市場調査レポート
商品コード
1272858

金融向けNLPの世界市場:提供別(ソフトウェア、サービス)、アプリケーション別(カスタマーサービス・サポート、リスク管理・不正検出、センチメント分析)、技術別(機械学習、深層学習)、業種別、地域別 - 2028年までの予測

NLP in Finance Market by Offering (Software, Services), Application (Customer Service and Support, Risk Management and Fraud Detection, Sentiment Analysis), Technology (Machine Learning, Deep Learning), Vertical and Region - Global Forecast to 2028

出版日: | 発行: MarketsandMarkets | ページ情報: 英文 364 Pages | 納期: 即納可能 即納可能とは

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価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=151.55円
金融向けNLPの世界市場:提供別(ソフトウェア、サービス)、アプリケーション別(カスタマーサービス・サポート、リスク管理・不正検出、センチメント分析)、技術別(機械学習、深層学習)、業種別、地域別 - 2028年までの予測
出版日: 2023年04月25日
発行: MarketsandMarkets
ページ情報: 英文 364 Pages
納期: 即納可能 即納可能とは
  • 全表示
  • 概要
  • 目次
概要

世界の金融向けNLPの市場規模は、2023年の55億米ドルから、2028年までに188億米ドルまで拡大し、CAGRで27.6%の成長が予測されています。

自動化された効率的な金融サービスへの需要の高まりと、複雑な金融データの正確かつリアルタイム分析に対するニーズの高まりにより、市場の成長が予想されています。

提供別では、サービスセグメントのマネージドサービスが予測期間中に最も高い市場成長率を記録する

金融業界におけるNLP機能に対する需要の高まりにより、金融向けNLPのマネージドサービス市場は今後数年間で大きく成長すると予想されます。市場は競争が激しく、複数の既存プレーヤーがあらゆる規模の金融機関に幅広いNLPサービスを提供しています。この市場の主要プレーヤーには、IBM、Amazon Web Services、Google、Microsoft、SASが含まれます。これらのサービスにより、金融機関はコアビジネスに集中できる一方、正確で効率的なNLPソリューションを提供するために必要なインフラ、技術、専門知識を備えた専門家にNLPタスクをアウトソーシングすることができます。

業種別では、保険セグメントが予測期間中に最も速いCAGRを記録する

保険は、不測の事態や損失から身を守るための金融商品です。保険業界では、引受業務、請求処理、カスタマーサービス、不正検出など、さまざまなプロセスを改善するためにNLPの活用が進んでいます。保険でNLPが活用されている重要な分野の1つが、引受業務です。保険会社は、ソーシャルメディア、クレジットスコア、医療記録など、さまざまなソースからの大量のデータをNLPで分析し、リスクの評価や保険料の決定を行っています。

北米が、予測期間中に最大の市場規模を占める

技術に精通した人口の増加、インターネットの普及率の高さ、AIの進歩により、金融分野で使用されるNLPソリューションが増加しています。北米の顧客の多くは、NLPを活用して効率性の向上、コスト削減、顧客体験の向上を図り、最終的にビジネス成果の向上に繋げています。NLPの人気の高まりと普及率の高さは、この地域の中小企業や新興企業が、ビジネスの構築と促進、消費者層の拡大、より多くの人々へのアプローチに、費用対効果が高く技術的に高度なツールとして、NLP技術を活用することをさらに後押しします。

目次

第1章 イントロダクション

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 重要考察

第5章 市場概要と業界動向

  • イントロダクション
  • 市場力学
    • 促進要因
    • 抑制要因
    • 機会
    • 課題
  • 金融向けNLPの倫理と意味
  • 金融向けNLPの簡単な歴史
  • エコシステム分析
  • 財務ツールとフレームワークにおけるNLP
  • ケーススタディ分析
  • サプライチェーン分析
  • 規制状況
  • 特許分析
  • 主要な会議とイベント(2023年~2024年)
  • 価格分析
  • ポーターのファイブフォース分析
  • 主要な利害関係者と購入基準
  • 金融向けNLP市場の購入者/顧客に影響を与える動向/混乱
  • 金融向けNLP市場のベストプラクティス
  • 金融向けNLPの技術ロードマップ
  • 現在・新興のビジネスモデル
  • 隣接するニッチ技術に対する金融向けNLPの影響

第6章 金融向けNLP市場:提供別

  • イントロダクション
  • ソフトウェア
  • サービス
    • プロフェッショナルサービス
    • マネージドサービス

第7章 金融向けNLP市場:アプリケーション別

  • イントロダクション
  • センチメント分析
  • リスク管理・不正検出
  • コンプライアンス監視
  • 投資分析
  • 金融ニュース・市場分析
  • カスタマーサービス・サポート
  • ドキュメント・契約分析
  • 音声認識・音声表記
  • 言語翻訳
  • その他

第8章 金融向けNLP市場:技術別

  • イントロダクション
  • 機械学習
  • 深層学習
  • 自然言語生成
  • テキスト分類
  • トピックモデル
  • センチメント検出
  • その他

第9章 金融向けNLP市場:業種別

  • イントロダクション
  • バンキング
  • 保険
  • 金融サービス
  • その他

第10章 金融向けNLP市場:地域別

  • イントロダクション
  • 北米
    • 米国
    • カナダ
  • 欧州
    • 英国
    • ドイツ
    • フランス
    • イタリア
    • スペイン
    • スイス
    • その他の欧州
  • アジア太平洋地域
    • 中国
    • インド
    • 日本
    • 韓国
    • シンガポール
    • ニュージーランド
    • その他のアジア太平洋地域
  • 中東・アフリカ
    • サウジアラビア
    • アラブ首長国連邦
    • 南アフリカ
    • イスラエル
    • その他の中東・アフリカ
  • ラテンアメリカ

第11章 競合情勢

  • 概要
  • 大手企業が採用した主な戦略
  • 収益分析
  • 市場シェア分析
  • 企業の評価象限
  • 競合ベンチマーキング
  • スタートアップ/中小企業の評価象限
  • スタートアップ/中小企業の競合ベンチマーキング
  • 金融向けNLP製品の情勢
  • 金融向けNLP主要ベンダーの評価と財務指標
  • 競合シナリオと動向

第12章 企業プロファイル

  • 主要企業
    • MICROSOFT
    • IBM
    • GOOGLE
    • AWS
    • ORACLE
    • SAS INSTITUTE
    • QUALTRICS
    • BAIDU
    • INBENTA
    • BASIS TECHNOLOGY
    • NUANCE COMMUNICATIONS
    • EXPERT.AI
    • LIVEPERSON
    • VERITONE
    • AUTOMATED INSIGHTS
    • BITEXT
    • CONVERSICA
    • ACCERN
    • KASISTO
    • KENSHO
    • ABBYY
    • MOSAIC
    • UNIPHORE
  • スタートアップ/中小企業プロファイル
    • OBSERVE.AI
    • LILT
    • COGNIGY
    • ADDEPTO
    • SKIT.AI
    • MINDTITAN
    • SUPERTEXT.AI
    • NARRATIVA
    • CRESTA

第13章 隣接市場・関連市場

  • 医療・ライフサイエンス向けNLP
  • 音声アナリティクス市場

第14章 付録

目次
Product Code: TC 8620

The NLP in finance market is projected to grow from USD 5.5 billion in 2023 to USD 18.8 billion by 2028 at a compound annual growth rate (CAGR) of 27.6%. The market is anticipated to grow due to the increasing demand for automated and efficient financial services and rising need for accurate and real-time analysis of complex financial data.

By offering, managed services under services segment to register for fastest growing market rate during forecast period

The market for managed services in NLP in finance is expected to grow significantly in the coming years due to the increasing demand for NLP capabilities in the finance industry. The market is highly competitive, with several established players offering a wide range of NLP services to financial institutions of all sizes. Some of the key players in this market include IBM, Amazon Web Services, Google, Microsoft, and SAS. These services allow financial institutions to focus on their core business while outsourcing NLP tasks to experts who have the necessary infrastructure, technology, and expertise to provide accurate and efficient NLP solutions.

By vertical, insurance segment to register fastest growing CAGR during forecast period

Insurance is a financial product that protects against unforeseen events or losses. NLP is increasingly used in the insurance industry to improve various processes, including underwriting, claims processing, customer service, and fraud detection. One of the key areas where NLP is used in insurance is underwriting. Insurance companies use NLP to analyze large amounts of data from various sources, such as social media, credit scores, and medical records, to assess risk and determine premiums.

North America to account for the largest market size during the forecast period

The presence of a growing tech-savvy population, high internet penetration, and advances in AI has resulted in the growth of NLP solutions used in the finance sector. Most of the customers in North America have been leveraging NLP to improve their efficiency, reduce costs, and enhance the customer experience, ultimately leading to better business outcomes. The rising popularity and higher reach of NLP further empower SMEs and startups in the region to harness NLP technology as a cost-effective and technologically advanced tool for building and promoting business, growing consumer base, and reaching out to a wider audience.

Breakdown of primaries

In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the NLP in finance market.

  • By Company: Tier I: 38%, Tier II: 50%, and Tier III: 12%
  • By Designation: C-Level Executives: 35%, D-Level Executives: 40%, and Managers: 25%
  • By Region: Asia Pacific: 20%, Europe: 26%, North America: 42%, and the Rest of the World: 12%

The report includes the study of key players offering NLP in finance solutions. It profiles major vendors in the NLP in finance market. The major players in the NLP in finance market include Microsoft (US), IBM (US), Google (US), AWS (US), Oracle (US), SAS Institute (US), Qualtrics (US), Baidu (China), Inbenta (US), Basis Technology (US), Nuance Communications (US), Expert.ai (Italy), LivePerson (US), Veritone (US), Automated Insights (US), Bitext (US), Conversica (US), Accern (US), Kasisto (US), Kensho (US), ABBYY (US), Mosaic (US), Uniphore (US), Observe.AI (US), Lilt (US), Cognigy (Germany), Addepto (Poland), Skit.ai (US), MindTitan (Estonia), Supertext.ai (India), Narrativa (US), and Cresta (US).

