Natural Language Processing for Finance - Global Market Share and Ranking, Overall Sales and Demand Forecast 2024-2030

Publication ID:

PB511246858

Publication Date:

November 8, 2024

Pages:

Publisher:

MRRPB5

Countries:

Global [1]

USD 3,950.00

IT Services [2]

Computing & Electronics [3]

Description:

NLP in the banking and finance sector has advanced to a global scale with more and more financial institutions leveraging the benefits of advanced technological innovation. Along with Artificial Intelligence and Machine Learning, NLP application is creating its footprints across operations, risk, sales, R&D, customer support and many other verticals in the financial sector, that鈥檚 in turn leading to greater efficiencies, productivity, cost savings and time and resource management.
The global market for Natural Language Processing for Finance was estimated to be worth US$ million in 2023 and is forecast to a readjusted size of US$ million by 2030 with a CAGR of % during the forecast period 2024-2030.
North American market for Natural Language Processing for Finance was valued at $ million in 2023 and will reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
Asia-Pacific market for Natural Language Processing for Finance was valued at $ million in 2023 and will reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
Europe market for Natural Language Processing for Finance was valued at $ million in 2023 and will reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The global key companies of Natural Language Processing for Finance include Bloomberg, Yahoo, Google Finance, Bank of America, ICBC, JP Morgan and Ant Group, etc. In 2023, the global five largest players hold a share approximately % in terms of revenue.
Report Scope
This report aims to provide a comprehensive presentation of the global market for Natural Language Processing for Finance, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Natural Language Processing for Finance by region & country, by Type, and by Application.
The Natural Language Processing for Finance market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. 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 Natural Language Processing for Finance.
Market Segmentation
By Company
Bloomberg
Yahoo
Google Finance
Bank of America
ICBC
JP Morgan
Ant Group
Segment by Type:
Sentiment Analysis
Name Matching and KYC
Sell-Side Research
Document Management
Risk Monitoring
Credit Scoring
Customer Service
Segment by Application
Commercial Banks
Investment Banks
Asset Management Company
Individual Investors
By Region
North America
U.S.
Canada
Europe
Germany
France
U.K.
Italy
Russia
Asia-Pacific
China
Japan
South Korea
China Taiwan
Southeast Asia
India
Latin America
Mexico
Brazil
Argentina
Middle East & Africa
Turkey
Saudi Arabia
UAE
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Natural Language Processing for Finance manufacturers competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: 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 4: 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 5: Revenue of Natural Language Processing for Finance in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of Natural Language Processing for Finance in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.

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Table Of Contents:

