サマリー

金融分野におけるNLP市場は、2023年の55億米ドルから2028年には188億米ドルまで、年平均成長率（CAGR）27.6％で成長すると予測されます。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、複雑な金融データを正確かつリアルタイムに分析するニーズの高まりから、市場の拡大が予想されます。
サービス別では、サービス分野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、金融における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る。同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向けに幅広い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、専門知識を持つ専門家に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、保険分野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、クレーム処理、顧客サービス、不正行為の検出など、さまざまなプロセスを改善するためにNLPの利用が進んでいます。保険でNLPが活用されている重要な分野のひとつが、アンダーライティングです。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、リスクを評価して保険料を決定しています。

予測期間中、最大の市場規模を占めるのは北アメリカ
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の進歩が、金融分野で使用されるNLPソリューションの成長をもたらしています。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つなげています。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にとって、ビジネスの構築と推進、消費者層の拡大、より多くの人々へのアプローチに役立つ、費用対効果が高く技術的に高度なツールとしてNLP技術を活用する上で、さらなる力となります。
プライマリーの内訳
金融分野におけるNLP市場で事業を展開する様々な主要組織の最高経営責任者（CEO）、革新・技術責任者、システムインテグレーター、経営幹部に対して、詳細なインタビューを実施したものです。
 企業別：ティアI：38％、ティアII：50％、ティアIII：12％。
 By Designation：C-Level Executives：35％、D-レベルエグゼクティブ：40％、マネージャー：25
 By Region：アジア太平洋地域：20％、ヨーロッパ：26％、北米：42％、その他の地域：12％。
本レポートでは、金融ソリューションにおけるNLPを提供する主要プレイヤーの調査も行っています。NLP in finance市場の主要ベンダーのプロフィールを掲載しています。金融分野におけるNLP市場の主要プレーヤーには、マイクロソフト（米国）、IBM（米国）、グーグル（米国）、AWS（米国）、オラクル（米国）、SAS Institute（米国）、Qualtrics（米国）、Baidu（中国）、Inbenta（米国）、Basis Technology（米国）、Nuance Communications（米国）、Expert．ai（イタリア）、LivePerson（米国）、Veritone（米国）、Automated Insights（米国）、Bitext（米国）、Conversica（米国）、Accern（米国）、Kasisto（米国）、Kensho（米国）、ABBYY（米国）、Mosaic（米国）、Uniphore（米国）、Observe．AI（米国）、Lilt（米国）、Cognigy（ドイツ）、Addepto（ポーランド）、Skit.ai（米国）、MindTitan（エストニア）、Supertext.ai（インド）、Narrativa（米国）、Cresta（米国）です。
研究対象
金融におけるNLP市場の調査には、広範な二次ソース、ディレクトリ、ジャーナル、有料データベースを使用しました。一次情報源は、主に基幹産業および関連産業の業界専門家、好ましいNLP in financeプロバイダー、第三者サービスプロバイダー、コンサルティングサービスプロバイダー、エンドユーザー、およびその他の営利企業である。重要な質的・量的情報を入手・検証し、市場の将来性を評価するために、主要な業界関係者や主題専門家を含む主要回答者との綿密なインタビューを実施した。

本レポートを購入する主なメリット
本レポートは、市場リーダーや新規参入者に、金融分野におけるNLP市場全体とそのサブセグメントにおける収益数字の最も近い近似値に関する情報を提供します。本レポートは、関係者が競争環境を理解し、自社のビジネスを位置づけ、適切な市場参入戦略を計画するためのより良い洞察を得るのに役立つことでしょう。また、利害関係者が市場の脈を理解し、主要な市場促進要因、阻害要因、課題、および機会に関する情報を提供するのに役立ちます。
本レポートは、以下のポイントに関する洞察を提供します：
- 主要な推進要因の分析（世界中で自動化された効率的な金融サービスへの需要の高まり、複雑な金融データの正確かつリアルタイムな分析へのニーズの高まり、金融におけるNLP機能の強化を可能にするAIおよびMLモデルの出現）、阻害要因（NLPベースの金融アプリケーションおよびサービスにおける標準化の欠如、大量の非構造化データの管理の困難さ、高度なNLPモデルの開発およびトレーニングにおける複雑さ）、機会（特定の金融サービスやユースケース向けにカスタマイズされたNLPソリューションの開発、金融業務の精度と効率を高めるためのブロックチェーンやビッグデータとのNLPの統合、NLPを搭載したチャットボットやバーチャルアシスタントの採用拡大）、課題（NLPに関する高い導入コスト、金融におけるNLP使用に関連する熟練専門家の限られた利用可能性およびデータプライバシーに関する懸念）です。
- 製品開発/イノベーション：金融分野におけるNLP市場の今後の技術、研究開発活動、製品・サービス発表に関する詳細なインサイト。
- 市場開発：有利な市場に関する包括的な情報 - 本レポートでは、地域ごとの金融分野におけるNLP市場を分析しています。
- 市場の多様化：新製品・サービス、未開拓の地域、最近の開発、NLPファイナンス市場への投資に関する詳細な情報を提供します。
- 競争力のある評価：マイクロソフト（米国）、IBM（米国）、グーグル（米国）、AWS（米国）、オラクル（米国）、SAS Institute（米国）、Qualtrics（米国）、百度（中国）、Inbenta（米国）、Basis Technology（米国）、Nuance Communications（米国）、Expert.ai（イタリア）などの主要企業の市場シェア、成長戦略、サービス提供について詳細に評価して、NLPの市場戦略における他のプレーヤーと同様に説明する。また、本レポートは、関係者がNLP in finance市場の鼓動を理解するのに役立ち、主要な市場促進要因、阻害要因、課題、および機会に関する情報を提供する。

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目次

1 INTRODUCTION 46
1.1 STUDY OBJECTIVES 46
1.2 MARKET DEFINITION 46
1.2.1 INCLUSIONS AND EXCLUSIONS 47
1.3 MARKET SCOPE 48
1.3.1 MARKET SEGMENTATION 48
1.3.2 REGIONS COVERED 49
1.3.3 YEARS CONSIDERED 49
1.4 CURRENCY CONSIDERED 50
TABLE 1 US DOLLAR EXCHANGE RATE, 2019–2022 50
1.5 STAKEHOLDERS 50
2 RESEARCH METHODOLOGY 51
2.1 RESEARCH DATA 51
FIGURE 1 NLP IN FINANCE MARKET: RESEARCH DESIGN 51
2.1.1 SECONDARY DATA 52
2.1.2 PRIMARY DATA 52
2.1.2.1 Primary interviews 52
2.1.2.2 Breakup of primary profiles 53
2.1.2.3 Key industry insights 53
2.2 DATA TRIANGULATION 54
FIGURE 2 DATA TRIANGULATION 54
2.3 MARKET SIZE ESTIMATION 55
FIGURE 3 NLP IN FINANCE MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES 55
2.3.1 TOP-DOWN APPROACH 55