Research coverage

The research study for the NLP in finance market involved extensive secondary sources, directories, journals, and paid databases. Primary sources were mainly industry experts from the core and related industries, preferred NLP in finance providers, third-party service providers, consulting service providers, end-users, and other commercial enterprises. In-depth interviews were conducted with primary respondents, including key industry participants and subject matter experts, to obtain and verify critical qualitative and quantitative information and assess the market's prospects.

Key Benefits of Buying the Report

The report would provide the market leaders/new entrants with information on the closest approximations of the revenue numbers for the overall NLP in Finance market and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights better to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the pulse of the market and provide them with information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:

  • Analysis of key drivers (Increasing demand for automated and efficient financial services across the globe, rising need for accurate and real-time analysis of complex financial data, and the emergence of AI and ML models enabling enhanced NLP capabilities in finance), restraints (The lack of standardization in NLP-based financial applications and services, difficulty in managing large volumes of unstructured data, and complexity in developing and training sophisticated NLP models), opportunities (The development of customized NLP solutions for specific financial services and use cases, integration of NLP with blockchain and big data to enhance the accuracy and efficiency of financial operations, and growing adoption of NLP-powered chatbots and virtual assistants), and challenges (The high implementation costs associated with NLP, limited availability of skilled professionals and data privacy concerns associated with the use of NLP in finance).
  • Product Development/Innovation: Detailed insights on upcoming technologies, R&D activities, and product & service launches in the NLP in finance market
  • Market Development: Comprehensive information about lucrative markets - the report analyses the NLP in finance market across regions
  • Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the NLP in finance market
  • Competitive Assessment: In-depth assessment of market shares, growth strategies, and service offerings of leading players include Microsoft (US), IBM (US), Google (US), AWS (US), Oracle (US), SAS Institute (US), Qualtrics (US), Baidu (China), Inbenta (US), Basis Technology (US), Nuance Communications (US), Expert.ai (Italy), among others in the NLP in finance market strategies. The report also helps stakeholders understand the pulse of the NLP in finance market and provides them with information on key market drivers, restraints, challenges, and opportunities.

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 STUDY OBJECTIVES
  • 1.2 MARKET DEFINITION
    • 1.2.1 INCLUSIONS AND EXCLUSIONS
  • 1.3 MARKET SCOPE
    • 1.3.1 MARKET SEGMENTATION
    • 1.3.2 REGIONS COVERED
    • 1.3.3 YEARS CONSIDERED
  • 1.4 CURRENCY CONSIDERED
    • TABLE 1 US DOLLAR EXCHANGE RATE, 2019-2022
  • 1.5 STAKEHOLDERS

2 RESEARCH METHODOLOGY

  • 2.1 RESEARCH DATA
    • FIGURE 1 NLP IN FINANCE MARKET: RESEARCH DESIGN
    • 2.1.1 SECONDARY DATA
    • 2.1.2 PRIMARY DATA
      • 2.1.2.1 Primary interviews
      • 2.1.2.2 Breakup of primary profiles
      • 2.1.2.3 Key industry insights
  • 2.2 DATA TRIANGULATION
    • FIGURE 2 DATA TRIANGULATION
  • 2.3 MARKET SIZE ESTIMATION
    • FIGURE 3 NLP IN FINANCE MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES
    • 2.3.1 TOP-DOWN APPROACH
    • 2.3.2 BOTTOM-UP APPROACH
    • FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 1 (SUPPLY-SIDE): REVENUE FROM SOLUTIONS/SERVICES OF NLP IN FINANCE MARKET
    • FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 2, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL SOLUTIONS/SERVICES OF NLP IN FINANCE MARKET
    • FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 3, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL SOLUTIONS/SERVICES OF NLP IN FINANCE MARKET
    • FIGURE 7 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 4, BOTTOM-UP (DEMAND-SIDE): SHARE OF NLP IN FINANCE THROUGH OVERALL SPENDING
  • 2.4 MARKET FORECAST
    • TABLE 2 FACTOR ANALYSIS
  • 2.5 RESEARCH ASSUMPTIONS
  • 2.6 STUDY LIMITATIONS
  • 2.7 IMPLICATIONS OF RECESSION IMPACT ON NLP IN FINANCE

3 EXECUTIVE SUMMARY

    • TABLE 3 NLP IN FINANCE MARKET SIZE AND GROWTH RATE, 2019-2022 (USD MILLION, Y-O-Y %)
    • TABLE 4 GLOBAL NLP IN FINANCE MARKET SIZE AND GROWTH RATE, 2023-2028 (USD MILLION, Y-O-Y %)
    • FIGURE 8 SOFTWARE SEGMENT TO HOLD LARGEST MARKET SIZE IN 2023
    • FIGURE 9 STATISTICAL NLP SOFTWARE TO ACCOUNT FOR MAJOR MARKET SHARE IN 2023
    • FIGURE 10 PROFESSIONAL SERVICES TO DOMINATE MARKET IN 2023
    • FIGURE 11 SYSTEM INTEGRATION AND IMPLEMENTATION SERVICES TO DOMINATE MARKET IN 2023
    • FIGURE 12 RISK MANAGEMENT AND FRAUD DETECTION TO BE LEADING APPLICATION IN 2023
    • FIGURE 13 MACHINE LEARNING TO BE MOST DEPLOYED TECHNOLOGY IN 2023
    • FIGURE 14 INSURANCE VERTICAL SET TO WITNESS FASTEST GROWTH RATE
    • FIGURE 15 NORTH AMERICA TO HOLD LARGEST MARKET SHARE

4 PREMIUM INSIGHTS

  • 4.1 ATTRACTIVE OPPORTUNITIES IN NLP IN FINANCE MARKET
    • FIGURE 16 INCREASING POPULARITY OF CHATBOTS ACROSS FINANCE AND IMPROVING PERFORMANCE OF NLP MODELS TO DRIVE MARKET GROWTH
  • 4.2 NLP IN FINANCE MARKET: TOP THREE APPLICATIONS
    • FIGURE 17 CUSTOMER SERVICE AND SUPPORT APPLICATION SEGMENT TO ACCOUNT FOR HIGHEST GROWTH RATE
  • 4.3 NORTH AMERICA: NLP IN FINANCE MARKET, BY OFFERING AND VERTICAL
    • FIGURE 18 SOFTWARE AND BANKING TO BE LARGEST SHAREHOLDERS IN NORTH AMERICA IN 2023
  • 4.4 NLP IN FINANCE MARKET, BY REGION
    • FIGURE 19 NORTH AMERICA TO HOLD LARGEST MARKET SHARE IN 2023

