by The generative AI in banking and finance market size is poised to grow by USD 12,337.87 million by 2032 from USD 712.4 million in 2022, exhibiting a CAGR of 33% during the forecast period 2023-2032.
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.
Precedence Research has conducted a comprehensive market study that provides valuable insights into the performance of the market during the forecast period. The study identifies significant trends that are shaping the growth of the Generative AI in banking and finance market. In this recently published report, essential dynamics such as drivers, restraints, and opportunities are highlighted for both established market players and emerging participants involved in production and supply.
To begin with, the Generative AI in banking and finance Market report features an executive summary that offers a concise overview of the marketplace. It outlines the key players and industry categories expected to have an impact on the market in the coming years. The executive summary provides an unbiased summary of the market.
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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 |
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The empirical study on the global Generative AI in banking and finance market primarily focuses on the drivers in subsequent sections. It demonstrates how changing demographics are projected to influence the supply and demand dynamics in the Generative AI in banking and finance Market. Our market report for the Generative AI in banking and finance market also delves into the significant rules and regulations that are likely to impact the future growth of this sector. Moreover, in order to comprehend the underlying demand factors, industry experts have provided insights into its fundamental origins.
Regional Snapshot:
Over the forecast period, North America is poised to maintain its market dominance, owing to its reputation for technological advancements and innovation in artificial intelligence. The region boasts prominent financial hubs, such as New York and San Francisco, fostering a thriving fintech ecosystem where both startups and established companies actively pioneer generative AI solutions for the banking and finance sector. A crucial factor contributing to this momentum is the well-established regulatory framework for banking and finance, which necessitates robust risk assessment and fraud detection systems. Generative AI emerges as a pivotal solution, as it enables the generation of synthetic data and simulation of diverse scenarios, facilitating compliance with stringent regulations like anti-money laundering (AML) and fraud prevention guidelines. The region’s remarkable inclination towards embracing advanced and automated solutions further drives the expansion of the market in North America.
Top Key Players:
- Amazon Web Services Inc.
- Cisco Systems Inc.
- Microsoft Corporation
- SAP SE
- BigML Inc.
- Fair Isaac Corporation
- IBM Corporation
- Google LLC
- Accenture
- Oracle
Data Sources and Methodology
To gather comprehensive insights on the Global Generative AI in banking and finance Market, we relied on a range of data sources and followed a well-defined methodology. Our approach involved interactions with industry experts and key stakeholders across the market’s value chain, including management organizations, processing organizations, and analytics service providers.
We followed a rigorous data analysis process to ensure the quality and credibility of our research. The gathered information was carefully evaluated, and relevant quantitative data was subjected to statistical analysis. By employing robust analytical techniques, we were able to derive meaningful insights and present a comprehensive overview of the Global Generative AI in banking and finance Market.
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- The research report has been meticulously crafted to provide comprehensive knowledge on essential marketing strategies and a holistic understanding of crucial marketing plans spanning the forecasted period from 2023 to 2032.
Key Features of the Report:
- Comprehensive Coverage: The report extensively encompasses a detailed explanation of highly effective analytical marketing methods applicable to companies across all industry sectors.
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- Articulated R&D Approach: The report presents a well-defined approach to conducting research and development (R&D) activities, enabling accurate data acquisition on current and future marketing conditions.
Generative AI in Banking and Finance 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
By Geography
- North America
- Europe
- Asia-Pacific
- Latin America
- Middle East and Africa
Reasons to Consider Purchasing the Report:
- Enhance your market research capabilities by accessing this comprehensive and precise report on the global Generative AI in banking and finance market.
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- Receive valuable recommendations and guidance for both new entrants and established players seeking further market expansion.
- Discover not only the cutting-edge technological advancements in the global Generative AI in banking and finance market but also the strategic plans of industry leaders.
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
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