2.3.2 BOTTOM-UP APPROACH 56
FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 1 (SUPPLY-SIDE): REVENUE FROM SOLUTIONS/SERVICES OF NLP IN FINANCE MARKET 56
FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 2, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL SOLUTIONS/SERVICES OF NLP IN FINANCE MARKET 57
FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 3, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL SOLUTIONS/SERVICES OF NLP IN FINANCE MARKET 58
FIGURE 7 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 4, BOTTOM-UP (DEMAND-SIDE): SHARE OF NLP IN FINANCE THROUGH OVERALL SPENDING 58
2.4 MARKET FORECAST 59
TABLE 2 FACTOR ANALYSIS 59
2.5 RESEARCH ASSUMPTIONS 60
 
2.6 STUDY LIMITATIONS 62
2.7 IMPLICATIONS OF RECESSION IMPACT ON NLP IN FINANCE 62
3 EXECUTIVE SUMMARY 64
TABLE 3 NLP IN FINANCE MARKET SIZE AND GROWTH RATE, 2019–2022 (USD MILLION, Y-O-Y %) 66
TABLE 4 GLOBAL NLP IN FINANCE MARKET SIZE AND GROWTH RATE, 2023–2028 (USD MILLION, Y-O-Y %) 66
FIGURE 8 SOFTWARE SEGMENT TO HOLD LARGEST MARKET SIZE IN 2023 66
FIGURE 9 STATISTICAL NLP SOFTWARE TO ACCOUNT FOR MAJOR MARKET SHARE IN 2023 66
FIGURE 10 PROFESSIONAL SERVICES TO DOMINATE MARKET IN 2023 67
FIGURE 11 SYSTEM INTEGRATION AND IMPLEMENTATION SERVICES TO DOMINATE MARKET IN 2023 67
FIGURE 12 RISK MANAGEMENT AND FRAUD DETECTION TO BE LEADING APPLICATION IN 2023 68
FIGURE 13 MACHINE LEARNING TO BE MOST DEPLOYED TECHNOLOGY IN 2023 68
FIGURE 14 INSURANCE VERTICAL SET TO WITNESS FASTEST GROWTH RATE 69
FIGURE 15 NORTH AMERICA TO HOLD LARGEST MARKET SHARE 69
4 PREMIUM INSIGHTS 70
4.1 ATTRACTIVE OPPORTUNITIES IN NLP IN FINANCE MARKET 70
FIGURE 16 INCREASING POPULARITY OF CHATBOTS ACROSS FINANCE AND IMPROVING PERFORMANCE OF NLP MODELS TO DRIVE MARKET GROWTH 70
4.2 NLP IN FINANCE MARKET: TOP THREE APPLICATIONS 71
FIGURE 17 CUSTOMER SERVICE AND SUPPORT APPLICATION SEGMENT TO ACCOUNT FOR HIGHEST GROWTH RATE 71
4.3 NORTH AMERICA: NLP IN FINANCE MARKET, BY OFFERING AND VERTICAL 71
FIGURE 18 SOFTWARE AND BANKING TO BE LARGEST SHAREHOLDERS IN NORTH AMERICA IN 2023 71
4.4 NLP IN FINANCE MARKET, BY REGION 72
FIGURE 19 NORTH AMERICA TO HOLD LARGEST MARKET SHARE IN 2023 72
5 MARKET OVERVIEW AND INDUSTRY TRENDS 73
5.1 INTRODUCTION 73
5.2 MARKET DYNAMICS 73
FIGURE 20 NLP IN FINANCE MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES 74
5.2.1 DRIVERS 74
5.2.1.1 Increasing demand for automated and efficient financial services worldwide 74
5.2.1.2 Rising need for accurate and real-time analysis of complex financial data 75
5.2.1.3 Emergence of AI and ML models 75
 
5.2.2 RESTRAINTS 76
5.2.2.1 Lack of standardization in NLP-based financial applications and services 76
5.2.2.2 Difficulty in managing large volumes of unstructured data 76
5.2.2.3 Complexity in developing and training sophisticated NLP models 77
5.2.3 OPPORTUNITIES 77
5.2.3.1 Development of customized NLP solutions for specific financial services and use cases 77
5.2.3.2 Integration of NLP with blockchain and big data to enhance accuracy and efficiency of financial operations 78
5.2.3.3 Growing adoption of NLP-powered chatbots and virtual assistants 78
5.2.4 CHALLENGES 79
5.2.4.1 High implementation costs associated with NLP 79
5.2.4.2 Limited availability of skilled professionals 79
5.2.4.3 Data privacy concerns associated with use of NLP 80
5.3 ETHICS AND IMPLICATIONS OF NLP IN FINANCE 80
5.3.1 BIAS AND FAIRNESS 80
5.3.2 PRIVACY AND SECURITY 81
5.3.3 INTELLECTUAL PROPERTY 81
5.3.4 ACCOUNTABILITY AND RESPONSIBILITY 81
5.3.5 SOCIETAL AND ECONOMIC IMPACT 81
5.4 BRIEF HISTORY OF NLP IN FINANCE 82
FIGURE 21 BRIEF HISTORY OF NLP IN FINANCE 82
5.5 ECOSYSTEM ANALYSIS 83
FIGURE 22 KEY PLAYERS IN NLP IN FINANCE MARKET ECOSYSTEM 83
5.5.1 NLP IN FINANCE TECHNOLOGY PROVIDERS 84
5.5.2 NLP IN FINANCE CLOUD PLATFORM PROVIDERS 84
5.5.3 NLP IN FINANCE API AND AS-A-SERVICE PROVIDERS 85
5.5.4 NLP IN FINANCE HARDWARE PROVIDERS 86
5.5.5 NLP IN FINANCE END USERS 86
5.5.6 NLP IN FINANCE REGULATORS 87
5.6 NLP IN FINANCE TOOLS AND FRAMEWORK 88
5.6.1 TENSORFLOW 88