5 MARKET OVERVIEW AND INDUSTRY TRENDS

  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
    • FIGURE 20 NLP IN FINANCE MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
    • 5.2.1 DRIVERS
      • 5.2.1.1 Increasing demand for automated and efficient financial services worldwide
      • 5.2.1.2 Rising need for accurate and real-time analysis of complex financial data
      • 5.2.1.3 Emergence of AI and ML models
    • 5.2.2 RESTRAINTS
      • 5.2.2.1 Lack of standardization in NLP-based financial applications and services
      • 5.2.2.2 Difficulty in managing large volumes of unstructured data
      • 5.2.2.3 Complexity in developing and training sophisticated NLP models
    • 5.2.3 OPPORTUNITIES
      • 5.2.3.1 Development of customized NLP solutions for specific financial services and use cases
      • 5.2.3.2 Integration of NLP with blockchain and big data to enhance accuracy and efficiency of financial operations
      • 5.2.3.3 Growing adoption of NLP-powered chatbots and virtual assistants
    • 5.2.4 CHALLENGES
      • 5.2.4.1 High implementation costs associated with NLP
      • 5.2.4.2 Limited availability of skilled professionals
      • 5.2.4.3 Data privacy concerns associated with use of NLP
  • 5.3 ETHICS AND IMPLICATIONS OF NLP IN FINANCE
    • 5.3.1 BIAS AND FAIRNESS
    • 5.3.2 PRIVACY AND SECURITY
    • 5.3.3 INTELLECTUAL PROPERTY
    • 5.3.4 ACCOUNTABILITY AND RESPONSIBILITY
    • 5.3.5 SOCIETAL AND ECONOMIC IMPACT
  • 5.4 BRIEF HISTORY OF NLP IN FINANCE
    • FIGURE 21 BRIEF HISTORY OF NLP IN FINANCE
  • 5.5 ECOSYSTEM ANALYSIS
    • FIGURE 22 KEY PLAYERS IN NLP IN FINANCE MARKET ECOSYSTEM
    • 5.5.1 NLP IN FINANCE TECHNOLOGY PROVIDERS
    • 5.5.2 NLP IN FINANCE CLOUD PLATFORM PROVIDERS
    • 5.5.3 NLP IN FINANCE API AND AS-A-SERVICE PROVIDERS
    • 5.5.4 NLP IN FINANCE HARDWARE PROVIDERS
    • 5.5.5 NLP IN FINANCE END USERS
    • 5.5.6 NLP IN FINANCE REGULATORS
  • 5.6 NLP IN FINANCE TOOLS AND FRAMEWORK
    • 5.6.1 TENSORFLOW
    • 5.6.2 PYTORCH
    • 5.6.3 KERAS
    • 5.6.4 NLTK
    • 5.6.5 APACHE OPENNLP
    • 5.6.6 SPACY
    • 5.6.7 GENSIM
    • 5.6.8 ALLENNLP
    • 5.6.9 FLAIR
    • 5.6.10 STANFORD CORENLP
  • 5.7 CASE STUDY ANALYSIS
    • 5.7.1 CASE STUDY 1: NATWEST IMPROVED SPEED AND ACCURACY OF COMPLAINT-HANDLING PROCESS THROUGH IBM
    • 5.7.2 CASE STUDY 2: AYASDI'S NLP PLATFORM HELPED J.P. MORGAN CHASE RAMP UP RISK ASSESSMENT TECHNIQUES
    • 5.7.3 CASE STUDY 3: CAPITAL ONE ELIMINATED INEFFICIENCIES IN CUSTOMER QUERY RESOLUTION THROUGH NLP
    • 5.7.4 CASE STUDY 4: BLACKROCK IDENTIFIED NEW INVESTMENT AVENUES BY ANALYZING LARGE VOLUMES OF UNSTRUCTURED DATA
    • 5.7.5 CASE STUDY 5: YSEOP ASSISTED TD AMERITRADE IN DISCOVERING NEW CUSTOMER INSIGHTS
    • 5.7.6 CASE STUDY 6: ALLIANZ WITNESSED SUBSTANTIAL IMPROVEMENT IN INSURANCE CLAIMS PROCESSING THROUGH NLP
    • 5.7.7 CASE STUDY 7: UBS TRAINED DATASETS THROUGH NLP TO AUGMENT RISK MANAGEMENT PROCESSES
    • 5.7.8 CASE STUDY 8: CITI ADDED PERSONALIZED TOUCH TO CUSTOMER RECOMMENDATIONS VIA NLP-BASED QUERY ANALYSIS
    • 5.7.9 CASE STUDY 9: BARCLAYS SCALED ITS TRADING AND INVESTMENT ANALYSIS PROCESSES VIA AYASDI'S NLP TOOL
    • 5.7.10 CASE STUDY 10: GOLDMAN SACHS AUGMENTED ITS FINANCIAL R&D PROWESS
    • 5.7.11 CASE STUDY 11: NLP EMPOWERED KABBAGE WITH SMARTER DECISION-MAKING FOR LOAN DISBURSAL
    • 5.7.12 CASE STUDY 12: CHAINALYSIS DEPLOYED NLP FOR FRAUD PREVENTION IN CRYPTO TRADING
  • 5.8 SUPPLY CHAIN ANALYSIS
    • FIGURE 23 NLP IN FINANCE MARKET: SUPPLY CHAIN ANALYSIS
    • TABLE 5 NLP IN FINANCE MARKET: SUPPLY CHAIN ANALYSIS
  • 5.9 REGULATORY LANDSCAPE
    • 5.9.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • TABLE 6 NORTH AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • TABLE 7 EUROPE: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • TABLE 8 ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • TABLE 9 MIDDLE EAST & AFRICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • TABLE 10 LATIN AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • 5.9.2 NORTH AMERICA
      • 5.9.2.1 Fair Credit Reporting Act (FCRA)
      • 5.9.2.2 Consumer Financial Protection Act (CFPA)
      • 5.9.2.3 Gramm-Leach-Bliley Act (GLBA)
      • 5.9.2.4 Sarbanes-Oxley Act (SOX)
      • 5.9.2.5 Dodd-Frank Wall Street Reform and Consumer Protection Act
    • 5.9.3 EUROPE
      • 5.9.3.1 Markets in Financial Instruments Directive II (MiFID II)
      • 5.9.3.2 General Data Protection Regulation (GDPR)
      • 5.9.3.3 Payment Services Directive 2 (PSD2)
      • 5.9.3.4 Markets in Financial Instruments Regulation (MiFIR)
      • 5.9.3.5 Anti-Money Laundering (AML) Directive
    • 5.9.4 ASIA PACIFIC
      • 5.9.4.1 Personal Information Protection Act (PIPA) - Japan
      • 5.9.4.2 Personal Data Protection Act (PDPA) - Singapore
      • 5.9.4.3 Information Technology Act (ITA) - India
      • 5.9.4.4 Personal Information Protection Law (PIPL) - China
      • 5.9.4.5 Privacy Act - Australia
    • 5.9.5 LATIN AMERICA
      • 5.9.5.1 General Data Protection Law (LGPD) - Brazil
      • 5.9.5.2 Data Protection Law (Ley de Proteccion de Datos Personales) - Mexico
      • 5.9.5.3 Financial Institutions Law (Ley de Instituciones de Credito) - Mexico
      • 5.9.5.4 Anti-Money Laundering (AML) Law - Colombia
      • 5.9.5.5 Financial Sector Law (Ley del Sector Financiero) - Colombia
    • 5.9.6 MIDDLE EAST AND AFRICA
      • 5.9.6.1 Dubai Financial Services Authority (DFSA) Regulations
      • 5.9.6.2 Financial Sector Regulation (FSR) - South Africa
      • 5.9.6.3 Anti-Money Laundering and Countering Financing of Terrorism (AML/CFT) Regulations - Saudi Arabia
      • 5.9.6.4 Data Protection and Privacy Regulations - Egypt
      • 5.9.6.5 Financial Services Authority (FSA) Regulations - Morocco
  • 5.10 PATENT ANALYSIS
    • 5.10.1 METHODOLOGY
    • 5.10.2 PATENTS FILED, BY DOCUMENT TYPE, 2019-2022
    • TABLE 11 PATENTS FILED, 2019-2022
    • 5.10.3 INNOVATION AND PATENT APPLICATIONS
    • FIGURE 24 TOTAL NUMBER OF PATENTS GRANTED, 2013-2022
    • 5.10.4 TOP APPLICANTS
    • FIGURE 25 TOP 10 COMPANIES WITH HIGHEST NUMBER OF PATENT APPLICATIONS IN LAST 10 YEARS, 2013-2022
    • TABLE 12 TOP 20 PATENT OWNERS IN NLP IN FINANCE MARKET, 2013-2022
    • TABLE 13 LIST OF PATENTS IN NLP IN FINANCE MARKET, 2021-2023
    • FIGURE 26 REGIONAL ANALYSIS OF PATENTS GRANTED FOR NLP IN FINANCE MARKET, 2013-2022
  • 5.11 KEY CONFERENCES AND EVENTS, 2023-2024
    • TABLE 14 NLP IN FINANCE MARKET: DETAILED LIST OF CONFERENCES AND EVENTS
  • 5.12 PRICING ANALYSIS
    • FIGURE 27 INDICATIVE SELLING PRICES OF KEY PLAYERS FOR TOP 3 APPLICATIONS
    • TABLE 15 AVERAGE SELLING PRICING ANALYSIS OF KEY PLAYERS FOR TOP 3 APPLICATIONS (USD)
  • 5.13 PORTER'S FIVE FORCES ANALYSIS
    • TABLE 16 IMPACT OF EACH FORCE ON NLP IN FINANCE MARKET
    • FIGURE 28 NLP IN FINANCE MARKET: PORTER'S FIVE FORCES ANALYSIS
    • 5.13.1 THREAT OF NEW ENTRANTS
    • 5.13.2 THREAT OF SUBSTITUTES
    • 5.13.3 BARGAINING POWER OF SUPPLIERS
    • 5.13.4 BARGAINING POWER OF BUYERS
    • 5.13.5 INTENSITY OF COMPETITIVE RIVALRY
  • 5.14 KEY STAKEHOLDERS AND BUYING CRITERIA
    • 5.14.1 KEY STAKEHOLDERS IN BUYING PROCESS
    • FIGURE 29 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE APPLICATIONS
    • TABLE 17 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE APPLICATIONS
    • 5.14.2 BUYING CRITERIA
    • FIGURE 30 KEY BUYING CRITERIA FOR TOP THREE APPLICATIONS
    • TABLE 18 KEY BUYING CRITERIA FOR TOP THREE APPLICATIONS
  • 5.15 TRENDS/DISRUPTIONS IMPACTING BUYERS/CLIENTS OF NLP IN FINANCE MARKET
    • FIGURE 31 NLP IN FINANCE MARKET: TRENDS/DISRUPTIONS IMPACTING BUYERS/CLIENTS
  • 5.16 BEST PRACTICES IN NLP IN FINANCE MARKET
    • 5.16.1 DOMAIN-SPECIFIC DATA SELECTION AND DATA CLEANING
    • 5.16.2 FEATURE ENGINEERING
    • 5.16.3 MODEL SELECTION
    • 5.16.4 EVALUATION METRICS
    • 5.16.5 CROSS-VALIDATION
    • 5.16.6 REGULARIZATION
    • 5.16.7 HYPERPARAMETER TUNING
    • 5.16.8 TRANSFER LEARNING
    • 5.16.9 INTERPRETABILITY
    • 5.16.10 REGULATORY COMPLIANCE
    • 5.16.11 BACKTESTING AND DEPLOYMENT
  • 5.17 TECHNOLOGY ROADMAP OF NLP IN FINANCE
    • 5.17.1 NLP IN FINANCE ROADMAP TILL 2030
    • TABLE 19 NLP IN FINANCE ROADMAP TILL 2030
      • 5.17.1.1 Pre-2020
      • 5.17.1.2 2020-2022
      • 5.17.1.3 Short-term (2023-2025)
      • 5.17.1.4 Mid-term (2026-2028)
      • 5.17.1.5 Long-term (2029-2030)
  • 5.18 CURRENT AND EMERGING BUSINESS MODELS
    • 5.18.1 SAAS MODEL
    • 5.18.2 CONSULTING SERVICES MODEL
    • 5.18.3 PARTNER PROGRAMS (REVENUE SHARING MODEL)
    • 5.18.4 PAY-PER-USE MODEL
  • 5.19 NLP IN FINANCE'S IMPACT ON ADJACENT NICHE TECHNOLOGIES
    • 5.19.1 HIGH-FREQUENCY TRADING AND ELECTRONIC TRADING PLATFORMS
    • 5.19.2 FINANCIAL CYBERSECURITY
    • 5.19.3 REGULATORY TECHNOLOGY (REGTECH)

