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NLP in Finance Market By Offering (Software, Services), By Application, Technology, By End User - Global Industry Outlook, Key Companies (Google IBM, AWS, and others), Trends and Forecast 2023-2032

Published on : November-2023  Report Code : RC-562  Pages Count : 258  Report Format : PDF
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Market Overview

The Global NLP in Finance Market is expected to reach a value of USD 5.7 billion in 2023, and it is further anticipated to reach a market value of USD 57.5 billion by 2032 at a CAGR of 29.2%. The market has seen significant growth over the past few years and is predicted to grow significantly during the forecasted period as well.

NLP in Finance Market Growth Analysis

In the financial sector, Natural Language Processing (NLP) refers to the application of computational linguistics & artificial intelligence methods to analyze & interpret human language data, which includes examining text data from different sources like social media posts, news articles, financial records, & customer interactions to extract valuable insights. 

NLP is an important tool that enables financial organizations & professionals to automate & enhance multiple processes, including risk assessment, sentiment analysis, customer service, fraud detection, & making informed investment decisions, thereby improving their overall efficiency and decision-making capabilities.

Natural Language Processing (NLP) is revolutionizing the finance sector by automating data analysis, enhancing risk management, and improving customer service. Recent trends highlight its use in sentiment analysis for market predictions and regulatory compliance. 

Key events like the NLP Summit bring industry leaders together to discuss advances such as emotion detection and deep learning in finance. Companies like HSBC are leveraging NLP for real-time market insights, boosting investment strategies. As demand grows, the Asia-Pacific region is poised to lead in adoption, while North America remains a dominant player.

Key Takeaways

  • The NLP in Finance Market is projected to grow from USD 5.7 billion in 2023 to USD 57.5 billion by 2032, at a CAGR of 29.2%.
  • By Offering: Services dominate the Offering segment with a 60% market share in 2023.
  • By Application: Fraud Detection & Prevention leads the Application segment, holding a 45% market share in 2023.
  • By Technology: Machine Learning drives the Technology segment with a commanding 55% share in 2023.
  • By End User: Banking dominates the End User segment, contributing to 50% of the market in 2023.
  • Regional Dominance: North America holds the largest share, accounting for 45.6% of the global market in 2023.

Market Dynamic

In the financial sector, an abundance of unstructured data is generated daily from different sources, like social media, news articles, and customer interactions. NLP technology is used to process & analyze this data, leading to valuable insights and a growing demand for NLP solutions within financial organizations.

Recognizing the significance of tapping into textual data, these institutions benefit from NLP, improving risk assessment, decision-making, & market analysis, while also helping in regulatory compliance through automated reporting & issue identification. The fast advancements in AI & machine learning have expanded NLP's capabilities, allowing more accurate entity recognition, sentiment analysis, & information extraction.

However, concerns about data security and compliance hinder NLP implementation in the banking industry. The complexity & context-specific nature of financial language pose challenges for NLP models, making accurate comprehension & analysis a continuing difficulty. 

Yet, NLP enhances the financial industry's abilities in risk assessment & fraud detection by interpreting unstructured data to identify trends & anomalies related to fraudulent activities, facilitating rapid detection & prevention. In addition, NLP empowers chatbots & virtual assistants to deliver customized experiences, thereby contributing to the sector's efficiency and security.

Research Scope and Analysis

By Offering

Within the NLP in finance market segmentation, the service category takes the lead with the most substantial market share in 2023, which is primarily attributed to the growing need for a range of services, including implementation support, professional services, & system integration. To utilize the full potential of NLP technology effectively, financial institutions depend on professional guidance & services like training & consultation. 

Expert advice is essential when integrating NLP into their operations to ensure that the technology is being used efficiently & effectively. These factors are fueling the increase in demand within this category as financial organizations seek to optimize their use of NLP technology.

By Application

In the NLP in finance market, the category of fraud detection & prevention takes the lead in the market share in 2023, in terms of application, mainly driven by the growing need among financial institutions to identify & prevent fraudulent activities. Fraud poses a large challenge for financial organizations, resulting in significant financial losses running into billions of dollars annually. 

To combat this, NLP technology plays an important role, as it analyzes large volumes of data from different sources, including transaction records, emails, social media content, chat logs, & other textual data, to look into patterns & anomalies that may show potential fraudulent behavior, which plays a critical role of NLP technology highlighting its prominence in the finance sector.

By Technology

The NLP in Finance Market, the market is categorized based on technological types, including Machine Learning, Rule-Based, and Hybrid, among which, the Machine Learning segment emerges as the dominant force, commanding the highest market share in 2023. Machine learning has significantly propelled NLP advancements in the financial sector. 

