradata Revenue in Big Data Analytics in Banking Business (2019-2024)
11.12.5 Teradata Recent Development
11.13 VMware
11.13.1 VMware Company Detail
11.13.2 VMware Business Overview
11.13.3 VMware Big Data Analytics in Banking Introduction
11.13.4 VMware Revenue in Big Data Analytics in Banking Business (2019-2024)
11.13.5 VMware Recent Development
11.14 Splice Machine
11.14.1 Splice Machine Company Detail
11.14.2 Splice Machine Business Overview
11.14.3 Splice Machine Big Data Analytics in Banking Introduction
11.14.4 Splice Machine Revenue in Big Data Analytics in Banking Business (2019-2024)
11.14.5 Splice Machine Recent Development
11.15 Splunk Enterprise
11.15.1 Splunk Enterprise Company Detail
11.15.2 Splunk Enterprise Business Overview
11.15.3 Splunk Enterprise Big Data Analytics in Banking Introduction
11.15.4 Splunk Enterprise Revenue in Big Data Analytics in Banking Business (2019-2024)
11.15.5 Splunk Enterprise Recent Development
11.16 Alteryx
11.16.1 Alteryx Company Detail
11.16.2 Alteryx Business Overview
11.16.3 Alteryx Big Data Analytics in Banking Introduction
11.16.4 Alteryx Revenue in Big Data Analytics in Banking Business (2019-2024)
11.16.5 Alteryx Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details

Companies Mentioned:

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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