6 NLP IN FINANCE MARKET, BY OFFERING

  • 6.1 INTRODUCTION
    • 6.1.1 OFFERING: NLP IN FINANCE MARKET DRIVERS
    • FIGURE 32 SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
    • TABLE 20 NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 21 NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
  • 6.2 SOFTWARE
    • TABLE 22 SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 23 SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
    • 6.2.1 NLP IN FINANCE SOFTWARE, BY SOFTWARE TYPE
    • FIGURE 33 STATISTICAL NLP SOFTWARE TO HOLD LARGEST MARKET SHARE IN 2023
    • TABLE 24 SOFTWARE: NLP IN FINANCE MARKET, BY SOFTWARE TYPE, 2019-2022 (USD MILLION)
    • TABLE 25 SOFTWARE: NLP IN FINANCE MARKET, BY SOFTWARE TYPE, 2023-2028 (USD MILLION)
      • 6.2.1.1 Rule-based NLP Software
        • 6.2.1.1.1 Rule-based NLP software to help financial institutions automate compliance and risk management processes
    • TABLE 26 RULE-BASED NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 27 RULE-BASED NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
          • 6.2.1.1.1.1 Regular Expression (Regex)
          • 6.2.1.1.1.2 Finite State Machines (FSMs)
          • 6.2.1.1.1.3 Named Entity Recognition (NER)
          • 6.2.1.1.1.4 Part-of-Speech (POS) Tagging
      • 6.2.1.2 Statistical NLP Software
        • 6.2.1.2.1 Statistical NLP software to analyze large volumes of unstructured data
    • TABLE 28 STATISTICAL NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 29 STATISTICAL NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
          • 6.2.1.2.1.1 Naive Bayes
          • 6.2.1.2.1.2 Logistic Regression
          • 6.2.1.2.1.3 Support Vector Machines (SVMs)
          • 6.2.1.2.1.4 Recurrent Neural Networks (RNNs)
      • 6.2.1.3 Hybrid NLP Software
        • 6.2.1.3.1 Hybrid NLP to combine strengths of rule-based and statistical approaches
    • TABLE 30 HYBRID NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 31 HYBRID NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
          • 6.2.1.3.1.1 Latent Dirichlet Allocation (LDA)
          • 6.2.1.3.1.2 Hidden Markov Models (HMMs)
          • 6.2.1.3.1.3 Conditional Random Fields (CRFs)
  • 6.3 SERVICES
    • FIGURE 34 MANAGED SERVICES SEGMENT TO REGISTER HIGHER CAGR IN NLP IN FINANCE MARKET FOR SERVICES DURING FORECAST PERIOD
    • TABLE 32 NLP IN FINANCE MARKET, BY SERVICE, 2019-2022 (USD MILLION)
    • TABLE 33 NLP IN FINANCE MARKET, BY SERVICE, 2023-2028 (USD MILLION)
    • TABLE 34 SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 35 SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
    • 6.3.1 PROFESSIONAL SERVICES
      • 6.3.1.1 Professional services to offer specialized expertise in NLP in finance
    • FIGURE 35 TRAINING AND CONSULTING SERVICES SUB-SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
    • TABLE 36 SERVICES: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2019-2022 (USD MILLION)
    • TABLE 37 SERVICES: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2023-2028 (USD MILLION)
    • TABLE 38 PROFESSIONAL SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 39 PROFESSIONAL SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
        • 6.3.1.1.1 Training and consulting services
    • TABLE 40 TRAINING AND CONSULTING SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 41 TRAINING AND CONSULTING SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
        • 6.3.1.1.2 System integration and implementation services
    • TABLE 42 SYSTEM INTEGRATION AND IMPLEMENTATION SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 43 SYSTEM INTEGRATION AND IMPLEMENTATION SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
        • 6.3.1.1.3 Support and maintenance services
    • TABLE 44 SUPPORT AND MAINTENANCE SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 45 SUPPORT AND MAINTENANCE SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
    • 6.3.2 MANAGED SERVICES
      • 6.3.2.1 Managed services to provide end-to-end management to help businesses focus on core competencies
    • TABLE 46 MANAGED SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 47 MANAGED SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)

7 NLP IN FINANCE MARKET, BY APPLICATION

  • 7.1 INTRODUCTION
    • 7.1.1 APPLICATION: NLP IN FINANCE MARKET DRIVERS
    • FIGURE 36 NATURAL LANGUAGE GENERATION SEGMENT TO ACCOUNT FOR LARGEST MARKET SHARE IN 2023
    • TABLE 48 NLP IN FINANCE MARKET, BY APPLICATION, 2019-2022 (USD MILLION)
    • TABLE 49 NLP IN FINANCE MARKET, BY APPLICATION, 2023-2028 (USD MILLION)
  • 7.2 SENTIMENT ANALYSIS
    • 7.2.1 SENTIMENT ANALYSIS TO IDENTIFY AND MITIGATE POTENTIAL FINANCIAL RISKS
    • TABLE 50 SENTIMENT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 51 SENTIMENT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 7.2.1.1 Brand reputation management
      • 7.2.1.2 Market sentiment analysis
      • 7.2.1.3 Customer feedback analysis
      • 7.2.1.4 Product review analysis
      • 7.2.1.5 Social media monitoring
  • 7.3 RISK MANAGEMENT AND FRAUD DETECTION
    • 7.3.1 NLP TO IMPROVE SPEED AND ACCURACY OF RISK IDENTIFICATION AND FRAUD DETECTION
    • TABLE 52 RISK MANAGEMENT AND FRAUD DETECTION: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 53 RISK MANAGEMENT AND FRAUD DETECTION: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 7.3.1.1 Credit risk assessment
      • 7.3.1.2 Fraud Detection and Prevention
      • 7.3.1.3 Anti-money laundering (AML)
      • 7.3.1.4 Compliance monitoring
      • 7.3.1.5 Cybersecurity threat detection
  • 7.4 COMPLIANCE MONITORING
    • 7.4.1 NLP TO ANALYZE FINANCIAL TRANSACTIONS AND IDENTIFY POTENTIAL NON-COMPLIANCE ISSUES
    • TABLE 54 COMPLIANCE MONITORING: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 55 COMPLIANCE MONITORING: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 7.4.1.1 Regulatory compliance monitoring
      • 7.4.1.2 KYC/AML compliance monitoring
      • 7.4.1.3 Legal and policy compliance monitoring
      • 7.4.1.4 Audit trail monitoring
      • 7.4.1.5 Trade surveillance
  • 7.5 INVESTMENT ANALYSIS
    • 7.5.1 FINANCIAL INSTITUTIONS INVESTING IN NLP TECHNOLOGY TO HAVE COMPETITIVE EDGE
    • TABLE 56 INVESTMENT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 57 INVESTMENT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 7.5.1.1 Asset allocation and portfolio optimization
      • 7.5.1.2 Equity research and analysis
      • 7.5.1.3 Quantitative analysis and modeling
      • 7.5.1.4 Investment recommendations and planning
      • 7.5.1.5 Risk management and prediction
      • 7.5.1.6 Investment opportunity identification
  • 7.6 FINANCIAL NEWS AND MARKET ANALYSIS
    • 7.6.1 NLP ALGORITHMS TO PREDICT HOW MARKETS REACT AND HELP INVESTORS MAKE INFORMED INVESTMENT DECISIONS
    • TABLE 58 FINANCIAL NEWS AND MARKET ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 59 FINANCIAL NEWS AND MARKET ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 7.6.1.1 Financial news analysis
      • 7.6.1.2 Stock market prediction
      • 7.6.1.3 Macroeconomic analysis
  • 7.7 CUSTOMER SERVICE AND SUPPORT
    • 7.7.1 ADOPTION OF INTELLIGENT CHATBOTS AND CUSTOMER SUPPORT SYSTEMS TO DRIVE GROWTH
    • TABLE 60 CUSTOMER SERVICE AND SUPPORT: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 61 CUSTOMER SERVICE AND SUPPORT: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 7.7.1.1 Chatbots and virtual assistants
      • 7.7.1.2 Personalized support and service
      • 7.7.1.3 Compliant resolution
      • 7.7.1.4 Query resolution and escalation management
      • 7.7.1.5 Self-service options
      • 7.7.1.6 Multilingual customer service and support
  • 7.8 DOCUMENT AND CONTRACT ANALYSIS
    • 7.8.1 DOCUMENT AND CONTRACT ANALYSIS TO STREAMLINE DATA PROCESSING WORKFLOWS
    • TABLE 62 DOCUMENT AND CONTRACT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 63 DOCUMENT AND CONTRACT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 7.8.1.1 Contract management
      • 7.8.1.2 Legal document analysis
      • 7.8.1.3 Due diligence analysis
      • 7.8.1.4 Data extraction and normalization
  • 7.9 SPEECH RECOGNITION AND TRANSCRIPTION
    • 7.9.1 POWERFUL TOOL TO CAPTURE AND ANALYZE VOICE DATA AND ENSURE COMPLIANCE
    • TABLE 64 SPEECH RECOGNITION AND TRANSCRIPTION: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 65 SPEECH RECOGNITION AND TRANSCRIPTION: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 7.9.1.1 Voice-enabled search and navigation
      • 7.9.1.2 Speech-to-text conversion
      • 7.9.1.3 Call transcription and analysis
      • 7.9.1.4 Voice biometrics and authentication
      • 7.9.1.5 Speech-enabled virtual assistants
  • 7.10 LANGUAGE TRANSLATION
    • 7.10.1 AUTOMATING REPORT WRITING AND PERSONALIZED FINANCIAL ADVICE TO DRIVE UPTAKE OF LANGUAGE TRANSLATION TOOLS
    • TABLE 66 LANGUAGE TRANSLATION: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 67 LANGUAGE TRANSLATION: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 7.10.1.1 Financial document translation
      • 7.10.1.2 Investment research translation
      • 7.10.1.3 Cross-border business communication
      • 7.10.1.4 Localization and internationalization
  • 7.11 OTHER APPLICATIONS
    • TABLE 68 OTHER APPLICATIONS: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 69 OTHER APPLICATIONS: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)