Its key advantage lies in its ability to learn from vast & complex datasets, which proves critical in the banking industry due to the sheer volume of data involved. Further, NLP models have become more sophisticated & precise, notably outperforming traditional machine learning algorithms in tasks such as sentiment analysis, resulting in more accurate predictions of market trends & behaviors.

NLP in Finance Market Technology Analysis

By End User

In the global NLP in the Finance market, the banking sector drives the growth of the overall market and is anticipated to do the same throughout the forecasted period, NPL plays a major role in the banking sector, transforming the way financial institutions operate. NLP technology allows banks to analyze & extract valuable insights from large volumes of textual data, including financial news, customer inquiries, & social media interactions. 

It improves customer service by automating responses to queries, providing instant support, & improving chatbots' efficiency. NLP is also instrumental in risk management, as it detects potential fraud by scrutinizing transaction data and identifying anomalies in real time. In addition, NLP assists banks in sentiment analysis, helping banks gauge market trends & customer opinions for more informed investment decisions.

The NLP in Finance Market Report is segmented on the basis of the following

By Offering

  • Software
  • Services

By Application

  • Fraud Detection & Prevention
  • Sentiment Analysis
  • Risk Management
  • Sentiment Analysis
  • Others

By Technology

  • Machine Learning
  • Rule Based
  • Hybrid

By End User

  • Banking
  • Insurance
  • Investment & Wealth Management
  • Others

Regional Analysis

In 2023, North America emerges as the leading region in the NLP Finance Market, having a substantial market share of 45.6%, which can be attributed to the region's rich ecosystem of technical research facilities, a skilled workforce, & advanced infrastructure. Further, the market's growth is driven by the region's advanced R&D sector & growing technical support. 

In this region, NLP technology finds large applications in the financial sector, serving many purposes like sentiment analysis, risk management, fraud detection, & customer service. Its effectiveness in analyzing vast volumes of unstructured data from sources like news articles, social media content, & consumer feedback plays an important role in its growing adoption & success.

NLP in Finance Market Regional Analysis

By Region

North America
  • The U.S.
  • Canada
Europe
  • Germany
  • The U.K.
  • France
  • Italy
  • Russia
  • Spain
  • Benelux
  • Nordic
  • Rest of Europe
Asia-Pacific
  • China
  • Japan
  • South Korea
  • India
  • ANZ
  • ASEAN
  • Rest of Asia-Pacific
Latin America
  • Brazil
  • Mexico
  • Argentina
  • Colombia
  • Rest of Latin America
Middle East & Africa
  • Saudi Arabia
  • UAE
  • South Africa
  • Israel
  • Egypt
  • Rest of MEA

Competitive Landscape

The competitive landscape of the Global NLP in the Finance market is characterized by a diverse mix of established technology companies, startups, & specialized NLP solution providers, as key players like IBM, Google, & Microsoft provide comprehensive NLP platforms with a range of financial applications, while smaller firms like Lexalytics & Ayasdi aiming at niche solutions. 

In addition, emerging startups are introducing innovative, specialized NLP tools, intensifying competition. With the growing demand for NLP in finance for tasks like risk assessment, sentiment analysis, & customer service, the market is dynamic & evolving, providing several options for financial institutions & businesses.

For instance, in February 2022, Google Cloud, KeyBank, & Deloitte announced an extended, multi-year strategic alliance, to expedite KeyBank's shift towards a cloud-centric approach to banking, which highlights KeyBank's dedication to prioritizing cloud technology in its financial services, & with the integrated expertise of Google Cloud & Deloitte, they intend to enhance and modernize their banking operations, providing more efficient & innovative services to their customers in the fast-evolving financial sector.

Some of the prominent players in the global NLP in Finance Market are
  • Google
  • IBM
  • AWS
  • Oracle
  • SAS
  • Nuance Communications
  • Microsoft Corp
  • Baidu
  • Inbenta
  • Expert.ai
  • Other Key Players

COVID-19 Pandemic & Recession: Impact on the Global NLP in Finance Market

The COVID-19 pandemic and the following economic recession had a significant impact on the Global Natural Language Processing (NLP) in Finance market. As in the pandemic, the financial industry experienced an increase in volatility & uncertainty, making NLP technology critical for analyzing large textual data to understand market sentiment & make informed decisions. 

However, economic challenges caused budget constraints & lower adoption in some areas of finance. As the global economy recovers, the NLP market is anticipated to regain momentum, driven by the need for efficient risk assessment, compliance monitoring, & customer service in financial institutions looking to navigate the post-pandemic landscape & foster trust & stability in the financial sector.

