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Synopsis
AI in Banking refers to a trend and practice of applying artificial intelligence technology in the banking industry. Banking AI can cover all aspects of banking operations to increase efficiency, improve customer service, manage risk, and innovate products and services.
The global AI in Banking market was valued at US$ 7354 million in 2023 and is anticipated to reach US$ 28330 million by 2030, witnessing a CAGR of 23.8% during the forecast period 2024-2030.
China and the United States are two leaders in AI industry. On the AI 100 list (2022) released by CB Insights, the number of companies in the United States ranks first, with more than 70 companies, followed by the United Kingdom, with 8 companies on the list. China and Canada both holds 5 companies on the list. According to data from the China Academy of Information and Communications Technology, the scale of China's core artificial intelligence industry reached ¥508 billion in 2022, a year-on-year increase of 18%. From 2013 to November 2022, the cumulative number of patent applications for artificial intelligence inventions in the world reached 729,000, and the cumulative number of applications in China reached 389,000, accounting for 53.4%.
However, the Global Artificial Intelligence Innovation Index Report 2021 released by the China Institute of Scientific and Technological Information shows that the overall strength of the United States is still far ahead. The number of artificial intelligence companies in the United States is about 4,670, while China has only 880. China's data center is less than 1/42 of that of the United States.
This report aims to provide a comprehensive presentation of the global market for AI 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 AI in Banking.
Report Scope
The AI 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 AI 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 AI 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
- Blue Frog Robotics
- Bsh Hausgeräte
- Fanuc
- AWS
- SAP
- IBM
- Intel
- Cisco Systems
- NVIDIA
- Hewlett Packard Enterprise
- JD
- Baidu
- Alibaba
- Huawei
- ByteDance
- Yusys Technologies
Segment by Type
- Hardware
- Software
- Services
Segment by Application
- Analytics
- Chatbots
- Robotic process automation (RPA)
By Region
- North America (United States, Canada)
- Europe (Germany, France, U.K., Italy, Netherlands)
- Asia-Pacific (China, Japan, South Korea, China Taiwan, Southeast Asia, India)
- Latin America, Middle East & Africa (Latin America, Mexico, Brazil, Turkey)
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 AI in Banking companies’ 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.
Index
1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global AI in Banking Market Size Growth Rate by Type: 2019 VS 2023 VS 2030
1.2.2 Hardware
1.2.3 Software
1.2.4 Services
1.3 Market by Application
1.3.1 Global AI in Banking Market Growth by Application: 2019 VS 2023 VS 2030
1.3.2 Analytics
1.3.3 Chatbots
1.3.4 Robotic process automation (RPA)
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global AI in Banking Market Perspective (2019-2030)
2.2 AI in Banking Growth Trends by Region
2.2.1 Global AI in Banking Market Size by Region: 2019 VS 2023 VS 2030
2.2.2 AI in Banking Historic Market Size by Region (2019-2024)
2.2.3 AI in Banking Forecasted Market Size by Region (2025-2030)
2.3 AI in Banking Market Dynamics
2.3.1 AI in Banking Industry Trends
2.3.2 AI in Banking Market Drivers
2.3.3 AI in Banking Market Challenges
2.3.4 AI in Banking Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top AI in Banking Players by Revenue
3.1.1 Global Top AI in Banking Players by Revenue (2019-2024)
3.1.2 Global AI in Banking Revenue Market Share by Players (2019-2024)
3.2 Global AI in Banking Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by AI in Banking Revenue
3.4 Global AI in Banking Market Concentration Ratio
3.4.1 Global AI in Banking Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by AI in Banking Revenue in 2023
3.5 AI in Banking Key Players Head office and Area Served
3.6 Key Players AI in Banking Product Solution and Service
3.7 Date of Enter into AI in Banking Market
3.8 Mergers & Acquisitions, Expansion Plans
4 AI in Banking Breakdown Data by Type
4.1 Global AI in Banking Historic Market Size by Type (2019-2024)
4.2 Global AI in Banking Forecasted Market Size by Type (2025-2030)
5 AI in Banking Breakdown Data by Application
5.1 Global AI in Banking Historic Market Size by Application (2019-2024)
5.2 Global AI in Banking Forecasted Market Size by Application (2025-2030)
6 North America
6.1 North America AI in Banking Market Size (2019-2030)
6.2 North America AI in Banking Market Growth Rate by Country: 2019 VS 2023 VS 2030
6.3 North America AI in Banking Market Size by Country (2019-2024)
6.4 North America AI in Banking Market Size by Country (2025-2030)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe AI in Banking Market Size (2019-2030)
7.2 Europe AI in Banking Market Growth Rate by Country: 2019 VS 2023 VS 2030