8 NLP IN FINANCE MARKET, BY TECHNOLOGY

  • 8.1 INTRODUCTION
    • 8.1.1 TECHNOLOGY: NLP IN FINANCE MARKET DRIVERS
    • FIGURE 37 DEEP LEARNING SEGMENT TO GROW AT HIGHER CAGR
    • TABLE 70 NLP IN FINANCE MARKET, BY TECHNOLOGY, 2019-2022 (USD MILLION)
    • TABLE 71 NLP IN FINANCE MARKET, BY TECHNOLOGY, 2023-2028 (USD MILLION)
  • 8.2 MACHINE LEARNING
    • 8.2.1 MACHINE LEARNING TO BE EXTENSIVELY DEPLOYED TO PREDICT FINANCIAL MARKET INSIGHTS
    • TABLE 72 MACHINE LEARNING: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 73 MACHINE LEARNING: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 8.2.1.1 Supervised learning
      • 8.2.1.2 Unsupervised learning
      • 8.2.1.3 Reinforcement learning
  • 8.3 DEEP LEARNING
    • 8.3.1 DEEP LEARNING TO PLAY CRITICAL ROLE IN ADVANCING NLP DEVELOPMENTS
    • TABLE 74 DEEP LEARNING: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 75 DEEP LEARNING: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 8.3.1.1 Convolutional neural networks (CNN)
      • 8.3.1.2 Recurrent neural networks (RNN)
      • 8.3.1.3 Transformer models (BERT, GPT-3, etc.)
  • 8.4 NATURAL LANGUAGE GENERATION
    • 8.4.1 FINANCIAL INSTITUTIONS TO INCREASINGLY ADOPT NLG TO IMPROVE EFFICIENCY AND REDUCE COSTS
    • TABLE 76 NATURAL LANGUAGE GENERATION: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 77 NATURAL LANGUAGE GENERATION: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 8.4.1.1 Automated report writing
      • 8.4.1.2 Customer communication
      • 8.4.1.3 Financial document generation
  • 8.5 TEXT CLASSIFICATION
    • 8.5.1 TEXT CLASSIFICATION TO ANALYZE MARKET SENTIMENTS IN FINANCE
    • TABLE 78 TEXT CLASSIFICATION: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 79 TEXT CLASSIFICATION: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 8.5.1.1 Sentiment classification
      • 8.5.1.2 Intent classification
  • 8.6 TOPIC MODELING
    • 8.6.1 TOPIC MODELING TO EXTRACT INSIGHTS FROM FINANCIAL NEWS ARTICLES
    • TABLE 80 TOPIC MODELING: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 81 TOPIC MODELING: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 8.6.1.1 Topic identification
      • 8.6.1.2 Topic clustering
      • 8.6.1.3 Topic visualization
  • 8.7 EMOTION DETECTION
    • 8.7.1 EMOTION DETECTION TO IMPROVE SENTIMENT ANALYSIS IN FINANCIAL DISCOURSE
    • TABLE 82 EMOTION DETECTION: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 83 EMOTION DETECTION: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 8.7.1.1 Emotion recognition
      • 8.7.1.2 Emotion classification
  • 8.8 OTHER TECHNOLOGIES
    • 8.8.1 NER AND EVENT EXTRACTION TO FACE SPIKE IN HANDLING UNSTRUCTURED FINANCIAL DATA
    • TABLE 84 OTHER TECHNOLOGIES: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 85 OTHER TECHNOLOGIES: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)

9 NLP IN FINANCE MARKET, BY VERTICAL

  • 9.1 INTRODUCTION
    • 9.1.1 VERTICAL: NLP IN FINANCE MARKET DRIVERS
    • FIGURE 38 INSURANCE SEGMENT TO GROW AT HIGHEST CAGR
    • TABLE 86 NLP IN FINANCE MARKET, BY VERTICAL, 2019-2022 (USD MILLION)
    • TABLE 87 NLP IN FINANCE MARKET, BY VERTICAL, 2023-2028 (USD MILLION)
  • 9.2 BANKING
    • 9.2.1 NLP TO IMPROVE EFFICIENCY, ACCURACY, AND CUSTOMER EXPERIENCE
    • 9.2.2 NLP IN FINANCE: BANKING USE CASES
    • TABLE 88 BANKING: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 89 BANKING: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 9.2.2.1 Retail banking
      • 9.2.2.2 Corporate banking
      • 9.2.2.3 Investment banking
      • 9.2.2.4 Wealth management
  • 9.3 INSURANCE
    • 9.3.1 INSURANCE COMPANIES TO ANALYZE LARGE AMOUNTS OF DATA USING NLP
    • 9.3.2 NLP IN FINANCE: INSURANCE USE CASES
    • TABLE 90 INSURANCE: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 91 INSURANCE: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 9.3.2.1 Life insurance
      • 9.3.2.2 Property and casualty insurance
      • 9.3.2.3 Health insurance
  • 9.4 FINANCIAL SERVICES
    • 9.4.1 USE OF NLP TO GROW IN FINTECH
    • 9.4.2 NLP IN FINANCE: FINANCIAL SERVICES USE CASES
    • TABLE 92 FINANCIAL SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 93 FINANCIAL SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
      • 9.4.2.1 Credit rating
      • 9.4.2.2 Payment processing and remitting
      • 9.4.2.3 Accounting and auditing
      • 9.4.2.4 Personal finance management
      • 9.4.2.5 Robo-advisory
      • 9.4.2.6 Cryptocurrencies and blockchain
      • 9.4.2.7 Stock movement prediction
      • 9.4.2.8 Others
  • 9.5 OTHER ENTERPRISE VERTICALS
    • 9.5.1 NLP IN FINANCE TO MAKE INROADS ACROSS FINANCIAL OPERATIONS
      • 9.5.1.1 Healthcare and life sciences
      • 9.5.1.2 Manufacturing
      • 9.5.1.3 Retail and eCommerce
      • 9.5.1.4 Energy & utilities
      • 9.5.1.5 Transportation and logistics
      • 9.5.1.6 Others

