by The global generative AI in banking and finance market size accounted for US$ 712.4 Mn in 2022 and is projected to reach around USD 12,337.87 Mn by 2032, growing at a CAGR of 33% from 2023 to 2032.
Key Takeaways:
- North America captured more than 37% of revenue share in 2022.
- By technology, the natural language processing segment is expected to grow at a significant rate over the forecast period.
- By application, the fraud detection segment is expected to grow at a significant rate over the forecast period.
Report Summary
The global generative AI in banking and finance market report provides a Point-by-Point and In-Depth analysis of global market size, regional and country-level market size, market share, segmentation market growth, competitive landscape, sales analysis, opportunities analysis, strategic market growth analysis, the impact of domestic and global market key players, value chain optimization, trade regulations, recent developments, product launches, area marketplace expanding, and technological innovations.
The study offers a comprehensive analysis on diverse features, including production capacities, demand, product developments, revenue generation, and sales in the generative AI in banking and finance market across the globe.
A comprehensive estimate on the generative AI in banking and finance market has been provided through an optimistic scenario as well as a conservative scenario, taking into account the sales of generative AI in banking and finance during the forecast period. Price point comparison by region with global average price is also considered in the study.
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Generative AI in Banking and Finance Market Report Scope
| Report Coverage | Details |
| Market Size in 2023 | USD 947.49 Million |
| Market Size in 2032 | USD 12,337.87 Million |
| Growth Rate from 2023 to 2032 | CAGR of 33% |
| Largest Market | North America |
| Base Year | 2022 |
| Forecast Period | 2023 to 2032 |
| Segments Covered | By Technology and By Application |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
Key Highlights:
Reports Coverage: It incorporates key market sections, key makers secured, the extent of items offered in the years considered, worldwide containerized generative AI in banking and finance market and study goals. Moreover, it contacts the division study gave in the report based on the sort of item and applications.
Market Outline: This area stresses the key investigations, market development rate, serious scene, market drivers, patterns, and issues notwithstanding the naturally visible pointers.
Market Production by Region: The report conveys information identified with import and fare, income, creation, and key players of every single local market contemplated are canvassed right now.
Market Segments:
Technology:
Based on technology, the market is divided into natural language processing, deep learning, reinforcement learning, generative adversarial networks, computer vision, and predictive analytics. Among these, the natural language processing segment is dominant in the technology segment in generative AI in banking market, with a market share of 36%. Owing to it revolutionizing the banking market by empowering generative AI models to understand and generate human-like language. This cutting-edge technology enables banks and financial institutions to develop sophisticated systems that can automate and enhance various banking processes. NLP-powered chatbots and virtual assistants are transforming customer interactions, providing personalized recommendations, and streamlining transactions. Furthermore, NLP techniques enable banks to analyze customer sentiment in real-time, improving customer support and tailoring services to meet individual needs. The integration of NLP with generative AI models also revolutionizes document analysis and processing, automating tasks such as data extraction, compliance checks, and risk assessments.
Also Read: Industrial Fasteners Market Size To Cross USD 153 Bn By 2032
Generative AI in Banking and Finance Market Players
The report includes the profiles of key generative AI in banking and finance market companies along with their SWOT analysis and market strategies. In addition, the report focuses on leading industry players with information such as company profiles, components and services offered, financial information, key development in past five years.
Major companies operating in this area
- Amazon Web Services Inc.
- Cisco Systems Inc.
- Microsoft Corporation
- SAP SE
- BigML Inc.