Report Details

Report Characteristics
Market Size (2023) USD 5.7 Bn
Forecast Value (2032) USD 57.5 Bn
CAGR (2023-2032) 29.2%
Historical Data 2017 - 2022
Forecast Data 2023 - 2032
Base Year 2022
Estimate Year 2023
Report Coverage Market Revenue Estimation, Market Dynamics, Competitive Landscape, Growth Factors and etc.
Segments Covered By Offering (Software and Services), By Application (Fraud Detection & Prevention, Sentiment Analysis, Risk Management, Sentiment Analysis, and Others), By Technology (Machine Learning, Rule Based, and Hybrid), By End User (Banking, Insurance, Investment & Wealth Management, and Others)
Regional Coverage North America – The US and Canada; Europe – Germany, The UK, France, Russia, Spain, Italy, Benelux, Nordic, & Rest of Europe; Asia- Pacific– China, Japan, South Korea, India, ANZ, ASEAN, Rest of APAC; Latin America – Brazil, Mexico, Argentina, Colombia, Rest of Latin America; Middle East & Africa – Saudi Arabia, UAE, South Africa, Turkey, Egypt, Israel, & Rest of MEA
Prominent Players Google, IBM, AWS, Oracle, SAS, Nuance Communications, Microsoft Corp, Baidu, Inbenta, Expert.ai, and Other Key Players
Purchase Options We have three licenses to opt for: Single User License (Limited to 1 user), Multi-User License (Up to 5 Users), and Corporate Use License (Unlimited User) along with free report customization equivalent to 0 analyst working days, 3 analysts working days and 5 analysts working days respectively.

 

Frequently Asked Questions

  • How big is the Global NLP in Finance Market?

    The Global NLP in Finance Market size is estimated to have a value of USD 5.7 billion in 2023 and is expected to reach USD 57.5 billion by the end of 2032.

  • Which region accounted for the largest Global NLP in Finance Market?

    North America has the largest market share for the Global NLP in Finance Market with a share of about 45.6% in 2023.

  • Who are the key players in the Global NLP in Finance Market?

    Some of the major key players in the Global NLP in Finance Market are Google IBM, AWS, and many others.

  • What is the growth rate in the Global NLP in Finance Market?

    The market is growing at a CAGR of 29.2 % over the forecasted period.