10 NLP IN FINANCE MARKET, BY REGION

  • 10.1 INTRODUCTION
    • FIGURE 39 ASIA PACIFIC NLP IN FINANCE MARKET TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
    • FIGURE 40 INDIA TO REGISTER HIGHEST CAGR IN NLP IN FINANCE
    • TABLE 94 NLP IN FINANCE MARKET, BY REGION, 2019-2022 (USD MILLION)
    • TABLE 95 NLP IN FINANCE MARKET, BY REGION, 2023-2028 (USD MILLION)
  • 10.2 NORTH AMERICA
    • 10.2.1 NORTH AMERICA: NLP IN FINANCE MARKET DRIVERS
    • 10.2.2 NORTH AMERICA: RECESSION IMPACT
    • FIGURE 41 NORTH AMERICA: SNAPSHOT OF NLP IN FINANCE MARKET
    • TABLE 96 NORTH AMERICA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 97 NORTH AMERICA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • TABLE 98 NORTH AMERICA: NLP IN FINANCE MARKET, BY SOFTWARE, 2019-2022 (USD MILLION)
    • TABLE 99 NORTH AMERICA: NLP IN FINANCE MARKET, BY SOFTWARE, 2023-2028 (USD MILLION)
    • TABLE 100 NORTH AMERICA: NLP IN FINANCE MARKET, BY SERVICE, 2019-2022 (USD MILLION)
    • TABLE 101 NORTH AMERICA: NLP IN FINANCE MARKET, BY SERVICE, 2023-2028 (USD MILLION)
    • TABLE 102 NORTH AMERICA: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2019-2022 (USD MILLION)
    • TABLE 103 NORTH AMERICA: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2023-2028 (USD MILLION)
    • TABLE 104 NORTH AMERICA: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2019-2022 (USD MILLION)
    • TABLE 105 NORTH AMERICA: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2023-2028 (USD MILLION)
    • TABLE 106 NORTH AMERICA: NLP IN FINANCE MARKET, BY APPLICATION, 2019-2022 (USD MILLION)
    • TABLE 107 NORTH AMERICA: NLP IN FINANCE MARKET, BY APPLICATION, 2023-2028 (USD MILLION)
    • TABLE 108 NORTH AMERICA: NLP IN FINANCE MARKET, BY VERTICAL, 2019-2022 (USD MILLION)
    • TABLE 109 NORTH AMERICA: NLP IN FINANCE MARKET, BY VERTICAL, 2023-2028 (USD MILLION)
    • TABLE 110 NORTH AMERICA: NLP IN FINANCE MARKET, BY COUNTRY, 2019-2022 (USD MILLION)
    • TABLE 111 NORTH AMERICA: NLP IN FINANCE MARKET, BY COUNTRY, 2023-2028 (USD MILLION)
    • 10.2.3 US
      • 10.2.3.1 US to implement NLP for real-time data analysis
    • TABLE 112 US: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 113 US: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.2.4 CANADA
      • 10.2.4.1 Canadian banks to use NLP-powered chatbots to interact with customers
    • TABLE 114 CANADA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 115 CANADA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
  • 10.3 EUROPE
    • 10.3.1 EUROPE: NLP IN FINANCE MARKET DRIVERS
    • 10.3.2 EUROPE: RECESSION IMPACT
    • TABLE 116 EUROPE: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 117 EUROPE: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • TABLE 118 EUROPE: NLP IN FINANCE MARKET, BY SOFTWARE, 2019-2022 (USD MILLION)
    • TABLE 119 EUROPE: NLP IN FINANCE MARKET, BY SOFTWARE, 2023-2028 (USD MILLION)
    • TABLE 120 EUROPE: NLP IN FINANCE MARKET, BY SERVICE, 2019-2022 (USD MILLION)
    • TABLE 121 EUROPE: NLP IN FINANCE MARKET, BY SERVICE, 2023-2028 (USD MILLION)
    • TABLE 122 EUROPE: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2019-2022 (USD MILLION)
    • TABLE 123 EUROPE: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2023-2028 (USD MILLION)
    • TABLE 124 EUROPE: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2019-2022 (USD MILLION)
    • TABLE 125 EUROPE: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2023-2028 (USD MILLION)
    • TABLE 126 EUROPE: NLP IN FINANCE MARKET, BY APPLICATION, 2019-2022 (USD MILLION)
    • TABLE 127 EUROPE: NLP IN FINANCE MARKET, BY APPLICATION, 2023-2028 (USD MILLION)
    • TABLE 128 EUROPE: NLP IN FINANCE MARKET, BY VERTICAL, 2019-2022 (USD MILLION)
    • TABLE 129 EUROPE: NLP IN FINANCE MARKET, BY VERTICAL, 2023-2028 (USD MILLION)
    • TABLE 130 EUROPE: NLP IN FINANCE MARKET, BY COUNTRY, 2019-2022 (USD MILLION)
    • TABLE 131 EUROPE: NLP IN FINANCE MARKET, BY COUNTRY, 2023-2028 (USD MILLION)
    • 10.3.3 UK
      • 10.3.3.1 UK companies to leverage NLP to improve operations and gain competitive edge
    • TABLE 132 UK: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 133 UK: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.3.4 GERMANY
      • 10.3.4.1 Adoption of NLP to be driven by regulatory compliance, cost reduction, and better customer experience
    • TABLE 134 GERMANY: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 135 GERMANY: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.3.5 FRANCE
      • 10.3.5.1 France to witness emergence of AI-based chatbots using NLP
    • TABLE 136 FRANCE: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 137 FRANCE: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.3.6 ITALY
      • 10.3.6.1 NLP to help financial institutions analyze large volumes of data efficiently and accurately
    • TABLE 138 ITALY: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 139 ITALY: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.3.7 SPAIN
      • 10.3.7.1 NLP to significantly improve customer service and reduce operating costs in banking
    • TABLE 140 SPAIN: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 141 SPAIN: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.3.8 SWITZERLAND
      • 10.3.8.1 Swiss banks and financial institutions to invest in NLP to gain competitive advantage
    • TABLE 142 SWITZERLAND: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 143 SWITZERLAND: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.3.9 REST OF EUROPE
    • TABLE 144 REST OF EUROPE: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 145 REST OF EUROPE: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
  • 10.4 ASIA PACIFIC
    • 10.4.1 ASIA PACIFIC: NLP IN FINANCE MARKET DRIVERS
    • 10.4.2 ASIA PACIFIC: RECESSION IMPACT
    • FIGURE 42 ASIA PACIFIC: SNAPSHOT OF NLP IN FINANCE MARKET
    • TABLE 146 ASIA PACIFIC: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 147 ASIA PACIFIC: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • TABLE 148 ASIA PACIFIC: NLP IN FINANCE MARKET, BY SOFTWARE, 2019-2022 (USD MILLION)
    • TABLE 149 ASIA PACIFIC: NLP IN FINANCE MARKET, BY SOFTWARE, 2023-2028 (USD MILLION)
    • TABLE 150 ASIA PACIFIC: NLP IN FINANCE MARKET, BY SERVICE, 2019-2022 (USD MILLION)
    • TABLE 151 ASIA PACIFIC: NLP IN FINANCE MARKET, BY SERVICE, 2023-2028 (USD MILLION)
    • TABLE 152 ASIA PACIFIC: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2019-2022 (USD MILLION)
    • TABLE 153 ASIA PACIFIC: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2023-2028 (USD MILLION)
    • TABLE 154 ASIA PACIFIC: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2019-2022 (USD MILLION)
    • TABLE 155 ASIA PACIFIC: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2023-2028 (USD MILLION)
    • TABLE 156 ASIA PACIFIC: NLP IN FINANCE MARKET, BY APPLICATION, 2019-2022 (USD MILLION)
    • TABLE 157 ASIA PACIFIC: NLP IN FINANCE MARKET, BY APPLICATION, 2023-2028 (USD MILLION)
    • TABLE 158 ASIA PACIFIC: NLP IN FINANCE MARKET, BY VERTICAL, 2019-2022 (USD MILLION)
    • TABLE 159 ASIA PACIFIC: NLP IN FINANCE MARKET, BY VERTICAL, 2023-2028 (USD MILLION)
    • TABLE 160 ASIA PACIFIC: NLP IN FINANCE MARKET, BY COUNTRY, 2019-2022 (USD MILLION)
    • TABLE 161 ASIA PACIFIC: NLP IN FINANCE MARKET, BY COUNTRY, 2023-2028 (USD MILLION)
    • 10.4.3 CHINA
      • 10.4.3.1 NLP solutions to develop as demand for digital transformation increases
    • TABLE 162 CHINA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 163 CHINA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.4.4 INDIA
      • 10.4.4.1 Adoption of NLP in banking to be influenced by startups and Digital India movement
    • TABLE 164 INDIA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 165 INDIA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.4.5 JAPAN
      • 10.4.5.1 NLP potential to be unlocked in Japan's finance markets
    • TABLE 166 JAPAN: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 167 JAPAN: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.4.6 SOUTH KOREA
      • 10.4.6.1 NLP to change financial sector by improving consumer experience
    • TABLE 168 SOUTH KOREA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 169 SOUTH KOREA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.4.7 SINGAPORE
      • 10.4.7.1 Singapore to improve its financial services and stay competitive using NLP
    • TABLE 170 SINGAPORE: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 171 SINGAPORE: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.4.8 ANZ
      • 10.4.8.1 NLP solutions to gain more prominence due to technology development
    • TABLE 172 ANZ: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 173 ANZ: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.4.9 REST OF ASIA PACIFIC
    • TABLE 174 REST OF ASIA PACIFIC: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 175 REST OF ASIA PACIFIC: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
  • 10.5 MIDDLE EAST & AFRICA
    • 10.5.1 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET DRIVERS
    • 10.5.2 MIDDLE EAST & AFRICA: RECESSION IMPACT
    • TABLE 176 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 177 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • TABLE 178 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY SOFTWARE, 2019-2022 (USD MILLION)
    • TABLE 179 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY SOFTWARE, 2023-2028 (USD MILLION)
    • TABLE 180 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY SERVICE, 2019-2022 (USD MILLION)
    • TABLE 181 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY SERVICE, 2023-2028 (USD MILLION)
    • TABLE 182 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2019-2022 (USD MILLION)
    • TABLE 183 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2023-2028 (USD MILLION)
    • TABLE 184 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2019-2022 (USD MILLION)
    • TABLE 185 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2023-2028 (USD MILLION)
    • TABLE 186 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY APPLICATION, 2019-2022 (USD MILLION)
    • TABLE 187 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY APPLICATION, 2023-2028 (USD MILLION)
    • TABLE 188 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY VERTICAL, 2019-2022 (USD MILLION)
    • TABLE 189 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY VERTICAL, 2023-2028 (USD MILLION)
    • TABLE 190 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY COUNTRY, 2019-2022 (USD MILLION)
    • TABLE 191 MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY COUNTRY, 2023-2028 (USD MILLION)
    • 10.5.3 SAUDI ARABIA
      • 10.5.3.1 Saudi Arabia to embrace NLP to drive economic growth
    • TABLE 192 SAUDI ARABIA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 193 SAUDI ARABIA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.5.4 UAE
      • 10.5.4.1 Several UAE startups to leverage NLP to drive innovation
    • TABLE 194 UAE: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 195 UAE: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.5.5 SOUTH AFRICA
      • 10.5.5.1 South Africa to witness several developments in NLP
    • TABLE 196 SOUTH AFRICA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 197 SOUTH AFRICA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.5.6 ISRAEL
      • 10.5.6.1 Adoption of NLP to position country as leader in technological advancements
    • TABLE 198 ISRAEL: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 199 ISRAEL: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • 10.5.7 REST OF MIDDLE EAST & AFRICA
    • TABLE 200 REST OF MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 201 REST OF MIDDLE EAST & AFRICA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
  • 10.6 LATIN AMERICA
    • 10.6.1 LATIN AMERICA: NLP IN FINANCE MARKET DRIVERS
    • 10.6.2 LATIN AMERICA: RECESSION IMPACT
    • TABLE 202 LATIN AMERICA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 203 LATIN AMERICA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
    • TABLE 204 LATIN AMERICA: NLP IN FINANCE MARKET, BY SOFTWARE, 2019-2022 (USD MILLION)
    • TABLE 205 LATIN AMERICA: NLP IN FINANCE MARKET, BY SOFTWARE, 2023-2028 (USD MILLION)
    • TABLE 206 LATIN AMERICA: NLP IN FINANCE MARKET, BY SERVICE, 2019-2022 (USD MILLION)
    • TABLE 207 LATIN AMERICA: NLP IN FINANCE MARKET, BY SERVICE, 2023-2028 (USD MILLION)
    • TABLE 208 LATIN AMERICA: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2019-2022 (USD MILLION)
    • TABLE 209 LATIN AMERICA: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2023-2028 (USD MILLION)
    • TABLE 210 LATIN AMERICA: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2019-2022 (USD MILLION)
    • TABLE 211 LATIN AMERICA: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2023-2028 (USD MILLION)
    • TABLE 212 LATIN AMERICA: NLP IN FINANCE MARKET, BY APPLICATION, 2019-2022 (USD MILLION)
    • TABLE 213 LATIN AMERICA: NLP IN FINANCE MARKET, BY APPLICATION, 2023-2028 (USD MILLION)
    • TABLE 214 LATIN AMERICA: NLP IN FINANCE MARKET, BY VERTICAL, 2019-2022 (USD MILLION)
    • TABLE 215 LATIN AMERICA: NLP IN FINANCE MARKET, BY VERTICAL, 2023-2028 (USD MILLION)
    • TABLE 216 LATIN AMERICA: NLP IN FINANCE MARKET, BY COUNTRY, 2019-2022 (USD MILLION)
    • TABLE 217 LATIN AMERICA: NLP IN FINANCE MARKET, BY COUNTRY, 2023-2028 (USD MILLION)
      • 10.6.2.1 Brazil
        • 10.6.2.1.1 NLP to be used in customer service
    • TABLE 218 BRAZIL: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 219 BRAZIL: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
      • 10.6.2.2 Mexico
        • 10.6.2.2.1 NLP to witness wide adoption in finance
    • TABLE 220 MEXICO: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 221 MEXICO: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
      • 10.6.2.3 Argentina
        • 10.6.2.3.1 Advancements in NLP to change ways how financial institutions interact with customers
    • TABLE 222 ARGENTINA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 223 ARGENTINA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)
      • 10.6.2.4 Rest of Latin America
    • TABLE 224 REST OF LATIN AMERICA: NLP IN FINANCE MARKET, BY OFFERING, 2019-2022 (USD MILLION)
    • TABLE 225 REST OF LATIN AMERICA: NLP IN FINANCE MARKET, BY OFFERING, 2023-2028 (USD MILLION)