7.3 Europe AI in Banking Market Size by Country (2019-2024)
7.4 Europe AI 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 AI in Banking Market Size (2019-2030)
8.2 Asia-Pacific AI in Banking Market Growth Rate by Region: 2019 VS 2023 VS 2030
8.3 Asia-Pacific AI in Banking Market Size by Region (2019-2024)
8.4 Asia-Pacific AI 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 AI in Banking Market Size (2019-2030)
9.2 Latin America AI in Banking Market Growth Rate by Country: 2019 VS 2023 VS 2030
9.3 Latin America AI in Banking Market Size by Country (2019-2024)
9.4 Latin America AI in Banking Market Size by Country (2025-2030)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa AI in Banking Market Size (2019-2030)
10.2 Middle East & Africa AI in Banking Market Growth Rate by Country: 2019 VS 2023 VS 2030
10.3 Middle East & Africa AI in Banking Market Size by Country (2019-2024)
10.4 Middle East & Africa AI in Banking Market Size by Country (2025-2030)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Blue Frog Robotics
11.1.1 Blue Frog Robotics Company Detail
11.1.2 Blue Frog Robotics Business Overview
11.1.3 Blue Frog Robotics AI in Banking Introduction
11.1.4 Blue Frog Robotics Revenue in AI in Banking Business (2019-2024)
11.1.5 Blue Frog Robotics Recent Development
11.2 Bsh Hausgeräte
11.2.1 Bsh Hausgeräte Company Detail
11.2.2 Bsh Hausgeräte Business Overview
11.2.3 Bsh Hausgeräte AI in Banking Introduction
11.2.4 Bsh Hausgeräte Revenue in AI in Banking Business (2019-2024)
11.2.5 Bsh Hausgeräte Recent Development
11.3 Fanuc
11.3.1 Fanuc Company Detail
11.3.2 Fanuc Business Overview
11.3.3 Fanuc AI in Banking Introduction
11.3.4 Fanuc Revenue in AI in Banking Business (2019-2024)
11.3.5 Fanuc Recent Development
11.4 AWS
11.4.1 AWS Company Detail
11.4.2 AWS Business Overview
11.4.3 AWS AI in Banking Introduction
11.4.4 AWS Revenue in AI in Banking Business (2019-2024)
11.4.5 AWS Recent Development
11.5 SAP
11.5.1 SAP Company Detail
11.5.2 SAP Business Overview
11.5.3 SAP AI in Banking Introduction
11.5.4 SAP Revenue in AI in Banking Business (2019-2024)
11.5.5 SAP Recent Development
11.6 IBM
11.6.1 IBM Company Detail
11.6.2 IBM Business Overview
11.6.3 IBM AI in Banking Introduction
11.6.4 IBM Revenue in AI in Banking Business (2019-2024)
11.6.5 IBM Recent Development
11.7 Intel
11.7.1 Intel Company Detail
11.7.2 Intel Business Overview
11.7.3 Intel AI in Banking Introduction
11.7.4 Intel Revenue in AI in Banking Business (2019-2024)
11.7.5 Intel Recent Development
11.8 Cisco Systems
11.8.1 Cisco Systems Company Detail
11.8.2 Cisco Systems Business Overview
11.8.3 Cisco Systems AI in Banking Introduction
11.8.4 Cisco Systems Revenue in AI in Banking Business (2019-2024)
11.8.5 Cisco Systems Recent Development
11.9 NVIDIA
11.9.1 NVIDIA Company Detail
11.9.2 NVIDIA Business Overview
11.9.3 NVIDIA AI in Banking Introduction
11.9.4 NVIDIA Revenue in AI in Banking Business (2019-2024)
11.9.5 NVIDIA Recent Development
11.10 Hewlett Packard Enterprise
11.10.1 Hewlett Packard Enterprise Company Detail
11.10.2 Hewlett Packard Enterprise Business Overview
11.10.3 Hewlett Packard Enterprise AI in Banking Introduction
11.10.4 Hewlett Packard Enterprise Revenue in AI in Banking Business (2019-2024)
11.10.5 Hewlett Packard Enterprise Recent Development
11.11 JD
11.11.1 JD Company Detail
11.11.2 JD Business Overview
11.11.3 JD AI in Banking Introduction
11.11.4 JD Revenue in AI in Banking Business (2019-2024)
11.11.5 JD Recent Development
11.12 Baidu
11.12.1 Baidu Company Detail
11.12.2 Baidu Business Overview
11.12.3 Baidu AI in Banking Introduction
11.12.4 Baidu Revenue in AI in Banking Business (2019-2024)
11.12.5 Baidu Recent Development
11.13 Alibaba
11.13.1 Alibaba Company Detail
11.13.2 Alibaba Business Overview
11.13.3 Alibaba AI in Banking Introduction
11.13.4 Alibaba Revenue in AI in Banking Business (2019-2024)
11.13.5 Alibaba Recent Development
11.14 Huawei
11.14.1 Huawei Company Detail
11.14.2 Huawei Business Overview
11.14.3 Huawei AI in Banking Introduction
11.14.4 Huawei Revenue in AI in Banking Business (2019-2024)
11.14.5 Huawei Recent Development
11.15 ByteDance
11.15.1 ByteDance Company Detail
11.15.2 ByteDance Business Overview
11.15.3 ByteDance AI in Banking Introduction
11.15.4 ByteDance Revenue in AI in Banking Business (2019-2024)
11.15.5 ByteDance Recent Development
11.16 Yusys Technologies
11.16.1 Yusys Technologies Company Detail
11.16.2 Yusys Technologies Business Overview
11.16.3 Yusys Technologies AI in Banking Introduction
11.16.4 Yusys Technologies Revenue in AI in Banking Business (2019-2024)
11.16.5 Yusys Technologies Recent Development
11.17 Yusys Technologies
11.17.1 Yusys Technologies Company Detail
11.17.2 Yusys Technologies Business Overview
11.17.3 Yusys Technologies AI in Banking Introduction
11.17.4 Yusys Technologies Revenue in AI in Banking Business (2019-2024)
11.17.5 Yusys Technologies 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
Published By : QY Research
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