5.6.2 PYTORCH 88
5.6.3 KERAS 88
5.6.4 NLTK 88
5.6.5 APACHE OPENNLP 88
5.6.6 SPACY 89
5.6.7 GENSIM 89
5.6.8 ALLENNLP 89
5.6.9 FLAIR 89
5.6.10 STANFORD CORENLP 89
 
5.7 CASE STUDY ANALYSIS 90
5.7.1 CASE STUDY 1: NATWEST IMPROVED SPEED AND ACCURACY OF COMPLAINT-HANDLING PROCESS THROUGH IBM 90
5.7.2 CASE STUDY 2: AYASDI’S NLP PLATFORM HELPED J.P. MORGAN CHASE RAMP UP RISK ASSESSMENT TECHNIQUES 90
5.7.3 CASE STUDY 3: CAPITAL ONE ELIMINATED INEFFICIENCIES IN CUSTOMER QUERY RESOLUTION THROUGH NLP 91
5.7.4 CASE STUDY 4: BLACKROCK IDENTIFIED NEW INVESTMENT AVENUES BY ANALYZING LARGE VOLUMES OF UNSTRUCTURED DATA 91
5.7.5 CASE STUDY 5: YSEOP ASSISTED TD AMERITRADE IN DISCOVERING NEW CUSTOMER INSIGHTS 92
5.7.6 CASE STUDY 6: ALLIANZ WITNESSED SUBSTANTIAL IMPROVEMENT IN INSURANCE CLAIMS PROCESSING THROUGH NLP 92
5.7.7 CASE STUDY 7: UBS TRAINED DATASETS THROUGH NLP TO AUGMENT RISK MANAGEMENT PROCESSES 93
5.7.8 CASE STUDY 8: CITI ADDED PERSONALIZED TOUCH TO CUSTOMER RECOMMENDATIONS VIA NLP-BASED QUERY ANALYSIS 93
5.7.9 CASE STUDY 9: BARCLAYS SCALED ITS TRADING AND INVESTMENT ANALYSIS PROCESSES VIA AYASDI’S NLP TOOL 94
5.7.10 CASE STUDY 10: GOLDMAN SACHS AUGMENTED ITS FINANCIAL R&D PROWESS 94
5.7.11 CASE STUDY 11: NLP EMPOWERED KABBAGE WITH SMARTER DECISION-MAKING FOR LOAN DISBURSAL 95
5.7.12 CASE STUDY 12: CHAINALYSIS DEPLOYED NLP FOR FRAUD PREVENTION IN CRYPTO TRADING 95
5.8 SUPPLY CHAIN ANALYSIS 96
FIGURE 23 NLP IN FINANCE MARKET: SUPPLY CHAIN ANALYSIS 96
TABLE 5 NLP IN FINANCE MARKET: SUPPLY CHAIN ANALYSIS 96
5.9 REGULATORY LANDSCAPE 98
5.9.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 98
TABLE 6 NORTH AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 98
TABLE 7 EUROPE: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 99
TABLE 8 ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 99
TABLE 9 MIDDLE EAST & AFRICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 100
TABLE 10 LATIN AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 100
5.9.2 NORTH AMERICA 100
5.9.2.1 Fair Credit Reporting Act (FCRA) 100
5.9.2.2 Consumer Financial Protection Act (CFPA) 101
5.9.2.3 Gramm-Leach-Bliley Act (GLBA) 101
5.9.2.4 Sarbanes-Oxley Act (SOX) 101
5.9.2.5 Dodd-Frank Wall Street Reform and Consumer Protection Act 101
5.9.3 EUROPE 101
5.9.3.1 Markets in Financial Instruments Directive II (MiFID II) 101
5.9.3.2 General Data Protection Regulation (GDPR) 102
5.9.3.3 Payment Services Directive 2 (PSD2) 102
5.9.3.4 Markets in Financial Instruments Regulation (MiFIR) 102
5.9.3.5 Anti-Money Laundering (AML) Directive 102
5.9.4 ASIA PACIFIC 102
5.9.4.1 Personal Information Protection Act (PIPA) – Japan 102
5.9.4.2 Personal Data Protection Act (PDPA) – Singapore 103
5.9.4.3 Information Technology Act (ITA) – India 103
5.9.4.4 Personal Information Protection Law (PIPL) – China 103
5.9.4.5 Privacy Act – Australia 103
5.9.5 LATIN AMERICA 103
5.9.5.1 General Data Protection Law (LGPD) – Brazil 103
5.9.5.2 Data Protection Law (Ley de Proteccion de Datos Personales) – Mexico 103
5.9.5.3 Financial Institutions Law (Ley de Instituciones de Credito) – Mexico 103
5.9.5.4 Anti-Money Laundering (AML) Law – Colombia 104
5.9.5.5 Financial Sector Law (Ley del Sector Financiero) – Colombia 104
5.9.6 MIDDLE EAST AND AFRICA 104
5.9.6.1 Dubai Financial Services Authority (DFSA) Regulations 104
5.9.6.2 Financial Sector Regulation (FSR) – South Africa 104
5.9.6.3 Anti-Money Laundering and Countering Financing of Terrorism (AML/CFT) Regulations – Saudi Arabia 104
5.9.6.4 Data Protection and Privacy Regulations – Egypt 104
5.9.6.5 Financial Services Authority (FSA) Regulations – Morocco 104
5.10 PATENT ANALYSIS 105
5.10.1 METHODOLOGY 105
5.10.2 PATENTS FILED, BY DOCUMENT TYPE, 2019–2022 105
TABLE 11 PATENTS FILED, 2019–2022 105
5.10.3 INNOVATION AND PATENT APPLICATIONS 105
FIGURE 24 TOTAL NUMBER OF PATENTS GRANTED, 2013–2022 105
5.10.4 TOP APPLICANTS 106
FIGURE 25 TOP 10 COMPANIES WITH HIGHEST NUMBER OF PATENT APPLICATIONS IN LAST 10 YEARS, 2013–2022 106
TABLE 12 TOP 20 PATENT OWNERS IN NLP IN FINANCE MARKET, 2013–2022 106