11 COMPETITIVE LANDSCAPE

  • 11.1 OVERVIEW
  • 11.2 KEY STRATEGIES ADOPTED BY MAJOR PLAYERS
    • TABLE 226 OVERVIEW OF STRATEGIES ADOPTED BY KEY NLP IN FINANCE VENDORS
  • 11.3 REVENUE ANALYSIS
    • 11.3.1 HISTORIC REVENUE ANALYSIS
    • FIGURE 43 HISTORIC REVENUE ANALYSIS OF TOP FIVE PLAYERS, 2020-2022 (USD MILLION)
  • 11.4 MARKET SHARE ANALYSIS
    • FIGURE 44 MARKET SHARE ANALYSIS FOR KEY COMPANIES IN 2022
    • TABLE 227 NLP IN FINANCE MARKET: DEGREE OF COMPETITION
  • 11.5 COMPANY EVALUATION QUADRANT
    • 11.5.1 STARS
    • 11.5.2 EMERGING LEADERS
    • 11.5.3 PERVASIVE PLAYERS
    • 11.5.4 PARTICIPANTS
    • FIGURE 45 NLP IN FINANCE MARKET: COMPANY EVALUATION QUADRANT, 2022
  • 11.6 COMPETITIVE BENCHMARKING
    • TABLE 228 NLP IN FINANCE MARKET: PRODUCT FOOTPRINT ANALYSIS OF KEY PLAYERS, 2022
    • TABLE 229 NLP IN FINANCE MARKET: PRODUCT FOOTPRINT ANALYSIS OF OTHER KEY PLAYERS, 2022
  • 11.7 STARTUP/SME EVALUATION QUADRANT
    • 11.7.1 PROGRESSIVE COMPANIES
    • 11.7.2 RESPONSIVE COMPANIES
    • 11.7.3 DYNAMIC COMPANIES
    • 11.7.4 STARTING BLOCKS
    • FIGURE 46 STARTUPS/SMES: COMPANY EVALUATION QUADRANT, 2022
  • 11.8 STARTUP/SME COMPETITIVE BENCHMARKING
    • TABLE 230 NLP IN FINANCE MARKET: DETAILED LIST OF KEY STARTUPS/SMES
    • TABLE 231 NLP IN FINANCE MARKET: PRODUCT FOOTPRINT ANALYSIS OF STARTUPS/ SMES, 2022
  • 11.9 NLP IN FINANCE PRODUCT LANDSCAPE
    • 11.9.1 PROMINENT NAMED SENTIMENT ANALYSIS PRODUCTS
    • TABLE 232 COMPARATIVE ANALYSIS OF PROMINENT NAMED SENTIMENT ANALYSIS PRODUCTS
      • 11.9.1.1 Lexalytics
      • 11.9.1.2 Aylien
      • 11.9.1.3 Google Cloud
      • 11.9.1.4 IBM Watson
      • 11.9.1.5 Amazon Comprehend
    • 11.9.2 PROMINENT NAMED ENTITY RECOGNITION PRODUCTS
    • TABLE 233 COMPARATIVE ANALYSIS OF PROMINENT NAMED ENTITY RECOGNITION PRODUCTS
      • 11.9.2.1 Rosette
      • 11.9.2.2 Spacy
      • 11.9.2.3 Basis Tech
      • 11.9.2.4 Expert.AI
      • 11.9.2.5 MeaningCloud
    • 11.9.3 PROMINENT TOPIC MODELING PRODUCTS
    • TABLE 234 COMPARATIVE ANALYSIS OF PROMINENT TOPIC MODELING PRODUCTS
      • 11.9.3.1 Gensim
      • 11.9.3.2 Mallet
      • 11.9.3.3 LDAvis
      • 11.9.3.4 bigARTM
      • 11.9.3.5 Stanford NLP
    • 11.9.4 PROMINENT TEXT CLASSIFICATION PRODUCTS
    • TABLE 235 COMPARATIVE ANALYSIS OF PROMINENT TEXT CLASSIFICATION PRODUCTS
      • 11.9.4.1 MonkeyLearn
      • 11.9.4.2 Datumbox
      • 11.9.4.3 OpenAI
      • 11.9.4.4 Hugging Face
      • 11.9.4.5 TensorFlow
    • 11.9.5 PROMINENT DOCUMENT CLASSIFICATION PRODUCTS
    • TABLE 236 COMPARATIVE ANALYSIS OF PROMINENT DOCUMENT CLASSIFICATION PRODUCTS
      • 11.9.5.1 Azure Cognitive Services Text Analytics
      • 11.9.5.2 OpenText Magellan
      • 11.9.5.3 RapidMiner
      • 11.9.5.4 Prodigy By Explosion AI
      • 11.9.5.5 KNIME Analytics Platform
  • 11.10 VALUATION AND FINANCIAL METRICS OF KEY NLP IN FINANCE VENDORS
    • FIGURE 47 VALUATION AND FINANCIAL METRICS OF KEY NLP IN FINANCE VENDORS
  • 11.11 COMPETITIVE SCENARIO AND TRENDS
    • 11.11.1 PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 237 SERVICE/PRODUCT LAUNCHES, 2020-2023
    • 11.11.2 DEALS
    • TABLE 238 DEALS, 2021-2023