1 Market Overview
1.1 Natural Language Processing for Finance Product Introduction
1.2 Global Natural Language Processing for Finance Market Size Forecast
1.3 Natural Language Processing for Finance Market Trends & Drivers
1.3.1 Natural Language Processing for Finance Industry Trends
1.3.2 Natural Language Processing for Finance Market Drivers & Opportunity
1.3.3 Natural Language Processing for Finance Market Challenges
1.3.4 Natural Language Processing for Finance Market Restraints
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Competitive Analysis by Company
2.1 Global Natural Language Processing for Finance Players Revenue Ranking (2023)
2.2 Global Natural Language Processing for Finance Revenue by Company (2019-2024)
2.3 Key Companies Natural Language Processing for Finance Manufacturing Base Distribution and Headquarters
2.4 Key Companies Natural Language Processing for Finance Product Offered
2.5 Key Companies Time to Begin Mass Production of Natural Language Processing for Finance
2.6 Natural Language Processing for Finance Market Competitive Analysis
2.6.1 Natural Language Processing for Finance Market Concentration Rate (2019-2024)
2.6.2 Global 5 and 10 Largest Companies by Natural Language Processing for Finance Revenue in 2023
2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Natural Language Processing for Finance as of 2023)
2.7 Mergers & Acquisitions, Expansion
3 Segmentation by Type
3.1 Introduction by Type
3.1.1 Sentiment Analysis
3.1.2 Name Matching and KYC
3.1.3 Sell-Side Research
3.1.4 Document Management
3.1.5 Risk Monitoring
3.1.6 Credit Scoring
3.1.7 Customer Service
3.2 Global Natural Language Processing for Finance Sales Value by Type
3.2.1 Global Natural Language Processing for Finance Sales Value by Type (2019 VS 2023 VS 2030)
3.2.2 Global Natural Language Processing for Finance Sales Value, by Type (2019-2030)
3.2.3 Global Natural Language Processing for Finance Sales Value, by Type (%) (2019-2030)
4 Segmentation by Application
4.1 Introduction by Application
4.1.1 Commercial Banks
4.1.2 Investment Banks
4.1.3 Asset Management Company
4.1.4 Individual Investors
4.2 Global Natural Language Processing for Finance Sales Value by Application
4.2.1 Global Natural Language Processing for Finance Sales Value by Application (2019 VS 2023 VS 2030)
4.2.2 Global Natural Language Processing for Finance Sales Value, by Application (2019-2030)
4.2.3 Global Natural Language Processing for Finance Sales Value, by Application (%) (2019-2030)
5 Segmentation by Region
5.1 Global Natural Language Processing for Finance Sales Value by Region
5.1.1 Global Natural Language Processing for Finance Sales Value by Region: 2019 VS 2023 VS 2030
5.1.2 Global Natural Language Processing for Finance Sales Value by Region (2019-2024)
5.1.3 Global Natural Language Processing for Finance Sales Value by Region (2025-2030)
5.1.4 Global Natural Language Processing for Finance Sales Value by Region (%), (2019-2030)
5.2 North America
5.2.1 North America Natural Language Processing for Finance Sales Value, 2019-2030
5.2.2 North America Natural Language Processing for Finance Sales Value by Country (%), 2023 VS 2030
5.3 Europe
5.3.1 Europe Natural Language Processing for Finance Sales Value, 2019-2030
5.3.2 Europe Natural Language Processing for Finance Sales Value by Country (%), 2023 VS 2030
5.4 Asia Pacific
5.4.1 Asia Pacific Natural Language Processing for Finance Sales Value, 2019-2030
5.4.2 Asia Pacific Natural Language Processing for Finance Sales Value by Country (%), 2023 VS 2030
5.5 South America
5.5.1 South America Natural Language Processing for Finance Sales Value, 2019-2030
5.5.2 South America Natural Language Processing for Finance Sales Value by Country (%), 2023 VS 2030
5.6 Middle East & Africa
5.6.1 Middle East & Africa Natural Language Processing for Finance Sales Value, 2019-2030
5.6.2 Middle East & Africa Natural Language Processing for Finance Sales Value by Country (%), 2023 VS 2030
6 Segmentation by Key Countries/Regions
6.1 Key Countries/Regions Natural Language Processing for Finance Sales Value Growth Trends, 2019 VS 2023 VS 2030
6.2 Key Countries/Regions Natural Language Processing for Finance Sales Value
6.3 United States
6.3.1 United States Natural Language Processing for Finance Sales Value, 2019-2030
6.3.2 United States Natural Language Processing for Finance Sales Value by Type (%), 2023 VS 2030
6.3.3 United States Natural Language Processing for Finance Sales Value by Application, 2023 VS 2030