- Fair Isaac Corporation
- IBM Corporation
- Google LLC
- Accenture
- Oracle
Market Segmentation
By Technology
- Natural Language Processing
- Deep Learning
- Reinforcement Learning
- Generative Adversarial Networks
- Computer Vision
- Predictive Analytics
By Application
- Fraud Detection
- Customer Service
- Risk Assessment
- Compliance
- Trading and Portfolio Management
Regional Segmentation
- North America (U.S., Canada, Mexico)
- Europe (Germany, France, U.K., Italy, Spain, Rest of Europe)
- Asia-Pacific (China, Japan, India, Southeast Asia and Rest of APAC)
- Latin America (Brazil and Rest of Latin America)
- Middle East and Africa (GCC, North Africa, South Africa, Rest of MEA)
Research Methodology
Secondary Research
It involves company databases such as Hoover’s: This assists us to recognize financial information, the structure of the market participants and industry’s competitive landscape.
The secondary research sources referred in the process are as follows:
- Governmental bodies, and organizations creating economic policies
- National and international social welfare institutions
- Company websites, financial reports and SEC filings, broker and investor reports
- Related patent and regulatory databases
- Statistical databases and market reports
- Corporate Presentations, news, press release, and specification sheet of Manufacturers
Primary Research
Primary research includes face-to-face interviews, online surveys, and telephonic interviews.
- Means of primary research: Email interactions, telephonic discussions and Questionnaire-based research etc.
- In order to validate our research findings and analysis, we conduct primary interviews of key industry participants. Insights from primary respondents help in validating the secondary research findings. It also develops Research Team’s expertise and market understanding.
TABLE OF CONTENT
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology (Premium Insights)
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Generative AI in Banking and Finance Market
5.1. COVID-19 Landscape: Generative AI in Banking and Finance Industry Impact
5.2. COVID 19 – Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Generative AI in Banking and Finance Market, By Technology
8.1. Generative AI in Banking and Finance Market, by Technology, 2023-2032
8.1.1. Natural Language Processing
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Deep Learning
8.1.2.1. Market Revenue and Forecast (2020-2032)
8.1.3. GlucagoReinforcement Learning
8.1.3.1. Market Revenue and Forecast (2020-2032)
8.1.4. Generative Adversarial Networks
8.1.4.1. Market Revenue and Forecast (2020-2032)
8.1.5. Computer Vision
8.1.5.1. Market Revenue and Forecast (2020-2032)
8.1.6. Predictive Analytics
8.1.6.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Generative AI in Banking and Finance Market, By Application
9.1. Generative AI in Banking and Finance Market, by Application, 2023-2032
9.1.1. Fraud Detection
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Customer Service
9.1.2.1. Market Revenue and Forecast (2020-2032)
9.1.3. Risk Assessment
9.1.3.1. Market Revenue and Forecast (2020-2032)
9.1.4. Compliance
9.1.4.1. Market Revenue and Forecast (2020-2032)
9.1.5. Trading and Portfolio Management
9.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Generative AI in Banking and Finance Market, Regional Estimates and Trend Forecast