  • Contents

      1.Introduction
        1.1.Objectives of the Study
        1.2.Market Scope
        1.3.Market Definition and Scope
      2.NLP in Finance Market Market Overview
        2.1.Global NLP in Finance Market Market Overview by Type
        2.2.Global NLP in Finance Market Market Overview by Application
      3.NLP in Finance Market Market Dynamics, Opportunity, Regulations, and Trends Analysis
        3.1.Market Dynamics
          3.1.1.NLP in Finance Market Market Drivers
          3.1.2.NLP in Finance Market Market Opportunities
          3.1.3.NLP in Finance Market Market Restraints
          3.1.4.NLP in Finance Market Market Challenges
        3.2.Emerging Trend/Technology
        3.3.PESTLE Analysis
        3.4.PORTER'S Five Forces Analysis
        3.5.Technology Roadmap
        3.6.Opportunity Map Analysis
        3.7.Case Studies
        3.8.Opportunity Orbits
        3.9.Pricing Analysis
        3.10.Ecosystem Analysis
        3.11.Supply/Value Chain Analysis
        3.12.Covid-19 & Recession Impact Analysis
        3.13.Product/Brand Comparison
      4.Global NLP in Finance Market Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By Offering, 2017-2032
        4.1.Global NLP in Finance Market Market Analysis by By Offering: Introduction
        4.2.Market Size and Forecast by Region
        4.3.Software
        4.4.Services
      5.Global NLP in Finance Market Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By Application, 2017-2032
        5.1.Global NLP in Finance Market Market Analysis by By Application: Introduction
        5.2.Market Size and Forecast by Region
        5.3.Fraud Detection & Prevention
        5.4.Sentiment Analysis
        5.5.Risk Management
        5.6.Sentiment Analysis
        5.7.Others
      6.Global NLP in Finance Market Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By Technology, 2017-2032
        6.1.Global NLP in Finance Market Market Analysis by By Technology: Introduction
        6.2.Market Size and Forecast by Region
        6.3.Machine Learning
        6.4.Rule Based
        6.5.Hybrid
      7.Global NLP in Finance Market Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by By End User, 2017-2032
        7.1.Global NLP in Finance Market Market Analysis by By End User: Introduction
        7.2.Market Size and Forecast by Region
        7.3.Banking
        7.4.Insurance
        7.5.Investment & Wealth Management
        7.6.Others
      10.Global NLP in Finance Market Market Value ((US$ Mn)), Share (%), and Growth Rate (%) Comparison by Region, 2017-2032
        10.1.North America
          10.1.1.North America NLP in Finance Market Market: Regional Analysis, 2017-2032
            10.1.1.1.The US
            10.1.1.2.Canada
        10.2.1.Europe
          10.2.1.Europe NLP in Finance Market Market: Regional Trend Analysis
            10.2.1.1.Germany
            10.2.1.2.France
            10.2.1.3.UK
            10.2.1.4.Russia
            10.2.1.5.Italy
            10.2.1.6.Spain
            10.2.1.7.Nordic
            10.2.1.8.Benelux
            10.2.1.9.Rest of Europe
        10.3.Asia-Pacific
          10.3.1.Asia-Pacific NLP in Finance Market Market: Regional Analysis, 2017-2032
            10.3.1.1.China
            10.3.1.2.Japan
            10.3.1.3.South Korea
            10.3.1.4.India
            10.3.1.5.ANZ
            10.3.1.6.ASEAN
            10.3.1.7.Rest of Asia-Pacifc
        10.4.Latin America
          10.4.1.Latin America NLP in Finance Market Market: Regional Analysis, 2017-2032
            10.4.1.1.Brazil
            10.4.1.2.Mexico
            10.4.1.3.Argentina
            10.4.1.4.Colombia
            10.4.1.5.Rest of Latin America
        10.5.Middle East and Africa
          10.5.1.Middle East and Africa NLP in Finance Market Market: Regional Analysis, 2017-2032
            10.5.1.1.Saudi Arabia
            10.5.1.2.UAE
            10.5.1.3.South Africa
            10.5.1.4.Israel
            10.5.1.5.Egypt
            10.5.1.6.Turkey
            10.5.1.7.Rest of MEA
      11.Global NLP in Finance Market Market Company Evaluation Matrix, Competitive Landscape, Market Share Analysis, and Company Profiles
        11.1.Market Share Analysis
        11.2.Company Profiles
        11.3.Google
          11.3.1.Company Overview
          11.3.2.Financial Highlights
          11.3.3.Product Portfolio
          11.3.4.SWOT Analysis
          11.3.5.Key Strategies and Developments
        11.4.IBM
          11.4.1.Company Overview
          11.4.2.Financial Highlights
          11.4.3.Product Portfolio
          11.4.4.SWOT Analysis
          11.4.5.Key Strategies and Developments
        11.5.AWS
          11.5.1.Company Overview
          11.5.2.Financial Highlights
          11.5.3.Product Portfolio
          11.5.4.SWOT Analysis
          11.5.5.Key Strategies and Developments
        11.6.Oracle
          11.6.1.Company Overview
          11.6.2.Financial Highlights
          11.6.3.Product Portfolio
          11.6.4.SWOT Analysis
          11.6.5.Key Strategies and Developments
        11.7.SAS
          11.7.1.Company Overview
          11.7.2.Financial Highlights
          11.7.3.Product Portfolio
          11.7.4.SWOT Analysis
          11.7.5.Key Strategies and Developments
        11.8.Nuance Communications
          11.8.1.Company Overview
          11.8.2.Financial Highlights
          11.8.3.Product Portfolio
          11.8.4.SWOT Analysis
          11.8.5.Key Strategies and Developments
        11.9.Microsoft Corp
          11.9.1.Company Overview
          11.9.2.Financial Highlights
          11.9.3.Product Portfolio
          11.9.4.SWOT Analysis
          11.9.5.Key Strategies and Developments
        11.10.Baidu
          11.10.1.Company Overview
          11.10.2.Financial Highlights
          11.10.3.Product Portfolio
          11.10.4.SWOT Analysis
          11.10.5.Key Strategies and Developments
        11.11.Inbenta
          11.11.1.Company Overview
          11.11.2.Financial Highlights
          11.11.3.Product Portfolio
          11.11.4.SWOT Analysis
          11.11.5.Key Strategies and Developments
        11.12.Expert.ai
          11.12.1.Company Overview
          11.12.2.Financial Highlights
          11.12.3.Product Portfolio
          11.12.4.SWOT Analysis
          11.12.5.Key Strategies and Developments
        11.13.Other Key Players
          11.13.1.Company Overview
          11.13.2.Financial Highlights
          11.13.3.Product Portfolio
          11.13.4.SWOT Analysis
          11.13.5.Key Strategies and Developments
      12.Assumptions and Acronyms
      13.Research Methodology
      14.Contact
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