6.4 Europe
6.4.1 Europe Natural Language Processing for Finance Sales Value, 2019-2030
6.4.2 Europe Natural Language Processing for Finance Sales Value by Type (%), 2023 VS 2030
6.4.3 Europe Natural Language Processing for Finance Sales Value by Application, 2023 VS 2030
6.5 China
6.5.1 China Natural Language Processing for Finance Sales Value, 2019-2030
6.5.2 China Natural Language Processing for Finance Sales Value by Type (%), 2023 VS 2030
6.5.3 China Natural Language Processing for Finance Sales Value by Application, 2023 VS 2030
6.6 Japan
6.6.1 Japan Natural Language Processing for Finance Sales Value, 2019-2030
6.6.2 Japan Natural Language Processing for Finance Sales Value by Type (%), 2023 VS 2030
6.6.3 Japan Natural Language Processing for Finance Sales Value by Application, 2023 VS 2030
6.7 South Korea
6.7.1 South Korea Natural Language Processing for Finance Sales Value, 2019-2030
6.7.2 South Korea Natural Language Processing for Finance Sales Value by Type (%), 2023 VS 2030
6.7.3 South Korea Natural Language Processing for Finance Sales Value by Application, 2023 VS 2030
6.8 Southeast Asia
6.8.1 Southeast Asia Natural Language Processing for Finance Sales Value, 2019-2030
6.8.2 Southeast Asia Natural Language Processing for Finance Sales Value by Type (%), 2023 VS 2030
6.8.3 Southeast Asia Natural Language Processing for Finance Sales Value by Application, 2023 VS 2030
6.9 India
6.9.1 India Natural Language Processing for Finance Sales Value, 2019-2030
6.9.2 India Natural Language Processing for Finance Sales Value by Type (%), 2023 VS 2030
6.9.3 India Natural Language Processing for Finance Sales Value by Application, 2023 VS 2030
7 Company Profiles
7.1 Bloomberg
7.1.1 Bloomberg Profile
7.1.2 Bloomberg Main Business
7.1.3 Bloomberg Natural Language Processing for Finance Products, Services and Solutions
7.1.4 Bloomberg Natural Language Processing for Finance Revenue (US$ Million) & (2019-2024)
7.1.5 Bloomberg Recent Developments
7.2 Yahoo
7.2.1 Yahoo Profile
7.2.2 Yahoo Main Business
7.2.3 Yahoo Natural Language Processing for Finance Products, Services and Solutions
7.2.4 Yahoo Natural Language Processing for Finance Revenue (US$ Million) & (2019-2024)
7.2.5 Yahoo Recent Developments
7.3 Google Finance
7.3.1 Google Finance Profile
7.3.2 Google Finance Main Business
7.3.3 Google Finance Natural Language Processing for Finance Products, Services and Solutions
7.3.4 Google Finance Natural Language Processing for Finance Revenue (US$ Million) & (2019-2024)
7.3.5 Bank of America Recent Developments
7.4 Bank of America
7.4.1 Bank of America Profile
7.4.2 Bank of America Main Business
7.4.3 Bank of America Natural Language Processing for Finance Products, Services and Solutions
7.4.4 Bank of America Natural Language Processing for Finance Revenue (US$ Million) & (2019-2024)
7.4.5 Bank of America Recent Developments
7.5 ICBC
7.5.1 ICBC Profile
7.5.2 ICBC Main Business
7.5.3 ICBC Natural Language Processing for Finance Products, Services and Solutions
7.5.4 ICBC Natural Language Processing for Finance Revenue (US$ Million) & (2019-2024)
7.5.5 ICBC Recent Developments
7.6 JP Morgan
7.6.1 JP Morgan Profile
7.6.2 JP Morgan Main Business
7.6.3 JP Morgan Natural Language Processing for Finance Products, Services and Solutions
7.6.4 JP Morgan Natural Language Processing for Finance Revenue (US$ Million) & (2019-2024)
7.6.5 JP Morgan Recent Developments
7.7 Ant Group
7.7.1 Ant Group Profile
7.7.2 Ant Group Main Business
7.7.3 Ant Group Natural Language Processing for Finance Products, Services and Solutions
7.7.4 Ant Group Natural Language Processing for Finance Revenue (US$ Million) & (2019-2024)
7.7.5 Ant Group Recent Developments
8 Industry Chain Analysis
8.1 Natural Language Processing for Finance Industrial Chain
8.2 Natural Language Processing for Finance Upstream Analysis
8.2.1 Key Raw Materials
8.2.2 Raw Materials Key Suppliers
8.2.3 Manufacturing Cost Structure
8.3 Midstream Analysis
8.4 Downstream Analysis (Customers Analysis)
8.5 Sales Model and Sales Channels
8.5.1 Natural Language Processing for Finance Sales Model
8.5.2 Sales Channel
8.5.3 Natural Language Processing for Finance Distributors
9 Research Findings and Conclusion
10 Appendix
10.1 Research Methodology
10.1.1 Methodology/Research Approach
10.1.2 Data Source
10.2 Author Details
10.3 Disclaimer

Companies Mentioned:

Bloomberg
Yahoo
Google Finance
Bank of America
ICBC
JP Morgan
Ant Group

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