12 COMPANY PROFILES

  • 12.1 INTRODUCTION
  • (Business Overview, Software/Services offered, Recent Developments, MnM view, Key strengths, Strategic choices, Weakness and competitive threats)**
  • 12.2 KEY PLAYERS
    • 12.2.1 MICROSOFT
    • TABLE 239 MICROSOFT: BUSINESS OVERVIEW
    • FIGURE 48 MICROSOFT: COMPANY SNAPSHOT
    • TABLE 240 MICROSOFT: SOFTWARE/SERVICES OFFERED
    • TABLE 241 MICROSOFT: PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 242 MICROSOFT: DEALS
    • 12.2.2 IBM
    • TABLE 243 IBM: BUSINESS OVERVIEW
    • FIGURE 49 IBM: COMPANY SNAPSHOT
    • TABLE 244 IBM: SOFTWARE/SERVICES OFFERED
    • TABLE 245 IBM: PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 246 IBM: DEALS
    • 12.2.3 GOOGLE
    • TABLE 247 GOOGLE: BUSINESS OVERVIEW
    • FIGURE 50 GOOGLE: COMPANY SNAPSHOT
    • TABLE 248 GOOGLE: SOFTWARE/SERVICES OFFERED
    • TABLE 249 GOOGLE: PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 250 GOOGLE: DEALS
    • 12.2.4 AWS
    • TABLE 251 AWS: BUSINESS OVERVIEW
    • FIGURE 51 AWS: COMPANY SNAPSHOT
    • TABLE 252 AWS: SOFTWARE/SERVICES OFFERED
    • TABLE 253 AWS: PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 254 AWS: DEALS
    • 12.2.5 ORACLE
    • TABLE 255 ORACLE: BUSINESS OVERVIEW
    • FIGURE 52 ORACLE: COMPANY SNAPSHOT
    • TABLE 256 ORACLE: SOFTWARE/SERVICES OFFERED
    • TABLE 257 ORACLE: PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 258 ORACLE: DEALS
    • 12.2.6 SAS INSTITUTE
    • TABLE 259 SAS INSTITUTE: BUSINESS OVERVIEW
    • TABLE 260 SAS INSTITUTE: SOFTWARE/SERVICES OFFERED
    • TABLE 261 SAS INSTITUTE: PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 262 SAS INSTITUTE: DEALS
    • 12.2.7 QUALTRICS
    • TABLE 263 QUALTRICS: BUSINESS OVERVIEW
    • FIGURE 53 QUALTRICS: COMPANY SNAPSHOT
    • TABLE 264 QUALTRICS: SOFTWARE/SERVICES OFFERED
    • TABLE 265 QUALTRICS: PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 266 QUALTRICS: DEALS
    • 12.2.8 BAIDU
    • TABLE 267 BAIDU: BUSINESS OVERVIEW
    • FIGURE 54 BAIDU: COMPANY SNAPSHOT
    • TABLE 268 BAIDU: SOFTWARE/SERVICES OFFERED
    • TABLE 269 BAIDU: PRODUCT LAUNCHES AND ENHANCEMENTS
    • 12.2.9 INBENTA
    • TABLE 270 INBENTA: BUSINESS OVERVIEW
    • TABLE 271 INBENTA: SOFTWARE/SERVICES OFFERED
    • TABLE 272 INBENTA: PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 273 INBENTA: DEALS
    • 12.2.10 BASIS TECHNOLOGY
    • TABLE 274 BASIS TECHNOLOGY: BUSINESS OVERVIEW
    • TABLE 275 BASIS TECHNOLOGY: SOFTWARE/SERVICES OFFERED
    • TABLE 276 BASIS TECHNOLOGY: PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 277 BASIS TECHNOLOGY: DEALS
    • 12.2.11 NUANCE COMMUNICATIONS
    • TABLE 278 NUANCE COMMUNICATIONS: BUSINESS OVERVIEW
    • FIGURE 55 NUANCE COMMUNICATIONS: COMPANY SNAPSHOT
    • TABLE 279 NUANCE COMMUNICATIONS: SOFTWARE/SERVICES OFFERED
    • TABLE 280 NUANCE COMMUNICATIONS: PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 281 NUANCE COMMUNICATIONS: DEALS
    • 12.2.12 EXPERT.AI
    • TABLE 282 EXPERT.AI: BUSINESS OVERVIEW
    • FIGURE 56 EXPERT.AI: COMPANY SNAPSHOT
    • TABLE 283 EXPERT.AI: SOFTWARE/SERVICES OFFERED
    • TABLE 284 EXPERT.AI: PRODUCT LAUNCHES AND ENHANCEMENTS
    • TABLE 285 EXPERT.AI: DEALS
    • 12.2.13 LIVEPERSON
    • 12.2.14 VERITONE
    • 12.2.15 AUTOMATED INSIGHTS
    • 12.2.16 BITEXT
    • 12.2.17 CONVERSICA
    • 12.2.18 ACCERN
    • 12.2.19 KASISTO
    • 12.2.20 KENSHO
    • 12.2.21 ABBYY
    • 12.2.22 MOSAIC
    • 12.2.23 UNIPHORE
  • *Details on Business Overview, Software/Services offered, Recent Developments, MnM view, Key strengths, Strategic choices, Weakness and competitive threats might not be captured in case of unlisted companies.
  • 12.3 STARTUP/SME PROFILES
    • 12.3.1 OBSERVE.AI
    • 12.3.2 LILT
    • 12.3.3 COGNIGY
    • 12.3.4 ADDEPTO
    • 12.3.5 SKIT.AI
    • 12.3.6 MINDTITAN
    • 12.3.7 SUPERTEXT.AI
    • 12.3.8 NARRATIVA
    • 12.3.9 CRESTA

13 ADJACENT AND RELATED MARKETS

  • 13.1 NLP IN HEALTHCARE & LIFE SCIENCES
    • 13.1.1 MARKET DEFINITION
    • 13.1.2 MARKET OVERVIEW
      • 13.1.2.1 NLP in healthcare & life sciences market, by component
    • TABLE 286 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY COMPONENT, 2017-2021 (USD MILLION)
    • TABLE 287 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY COMPONENT, 2022-2027 (USD MILLION)
    • TABLE 288 SOLUTIONS: NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY REGION, 2017-2021 (USD MILLION)
    • TABLE 289 SOLUTIONS: NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY REGION, 2022-2027 (USD MILLION)
    • TABLE 290 NLP IN HEALTHCARE & LIFE SCIENCES SOLUTIONS MARKET, BY TYPE, 2017-2021 (USD MILLION)
    • TABLE 291 NLP IN HEALTHCARE & LIFE SCIENCES SOLUTIONS MARKET, BY TYPE, 2022-2027 (USD MILLION)
    • TABLE 292 SERVICES: NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY TYPE, 2017-2021 (USD MILLION)
    • TABLE 293 SERVICES: NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY TYPE, 2022-2027 (USD MILLION)
    • TABLE 294 SERVICES: NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY REGION, 2017-2021 (USD MILLION)
    • TABLE 295 SERVICES: NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY REGION, 2022-2027 (USD MILLION)
      • 13.1.2.2 NLP in healthcare & life sciences market, by type
    • TABLE 296 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY TYPE, 2017-2021 (USD MILLION)
    • TABLE 297 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY TYPE, 2022-2027 (USD MILLION)
      • 13.1.2.3 NLP in healthcare & life sciences market, by application
    • TABLE 298 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY APPLICATION, 2017-2021 (USD MILLION)
    • TABLE 299 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY APPLICATION, 2022-2027 (USD MILLION)
      • 13.1.2.4 NLP in healthcare & life sciences market, by size
    • TABLE 300 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY SIZE, 2017-2021 (USD MILLION)
    • TABLE 301 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY SIZE, 2022-2027 (USD MILLION)
      • 13.1.2.5 NLP in healthcare & life sciences market, by deployment mode
    • TABLE 302 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY DEPLOYMENT MODE, 2017-2021 (USD MILLION)
    • TABLE 303 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY DEPLOYMENT MODE, 2022-2027 (USD MILLION)
      • 13.1.2.6 NLP in healthcare & life sciences market, by technique
    • TABLE 304 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY TECHNIQUE, 2017-2021 (USD MILLION)
    • TABLE 305 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY TECHNIQUE, 2022-2027 (USD MILLION)
      • 13.1.2.7 NLP in healthcare & life sciences market, by end user
    • TABLE 306 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY END USER, 2017-2021 (USD MILLION)
    • TABLE 307 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY END USER, 2022-2027 (USD MILLION)
      • 13.1.2.8 NLP in healthcare & life sciences market, by region
    • TABLE 308 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY REGION, 2017-2021 (USD MILLION)
    • TABLE 309 NLP IN HEALTHCARE & LIFE SCIENCES MARKET, BY REGION, 2022-2027 (USD MILLION)
  • 13.2 SPEECH ANALYTICS MARKET
    • 13.2.1 MARKET DEFINITION
    • 13.2.2 MARKET OVERVIEW
      • 13.2.2.1 Speech analytics market, by component
    • TABLE 310 SPEECH ANALYTICS MARKET, BY COMPONENT, 2018-2021(USD MILLION)
    • TABLE 311 SPEECH ANALYTICS MARKET, BY COMPONENT, 2022-2027(USD MILLION)
    • TABLE 312 SOLUTIONS: SPEECH ANALYTICS MARKET, BY REGION, 2018-2021(USD MILLION)
    • TABLE 313 SOLUTIONS: SPEECH ANALYTICS MARKET, BY REGION, 2022-2027(USD MILLION)
    • TABLE 314 SPEECH ANALYTICS MARKET, BY SERVICE, 2018-2021 (USD MILLION)
    • TABLE 315 SPEECH ANALYTICS MARKET, BY SERVICE, 2022-2027 (USD MILLION)
    • TABLE 316 SERVICES: SPEECH ANALYTICS MARKET, BY REGION, 2018-2021 (USD MILLION)
    • TABLE 317 SERVICES: SPEECH ANALYTICS MARKET, BY REGION, 2022-2027 (USD MILLION)
      • 13.2.2.2 Speech analytics market, by business function
    • TABLE 318 SPEECH ANALYTICS MARKET, BY BUSINESS FUNCTION, 2018-2021(USD MILLION)
    • TABLE 319 SPEECH ANALYTICS MARKET, BY BUSINESS FUNCTION, 2022-2027 (USD MILLION)
      • 13.2.2.3 Speech analytics market, by organization size
    • TABLE 320 SPEECH ANALYTICS MARKET, BY ORGANIZATION SIZE, 2018-2021 (USD MILLION)
    • TABLE 321 SPEECH ANALYTICS MARKET, BY ORGANIZATION SIZE, 2022-2027 (USD MILLION)
      • 13.2.2.4 Speech analytics market, by deployment mode
    • TABLE 322 SPEECH ANALYTICS MARKET, BY DEPLOYMENT MODE, 2018-2021(USD MILLION)
    • TABLE 323 SPEECH ANALYTICS MARKET, BY DEPLOYMENT MODE, 2022-2027(USD MILLION)
      • 13.2.2.5 Speech analytics market, by application
    • TABLE 324 SPEECH ANALYTICS MARKET, BY APPLICATION, 2017-2021 (USD MILLION)
    • TABLE 325 SPEECH ANALYTICS MARKET, BY APPLICATION, 2022-2027 (USD MILLION)
      • 13.2.2.6 Speech analytics market, by vertical
    • TABLE 326 SPEECH ANALYTICS MARKET BY VERTICAL, 2017-2021 (USD MILLION)
    • TABLE 327 SPEECH ANALYTICS MARKET, BY VERTICAL, 2022-2027 (USD MILLION)
      • 13.2.2.7 Speech analytics market, by region
    • TABLE 328 SPEECH ANALYTICS MARKET, BY REGION, 2017-2021 (USD MILLION)
    • TABLE 329 SPEECH ANALYTICS MARKET, BY REGION, 2022-2027 (USD MILLION)

14 APPENDIX

  • 14.1 DISCUSSION GUIDE
  • 14.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
  • 14.3 CUSTOMIZATION OPTIONS
  • 14.4 RELATED REPORTS
  • 14.5 AUTHOR DETAILS