TABLE 13 LIST OF PATENTS IN NLP IN FINANCE MARKET, 2021–2023 107
FIGURE 26 REGIONAL ANALYSIS OF PATENTS GRANTED FOR NLP IN FINANCE MARKET, 2013-2022 112
5.11 KEY CONFERENCES AND EVENTS, 2023–2024 113
TABLE 14 NLP IN FINANCE MARKET: DETAILED LIST OF CONFERENCES AND EVENTS 113
5.12 PRICING ANALYSIS 114
FIGURE 27 INDICATIVE SELLING PRICES OF KEY PLAYERS FOR TOP 3 APPLICATIONS 115
TABLE 15 AVERAGE SELLING PRICING ANALYSIS OF KEY PLAYERS FOR TOP 3 APPLICATIONS (USD) 115
5.13 PORTER’S FIVE FORCES ANALYSIS 116
TABLE 16 IMPACT OF EACH FORCE ON NLP IN FINANCE MARKET 116
FIGURE 28 NLP IN FINANCE MARKET: PORTER’S FIVE FORCES ANALYSIS 117
5.13.1 THREAT OF NEW ENTRANTS 117
5.13.2 THREAT OF SUBSTITUTES 118
5.13.3 BARGAINING POWER OF SUPPLIERS 118
5.13.4 BARGAINING POWER OF BUYERS 118
5.13.5 INTENSITY OF COMPETITIVE RIVALRY 118
5.14 KEY STAKEHOLDERS AND BUYING CRITERIA 119
5.14.1 KEY STAKEHOLDERS IN BUYING PROCESS 119
FIGURE 29 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE APPLICATIONS 119
TABLE 17 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE APPLICATIONS 119
5.14.2 BUYING CRITERIA 119
FIGURE 30 KEY BUYING CRITERIA FOR TOP THREE APPLICATIONS 119
TABLE 18 KEY BUYING CRITERIA FOR TOP THREE APPLICATIONS 120
5.15 TRENDS/DISRUPTIONS IMPACTING BUYERS/CLIENTS OF NLP IN FINANCE MARKET 120
FIGURE 31 NLP IN FINANCE MARKET: TRENDS/DISRUPTIONS IMPACTING BUYERS/CLIENTS 120
5.16 BEST PRACTICES IN NLP IN FINANCE MARKET 120
5.16.1 DOMAIN-SPECIFIC DATA SELECTION AND DATA CLEANING 120
5.16.2 FEATURE ENGINEERING 121
5.16.3 MODEL SELECTION 121
5.16.4 EVALUATION METRICS 121
5.16.5 CROSS-VALIDATION 122
5.16.6 REGULARIZATION 122
5.16.7 HYPERPARAMETER TUNING 122
5.16.8 TRANSFER LEARNING 122
5.16.9 INTERPRETABILITY 122
5.16.10 REGULATORY COMPLIANCE 122
5.16.11 BACKTESTING AND DEPLOYMENT 123
5.17 TECHNOLOGY ROADMAP OF NLP IN FINANCE 123
5.17.1 NLP IN FINANCE ROADMAP TILL 2030 123
TABLE 19 NLP IN FINANCE ROADMAP TILL 2030 123
5.17.1.1 Pre-2020 124
5.17.1.2 2020-2022 124
5.17.1.3 Short-term (2023-2025) 124
5.17.1.4 Mid-term (2026-2028) 124
5.17.1.5 Long-term (2029-2030) 125
 
5.18 CURRENT AND EMERGING BUSINESS MODELS 125
5.18.1 SAAS MODEL 125
5.18.2 CONSULTING SERVICES MODEL 125
5.18.3 PARTNER PROGRAMS (REVENUE SHARING MODEL) 125
5.18.4 PAY-PER-USE MODEL 126
5.19 NLP IN FINANCE’S IMPACT ON ADJACENT NICHE TECHNOLOGIES 126
5.19.1 HIGH-FREQUENCY TRADING AND ELECTRONIC TRADING PLATFORMS 126
5.19.2 FINANCIAL CYBERSECURITY 126
5.19.3 REGULATORY TECHNOLOGY (REGTECH) 127
6 NLP IN FINANCE MARKET, BY OFFERING 128
6.1 INTRODUCTION 129
6.1.1 OFFERING: NLP IN FINANCE MARKET DRIVERS 129
FIGURE 32 SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD 130
TABLE 20 NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 130
TABLE 21 NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 130
6.2 SOFTWARE 131
TABLE 22 SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 131
TABLE 23 SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 131
6.2.1 NLP IN FINANCE SOFTWARE, BY SOFTWARE TYPE 132
FIGURE 33 STATISTICAL NLP SOFTWARE TO HOLD LARGEST MARKET SHARE IN 2023 132
TABLE 24 SOFTWARE: NLP IN FINANCE MARKET, BY SOFTWARE TYPE, 2019–2022 (USD MILLION) 132
TABLE 25 SOFTWARE: NLP IN FINANCE MARKET, BY SOFTWARE TYPE, 2023–2028 (USD MILLION) 132
6.2.1.1 Rule-based NLP Software 133
6.2.1.1.1 Rule-based NLP software to help financial institutions automate compliance and risk management processes 133
TABLE 26 RULE-BASED NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 133
TABLE 27 RULE-BASED NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 133
6.2.1.1.1.1 Regular Expression (Regex) 134
6.2.1.1.1.2 Finite State Machines (FSMs) 134
6.2.1.1.1.3 Named Entity Recognition (NER) 134
6.2.1.1.1.4 Part-of-Speech (POS) Tagging 135
6.2.1.2 Statistical NLP Software 135
6.2.1.2.1 Statistical NLP software to analyze large volumes of unstructured data 135
TABLE 28 STATISTICAL NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 136
TABLE 29 STATISTICAL NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 136
