NLP in Finance Market by Offering, Technology, End-User

List of Tables

The NLP in Finance Market is projected to reach USD 33.29 billion by 2030 from USD 5.92 billion in 2022, at a CAGR of 24.07% during the forecast period.

Global NLP in Finance Market

KEY MARKET STATISTICS
Base Year Value [2022]	USD 5.92 billion
Estimated Year Value [2023]	USD 7.28 billion
Forecast Year Value [2030]	USD 33.29 billion
CAGR (%)	24.07%

Market Segmentation & Coverage:

This research report analyzes various sub-markets, forecasts revenues, and examines emerging trends in each category to provide a comprehensive outlook on the NLP in Finance Market.

Based on Offering, market is studied across Services and Software. The Software is projected to witness significant market share during forecast period.

Based on Technology, market is studied across Deep Learning, Emotion Detection, Machine Learning, Natural Language Generation, Text Classification, and Topic Modeling. The Emotion Detection is projected to witness significant market share during forecast period.

Based on End-User, market is studied across Banking, Financial Services, and Insurance. The Financial Services is projected to witness significant market share during forecast period.

Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom. The Asia-Pacific is projected to witness significant market share during forecast period.

Market Statistics:

The report provides market sizing and forecasts across 7 major currencies - USD, EUR, JPY, GBP, AUD, CAD, and CHF; multiple currency support helps organization leaders to make well-informed decisions. In this report, 2018 to 2021 are considered as historical years, 2022 is base year, 2023 is estimated year, and years from 2024 to 2030 are considered as forecast period.

FPNV Positioning Matrix:

The FPNV Positioning Matrix is an indispensable tool for assessing the NLP in Finance Market. It comprehensively evaluates vendors, analyzing key metrics related to Business Strategy and Product Satisfaction. This enables users to make informed decisions tailored to their specific needs. Through advanced analysis, vendors are categorized into four distinct quadrants, each representing a different level of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V). Be assured that this insightful framework empowers decision-makers to navigate the market with confidence.

Market Share Analysis:

The Market Share Analysis offers invaluable insights into the vendor landscape NLP in Finance Market. By evaluating their impact on overall revenue, customer base, and other key metrics, we provide companies with a comprehensive understanding of their performance and the competitive environment they confront. This analysis also uncovers the level of competition in terms of market share acquisition, fragmentation, dominance, and industry consolidation during the study period.

Key Company Profiles:

The report delves into recent significant developments in the NLP in Finance Market, highlighting leading vendors and their innovative profiles. These include Aalpha Information Systems India Pvt. Ltd., ABBYY Development Inc., Accern Corporation, Amazon Web Services, Inc., Attivio, Inc., Avaamo, Conversica, Inc., Flatworld Solutions Pvt. Ltd., Google LLC by Alphabet Inc., GupShup, Inbenta Holdings Inc., InData Labs Group Limited, Inexture solutions LLP, International Business Machines Corporation, Jio Haptik Technologies Limited, Kasisto, Inc., Matellio Inc., Microsoft Corporation, Mindtitan OU, Netguru S.A., Oracle Corporation, ProminentPixel, Qualtrics LLC, Quy Technology Pvt. Ltd., SAS Institute Inc., Senseforth Inc., Unicsoft LP, Veritone, Inc., and Yellow.ai.

The report offers valuable insights on the following aspects:

1. Market Penetration: It provides comprehensive information about key players' market dynamics and offerings.

2. Market Development: In-depth analysis of emerging markets and penetration across mature market segments, highlighting lucrative opportunities.

3. Market Diversification: Detailed information about new product launches, untapped geographies, recent developments, and investments.

4. Competitive Assessment & Intelligence: Exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of leading players.

5. Product Development & Innovation: Intelligent insights on future technologies, R&D activities, and breakthrough product developments.

The report addresses key questions such as:

1. What is the market size and forecast for the NLP in Finance Market?

2. Which products, segments, applications, and areas hold the highest investment potential in the NLP in Finance Market?

3. What is the competitive strategic window for identifying opportunities in the NLP in Finance Market?

4. What are the latest technology trends and regulatory frameworks in the NLP in Finance Market?

5. What is the market share of the leading vendors in the NLP in Finance Market?

6. Which modes and strategic moves are suitable for entering the NLP in Finance Market?

Product Code: MRR-961BA04A2E7D

1. Preface

1.1. Objectives of the Study
1.2. Market Segmentation & Coverage
1.3. Years Considered for the Study
1.4. Currency & Pricing
1.5. Language
1.6. Limitations
1.7. Assumptions
1.8. Stakeholders