10.1. North America
10.1.1. Market Revenue and Forecast, by Technology (2020-2032)
10.1.2. Market Revenue and Forecast, by Application (2020-2032)
10.1.3. U.S.
10.1.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.1.3.2. Market Revenue and Forecast, by Application (2020-2032)
10.1.4. Rest of North America
10.1.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.1.4.2. Market Revenue and Forecast, by Application (2020-2032)
10.2. Europe
10.2.1. Market Revenue and Forecast, by Technology (2020-2032)
10.2.2. Market Revenue and Forecast, by Application (2020-2032)
10.2.3. UK
10.2.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.2.3.2. Market Revenue and Forecast, by Application (2020-2032)
10.2.4. Germany
10.2.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.2.4.2. Market Revenue and Forecast, by Application (2020-2032)
10.2.5. France
10.2.5.1. Market Revenue and Forecast, by Technology (2020-2032)
10.2.5.2. Market Revenue and Forecast, by Application (2020-2032)
10.2.6. Rest of Europe
10.2.6.1. Market Revenue and Forecast, by Technology (2020-2032)
10.2.6.2. Market Revenue and Forecast, by Application (2020-2032)
10.3. APAC
10.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.3.2. Market Revenue and Forecast, by Application (2020-2032)
10.3.3. India
10.3.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.3.3.2. Market Revenue and Forecast, by Application (2020-2032)
10.3.4. China
10.3.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.3.4.2. Market Revenue and Forecast, by Application (2020-2032)
10.3.5. Japan
10.3.5.1. Market Revenue and Forecast, by Technology (2020-2032)
10.3.5.2. Market Revenue and Forecast, by Application (2020-2032)
10.3.6. Rest of APAC
10.3.6.1. Market Revenue and Forecast, by Technology (2020-2032)
10.3.6.2. Market Revenue and Forecast, by Application (2020-2032)
10.4. MEA
10.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.4.2. Market Revenue and Forecast, by Application (2020-2032)
10.4.3. GCC
10.4.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.4.3.2. Market Revenue and Forecast, by Application (2020-2032)
10.4.4. North Africa
10.4.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.4.4.2. Market Revenue and Forecast, by Application (2020-2032)
10.4.5. South Africa
10.4.5.1. Market Revenue and Forecast, by Technology (2020-2032)
10.4.5.2. Market Revenue and Forecast, by Application (2020-2032)
10.4.6. Rest of MEA
10.4.6.1. Market Revenue and Forecast, by Technology (2020-2032)
10.4.6.2. Market Revenue and Forecast, by Application (2020-2032)
10.5. Latin America
10.5.1. Market Revenue and Forecast, by Technology (2020-2032)
10.5.2. Market Revenue and Forecast, by Application (2020-2032)
10.5.3. Brazil
10.5.3.1. Market Revenue and Forecast, by Technology (2020-2032)
10.5.3.2. Market Revenue and Forecast, by Application (2020-2032)
10.5.4. Rest of LATAM
10.5.4.1. Market Revenue and Forecast, by Technology (2020-2032)
10.5.4.2. Market Revenue and Forecast, by Application (2020-2032)
Chapter 11. Company Profiles
11.1. Amazon Web Services Inc.
11.1.1. Company Overview
11.1.2. Product Offerings
11.1.3. Financial Performance
11.1.4. Recent Initiatives
11.2. Cisco Systems Inc.
11.2.1. Company Overview
11.2.2. Product Offerings
11.2.3. Financial Performance
11.2.4. Recent Initiatives
11.3. Microsoft Corporation
11.3.1. Company Overview
11.3.2. Product Offerings
11.3.3. Financial Performance
11.3.4. Recent Initiatives
11.4. SAP SE
11.4.1. Company Overview
11.4.2. Product Offerings
11.4.3. Financial Performance
11.4.4. Recent Initiatives
11.5. BigML Inc.
11.5.1. Company Overview
11.5.2. Product Offerings
11.5.3. Financial Performance
11.5.4. Recent Initiatives
11.6. Fair Isaac Corporation
11.6.1. Company Overview
11.6.2. Product Offerings
11.6.3. Financial Performance
11.6.4. Recent Initiatives
11.7. IBM Corporation
11.7.1. Company Overview
11.7.2. Product Offerings
11.7.3. Financial Performance
11.7.4. Recent Initiatives
11.8. Google LLC
11.8.1. Company Overview
11.8.2. Product Offerings
11.8.3. Financial Performance
11.8.4. Recent Initiatives
11.9. Accenture
11.9.1. Company Overview
11.9.2. Product Offerings
11.9.3. Financial Performance
11.9.4. Recent Initiatives
11.10. Oracle
11.10.1. Company Overview
11.10.2. Product Offerings
11.10.3. Financial Performance
11.10.4. Recent Initiatives
Chapter 12. Research Methodology
12.1. Primary Research
12.2. Secondary Research
12.3. Assumptions
Chapter 13. Appendix
13.1. About Us
13.2. Glossary of Terms
Thanks for reading you can also get individual chapter-wise sections or region-wise report versions such as North America, Europe, or the Asia Pacific.
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