6.2.1.2.1.1 Naive Bayes 136
6.2.1.2.1.2 Logistic Regression 137
6.2.1.2.1.3 Support Vector Machines (SVMs) 137
6.2.1.2.1.4 Recurrent Neural Networks (RNNs) 137
6.2.1.3 Hybrid NLP Software 138
6.2.1.3.1 Hybrid NLP to combine strengths of rule-based and statistical approaches 138
TABLE 30 HYBRID NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 138
TABLE 31 HYBRID NLP SOFTWARE: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 139
6.2.1.3.1.1 Latent Dirichlet Allocation (LDA) 139
6.2.1.3.1.2 Hidden Markov Models (HMMs) 139
6.2.1.3.1.3 Conditional Random Fields (CRFs) 140
6.3 SERVICES 140
FIGURE 34 MANAGED SERVICES SEGMENT TO REGISTER HIGHER CAGR IN NLP IN FINANCE MARKET FOR SERVICES DURING FORECAST PERIOD 140
TABLE 32 NLP IN FINANCE MARKET, BY SERVICE, 2019–2022 (USD MILLION) 141
TABLE 33 NLP IN FINANCE MARKET, BY SERVICE, 2023–2028 (USD MILLION) 141
TABLE 34 SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 141
TABLE 35 SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 141
6.3.1 PROFESSIONAL SERVICES 142
6.3.1.1 Professional services to offer specialized expertise in NLP in finance 142
FIGURE 35 TRAINING AND CONSULTING SERVICES SUB-SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD 142
TABLE 36 SERVICES: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2019–2022 (USD MILLION) 142
TABLE 37 SERVICES: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2023–2028 (USD MILLION) 143
TABLE 38 PROFESSIONAL SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 143
TABLE 39 PROFESSIONAL SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 143
6.3.1.1.1 Training and consulting services 143
TABLE 40 TRAINING AND CONSULTING SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 144
TABLE 41 TRAINING AND CONSULTING SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 144
6.3.1.1.2 System integration and implementation services 144
TABLE 42 SYSTEM INTEGRATION AND IMPLEMENTATION SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 145
TABLE 43 SYSTEM INTEGRATION AND IMPLEMENTATION SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 145
6.3.1.1.3 Support and maintenance services 145
TABLE 44 SUPPORT AND MAINTENANCE SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 146
TABLE 45 SUPPORT AND MAINTENANCE SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 146
6.3.2 MANAGED SERVICES 146
6.3.2.1 Managed services to provide end-to-end management to help businesses focus on core competencies 146
TABLE 46 MANAGED SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 147
TABLE 47 MANAGED SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 147
7 NLP IN FINANCE MARKET, BY APPLICATION 148
7.1 INTRODUCTION 149
7.1.1 APPLICATION: NLP IN FINANCE MARKET DRIVERS 149
FIGURE 36 NATURAL LANGUAGE GENERATION SEGMENT TO ACCOUNT FOR LARGEST MARKET SHARE IN 2023 150
TABLE 48 NLP IN FINANCE MARKET, BY APPLICATION, 2019–2022 (USD MILLION) 151
TABLE 49 NLP IN FINANCE MARKET, BY APPLICATION, 2023–2028 (USD MILLION) 151
7.2 SENTIMENT ANALYSIS 152
7.2.1 SENTIMENT ANALYSIS TO IDENTIFY AND MITIGATE POTENTIAL FINANCIAL RISKS 152
TABLE 50 SENTIMENT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 152
TABLE 51 SENTIMENT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 153
7.2.1.1 Brand reputation management 153
7.2.1.2 Market sentiment analysis 153
7.2.1.3 Customer feedback analysis 153
7.2.1.4 Product review analysis 154
7.2.1.5 Social media monitoring 154
7.3 RISK MANAGEMENT AND FRAUD DETECTION 154
7.3.1 NLP TO IMPROVE SPEED AND ACCURACY OF RISK IDENTIFICATION AND FRAUD DETECTION 154
TABLE 52 RISK MANAGEMENT AND FRAUD DETECTION: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 155
TABLE 53 RISK MANAGEMENT AND FRAUD DETECTION: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 155
7.3.1.1 Credit risk assessment 155
7.3.1.2 Fraud Detection and Prevention 155
7.3.1.3 Anti-money laundering (AML) 156
7.3.1.4 Compliance monitoring 156
7.3.1.5 Cybersecurity threat detection 156
7.4 COMPLIANCE MONITORING 157