2. Research Methodology

2.1. Define: Research Objective
2.2. Determine: Research Design
2.3. Prepare: Research Instrument
2.4. Collect: Data Source
2.5. Analyze: Data Interpretation
2.6. Formulate: Data Verification
2.7. Publish: Research Report
2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

4.1. Introduction
4.2. NLP in Finance Market, by Region

5. Market Insights

5.1. Market Dynamics
- 5.1.1. Drivers
  - 5.1.1.1. Increasing adoption of automated customer service machines in banks and financial institutions
  - 5.1.1.2. Higher need of NLP to to combat fraud and streamline the financial services
  - 5.1.1.3. Growing adoption of NLP platforms in stock trading activities
- 5.1.2. Restraints
  - 5.1.2.1. Issues associated with limited training data for NLP
- 5.1.3. Opportunities
  - 5.1.3.1. Increasing investment to digitized the banking services
  - 5.1.3.2. Ongoing product development to increase the efficiency
- 5.1.4. Challenges
  - 5.1.4.1. Uncertainty challenges and innate bias related to NLP platforms
5.2. Market Segmentation Analysis
5.3. Market Trend Analysis
5.4. Cumulative Impact of High Inflation
5.5. Porter's Five Forces Analysis
- 5.5.1. Threat of New Entrants
- 5.5.2. Threat of Substitutes
- 5.5.3. Bargaining Power of Customers
- 5.5.4. Bargaining Power of Suppliers
- 5.5.5. Industry Rivalry
5.6. Value Chain & Critical Path Analysis
5.7. Regulatory Framework

6. NLP in Finance Market, by Offering

6.1. Introduction
6.2. Services
6.3. Software

7. NLP in Finance Market, by Technology

7.1. Introduction
7.2. Deep Learning
7.3. Emotion Detection
7.4. Machine Learning
7.5. Natural Language Generation
7.6. Text Classification
7.7. Topic Modeling

8. NLP in Finance Market, by End-User

8.1. Introduction
8.2. Banking
8.3. Financial Services
8.4. Insurance

9. Americas NLP in Finance Market

9.1. Introduction
9.2. Argentina
9.3. Brazil
9.4. Canada
9.5. Mexico
9.6. United States

10. Asia-Pacific NLP in Finance Market

10.1. Introduction
10.2. Australia
10.3. China
10.4. India
10.5. Indonesia
10.6. Japan
10.7. Malaysia
10.8. Philippines
10.9. Singapore
10.10. South Korea
10.11. Taiwan
10.12. Thailand
10.13. Vietnam

11. Europe, Middle East & Africa NLP in Finance Market

11.1. Introduction
11.2. Denmark
11.3. Egypt
11.4. Finland
11.5. France
11.6. Germany
11.7. Israel
11.8. Italy
11.9. Netherlands
11.10. Nigeria
11.11. Norway
11.12. Poland
11.13. Qatar
11.14. Russia
11.15. Saudi Arabia
11.16. South Africa
11.17. Spain
11.18. Sweden
11.19. Switzerland
11.20. Turkey
11.21. United Arab Emirates
11.22. United Kingdom

12. Competitive Landscape

12.1. FPNV Positioning Matrix
12.2. Market Share Analysis, By Key Player
12.3. Competitive Scenario Analysis, By Key Player

13. Competitive Portfolio

13.1. Key Company Profiles
- 13.1.1. Aalpha Information Systems India Pvt. Ltd.
- 13.1.2. ABBYY Development Inc.
- 13.1.3. Accern Corporation
- 13.1.4. Amazon Web Services, Inc.
- 13.1.5. Attivio, Inc.
- 13.1.6. Avaamo
- 13.1.7. Conversica, Inc.
- 13.1.8. Flatworld Solutions Pvt. Ltd.
- 13.1.9. Google LLC by Alphabet Inc.
- 13.1.10. GupShup
- 13.1.11. Inbenta Holdings Inc.
- 13.1.12. InData Labs Group Limited
- 13.1.13. Inexture solutions LLP
- 13.1.14. International Business Machines Corporation
- 13.1.15. Jio Haptik Technologies Limited
- 13.1.16. Kasisto, Inc.
- 13.1.17. Matellio Inc.
- 13.1.18. Microsoft Corporation
- 13.1.19. Mindtitan OU
- 13.1.20. Netguru S.A.
- 13.1.21. Oracle Corporation
- 13.1.22. ProminentPixel
- 13.1.23. Qualtrics LLC
- 13.1.24. Quy Technology Pvt. Ltd.
- 13.1.25. SAS Institute Inc.
- 13.1.26. Senseforth Inc.
- 13.1.27. Unicsoft LP
- 13.1.28. Veritone, Inc.
- 13.1.29. Yellow.ai
13.2. Key Product Portfolio

14. Appendix

14.1. Discussion Guide
14.2. License & Pricing