7.4.1 NLP TO ANALYZE FINANCIAL TRANSACTIONS AND IDENTIFY POTENTIAL NON-COMPLIANCE ISSUES 157
TABLE 54 COMPLIANCE MONITORING: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 157
TABLE 55 COMPLIANCE MONITORING: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 157
7.4.1.1 Regulatory compliance monitoring 158
7.4.1.2 KYC/AML compliance monitoring 158
7.4.1.3 Legal and policy compliance monitoring 158
7.4.1.4 Audit trail monitoring 159
7.4.1.5 Trade surveillance 159
7.5 INVESTMENT ANALYSIS 159
7.5.1 FINANCIAL INSTITUTIONS INVESTING IN NLP TECHNOLOGY TO HAVE COMPETITIVE EDGE 159
TABLE 56 INVESTMENT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 160
TABLE 57 INVESTMENT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 160
7.5.1.1 Asset allocation and portfolio optimization 160
7.5.1.2 Equity research and analysis 161
7.5.1.3 Quantitative analysis and modeling 161
7.5.1.4 Investment recommendations and planning 161
7.5.1.5 Risk management and prediction 162
7.5.1.6 Investment opportunity identification 162
7.6 FINANCIAL NEWS AND MARKET ANALYSIS 162
7.6.1 NLP ALGORITHMS TO PREDICT HOW MARKETS REACT AND HELP INVESTORS MAKE INFORMED INVESTMENT DECISIONS 162
TABLE 58 FINANCIAL NEWS AND MARKET ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 163
TABLE 59 FINANCIAL NEWS AND MARKET ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 163
7.6.1.1 Financial news analysis 163
7.6.1.2 Stock market prediction 164
7.6.1.3 Macroeconomic analysis 164
7.7 CUSTOMER SERVICE AND SUPPORT 164
7.7.1 ADOPTION OF INTELLIGENT CHATBOTS AND CUSTOMER SUPPORT SYSTEMS TO DRIVE GROWTH 164
TABLE 60 CUSTOMER SERVICE AND SUPPORT: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 165
TABLE 61 CUSTOMER SERVICE AND SUPPORT: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 165
7.7.1.1 Chatbots and virtual assistants 165
7.7.1.2 Personalized support and service 166
7.7.1.3 Compliant resolution 166
7.7.1.4 Query resolution and escalation management 166
7.7.1.5 Self-service options 167
7.7.1.6 Multilingual customer service and support 167
7.8 DOCUMENT AND CONTRACT ANALYSIS 168
7.8.1 DOCUMENT AND CONTRACT ANALYSIS TO STREAMLINE DATA PROCESSING WORKFLOWS 168
TABLE 62 DOCUMENT AND CONTRACT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 168
TABLE 63 DOCUMENT AND CONTRACT ANALYSIS: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 168
7.8.1.1 Contract management 169
7.8.1.2 Legal document analysis 169
7.8.1.3 Due diligence analysis 169
7.8.1.4 Data extraction and normalization 169
7.9 SPEECH RECOGNITION AND TRANSCRIPTION 170
7.9.1 POWERFUL TOOL TO CAPTURE AND ANALYZE VOICE DATA AND ENSURE COMPLIANCE 170
TABLE 64 SPEECH RECOGNITION AND TRANSCRIPTION: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 170
TABLE 65 SPEECH RECOGNITION AND TRANSCRIPTION: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 171
7.9.1.1 Voice-enabled search and navigation 171
7.9.1.2 Speech-to-text conversion 171
7.9.1.3 Call transcription and analysis 172
7.9.1.4 Voice biometrics and authentication 172
7.9.1.5 Speech-enabled virtual assistants 173
7.10 LANGUAGE TRANSLATION 173
7.10.1 AUTOMATING REPORT WRITING AND PERSONALIZED FINANCIAL ADVICE TO DRIVE UPTAKE OF LANGUAGE TRANSLATION TOOLS 173
TABLE 66 LANGUAGE TRANSLATION: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 174
TABLE 67 LANGUAGE TRANSLATION: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 174
7.10.1.1 Financial document translation 174
7.10.1.2 Investment research translation 175
7.10.1.3 Cross-border business communication 175
7.10.1.4 Localization and internationalization 175
7.11 OTHER APPLICATIONS 176
TABLE 68 OTHER APPLICATIONS: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 176
TABLE 69 OTHER APPLICATIONS: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 177
8 NLP IN FINANCE MARKET, BY TECHNOLOGY 178
8.1 INTRODUCTION 179
8.1.1 TECHNOLOGY: NLP IN FINANCE MARKET DRIVERS 179
FIGURE 37 DEEP LEARNING SEGMENT TO GROW AT HIGHER CAGR 180
TABLE 70 NLP IN FINANCE MARKET, BY TECHNOLOGY, 2019–2022 (USD MILLION) 180
TABLE 71 NLP IN FINANCE MARKET, BY TECHNOLOGY, 2023–2028 (USD MILLION) 181
8.2 MACHINE LEARNING 181
8.2.1 MACHINE LEARNING TO BE EXTENSIVELY DEPLOYED TO PREDICT FINANCIAL MARKET INSIGHTS 181
TABLE 72 MACHINE LEARNING: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 182
TABLE 73 MACHINE LEARNING: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 182
8.2.1.1 Supervised learning 182
8.2.1.2 Unsupervised learning 182
8.2.1.3 Reinforcement learning 183
8.3 DEEP LEARNING 183
8.3.1 DEEP LEARNING TO PLAY CRITICAL ROLE IN ADVANCING NLP DEVELOPMENTS 183
TABLE 74 DEEP LEARNING: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 184
TABLE 75 DEEP LEARNING: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 184
8.3.1.1 Convolutional neural networks (CNN) 184
8.3.1.2 Recurrent neural networks (RNN) 184
8.3.1.3 Transformer models (BERT, GPT-3, etc.) 185
8.4 NATURAL LANGUAGE GENERATION 185
8.4.1 FINANCIAL INSTITUTIONS TO INCREASINGLY ADOPT NLG TO IMPROVE EFFICIENCY AND REDUCE COSTS 185
TABLE 76 NATURAL LANGUAGE GENERATION: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 186
TABLE 77 NATURAL LANGUAGE GENERATION: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 186
8.4.1.1 Automated report writing 186
8.4.1.2 Customer communication 187
8.4.1.3 Financial document generation 187
8.5 TEXT CLASSIFICATION 187
8.5.1 TEXT CLASSIFICATION TO ANALYZE MARKET SENTIMENTS IN FINANCE 187
TABLE 78 TEXT CLASSIFICATION: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 188
TABLE 79 TEXT CLASSIFICATION: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 188
8.5.1.1 Sentiment classification 188
8.5.1.2 Intent classification 189
8.6 TOPIC MODELING 189
8.6.1 TOPIC MODELING TO EXTRACT INSIGHTS FROM FINANCIAL NEWS ARTICLES 189
TABLE 80 TOPIC MODELING: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 189
TABLE 81 TOPIC MODELING: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 190
8.6.1.1 Topic identification 190
8.6.1.2 Topic clustering 190
8.6.1.3 Topic visualization 190
8.7 EMOTION DETECTION 191
8.7.1 EMOTION DETECTION TO IMPROVE SENTIMENT ANALYSIS IN FINANCIAL DISCOURSE 191
TABLE 82 EMOTION DETECTION: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 191
TABLE 83 EMOTION DETECTION: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 192
8.7.1.1 Emotion recognition 192
8.7.1.2 Emotion classification 192
8.8 OTHER TECHNOLOGIES 193
8.8.1 NER AND EVENT EXTRACTION TO FACE SPIKE IN HANDLING UNSTRUCTURED FINANCIAL DATA 193
TABLE 84 OTHER TECHNOLOGIES: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 193
TABLE 85 OTHER TECHNOLOGIES: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 193
9 NLP IN FINANCE MARKET, BY VERTICAL 194
9.1 INTRODUCTION 195
9.1.1 VERTICAL: NLP IN FINANCE MARKET DRIVERS 195
FIGURE 38 INSURANCE SEGMENT TO GROW AT HIGHEST CAGR 195
TABLE 86 NLP IN FINANCE MARKET, BY VERTICAL, 2019–2022 (USD MILLION) 196
TABLE 87 NLP IN FINANCE MARKET, BY VERTICAL, 2023–2028 (USD MILLION) 196
9.2 BANKING 196
9.2.1 NLP TO IMPROVE EFFICIENCY, ACCURACY, AND CUSTOMER EXPERIENCE 196
9.2.2 NLP IN FINANCE: BANKING USE CASES 197
TABLE 88 BANKING: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 197
TABLE 89 BANKING: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 197
9.2.2.1 Retail banking 197
9.2.2.2 Corporate banking 198
9.2.2.3 Investment banking 199
9.2.2.4 Wealth management 200
9.3 INSURANCE 200
9.3.1 INSURANCE COMPANIES TO ANALYZE LARGE AMOUNTS OF DATA USING NLP 200
9.3.2 NLP IN FINANCE: INSURANCE USE CASES 201
TABLE 90 INSURANCE: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 201
TABLE 91 INSURANCE: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 201
9.3.2.1 Life insurance 201
9.3.2.2 Property and casualty insurance 202
9.3.2.3 Health insurance 202
9.4 FINANCIAL SERVICES 203
9.4.1 USE OF NLP TO GROW IN FINTECH 203
9.4.2 NLP IN FINANCE: FINANCIAL SERVICES USE CASES 203
TABLE 92 FINANCIAL SERVICES: NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 203
TABLE 93 FINANCIAL SERVICES: NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 204
9.4.2.1 Credit rating 204
9.4.2.2 Payment processing and remitting 204
9.4.2.3 Accounting and auditing 205
9.4.2.4 Personal finance management 205
9.4.2.5 Robo-advisory 206
9.4.2.6 Cryptocurrencies and blockchain 206
9.4.2.7 Stock movement prediction 206
9.4.2.8 Others 207
9.5 OTHER ENTERPRISE VERTICALS 207
9.5.1 NLP IN FINANCE TO MAKE INROADS ACROSS FINANCIAL OPERATIONS 207
9.5.1.1 Healthcare and life sciences 208
9.5.1.2 Manufacturing 208
9.5.1.3 Retail and eCommerce 208
9.5.1.4 Energy & utilities 209
9.5.1.5 Transportation and logistics 209
9.5.1.6 Others 209
10 NLP IN FINANCE MARKET, BY REGION 210
10.1 INTRODUCTION 211
FIGURE 39 ASIA PACIFIC NLP IN FINANCE MARKET TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD 211
FIGURE 40 INDIA TO REGISTER HIGHEST CAGR IN NLP IN FINANCE 212
TABLE 94 NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION) 212
TABLE 95 NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION) 212
10.2 NORTH AMERICA 213
10.2.1 NORTH AMERICA: NLP IN FINANCE MARKET DRIVERS 213
10.2.2 NORTH AMERICA: RECESSION IMPACT 214
FIGURE 41 NORTH AMERICA: SNAPSHOT OF NLP IN FINANCE MARKET 214
TABLE 96 NORTH AMERICA: NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 215
TABLE 97 NORTH AMERICA: NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 215
TABLE 98 NORTH AMERICA: NLP IN FINANCE MARKET, BY SOFTWARE, 2019–2022 (USD MILLION) 215
TABLE 99 NORTH AMERICA: NLP IN FINANCE MARKET, BY SOFTWARE, 2023–2028 (USD MILLION) 215
TABLE 100 NORTH AMERICA: NLP IN FINANCE MARKET, BY SERVICE, 2019–2022 (USD MILLION) 216
TABLE 101 NORTH AMERICA: NLP IN FINANCE MARKET, BY SERVICE, 2023–2028 (USD MILLION) 216
TABLE 102 NORTH AMERICA: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2019–2022 (USD MILLION) 216
TABLE 103 NORTH AMERICA: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2023–2028 (USD MILLION) 216
TABLE 104 NORTH AMERICA: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2019–2022 (USD MILLION) 217
TABLE 105 NORTH AMERICA: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2023–2028 (USD MILLION) 217
TABLE 106 NORTH AMERICA: NLP IN FINANCE MARKET, BY APPLICATION, 2019–2022 (USD MILLION) 218
TABLE 107 NORTH AMERICA: NLP IN FINANCE MARKET, BY APPLICATION, 2023–2028 (USD MILLION) 218
TABLE 108 NORTH AMERICA: NLP IN FINANCE MARKET, BY VERTICAL, 2019–2022 (USD MILLION) 219
TABLE 109 NORTH AMERICA: NLP IN FINANCE MARKET, BY VERTICAL, 2023–2028 (USD MILLION) 219
TABLE 110 NORTH AMERICA: NLP IN FINANCE MARKET, BY COUNTRY, 2019–2022 (USD MILLION) 219
TABLE 111 NORTH AMERICA: NLP IN FINANCE MARKET, BY COUNTRY, 2023–2028 (USD MILLION) 219
10.2.3 US 220
10.2.3.1 US to implement NLP for real-time data analysis 220
TABLE 112 US: NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 220
TABLE 113 US: NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 220
10.2.4 CANADA 221
10.2.4.1 Canadian banks to use NLP-powered chatbots to interact with customers 221
TABLE 114 CANADA: NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 221
TABLE 115 CANADA: NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 221
10.3 EUROPE 222
10.3.1 EUROPE: NLP IN FINANCE MARKET DRIVERS 222
10.3.2 EUROPE: RECESSION IMPACT 222
TABLE 116 EUROPE: NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 223
TABLE 117 EUROPE: NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 223
TABLE 118 EUROPE: NLP IN FINANCE MARKET, BY SOFTWARE, 2019–2022 (USD MILLION) 223
TABLE 119 EUROPE: NLP IN FINANCE MARKET, BY SOFTWARE, 2023–2028 (USD MILLION) 224
TABLE 120 EUROPE: NLP IN FINANCE MARKET, BY SERVICE, 2019–2022 (USD MILLION) 224
TABLE 121 EUROPE: NLP IN FINANCE MARKET, BY SERVICE, 2023–2028 (USD MILLION) 224
TABLE 122 EUROPE: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2019–2022 (USD MILLION) 224
TABLE 123 EUROPE: NLP IN FINANCE MARKET, BY PROFESSIONAL SERVICE, 2023–2028 (USD MILLION) 225
TABLE 124 EUROPE: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2019–2022 (USD MILLION) 225
TABLE 125 EUROPE: NLP IN FINANCE MARKET, BY TECHNOLOGY, 2023–2028 (USD MILLION) 225
TABLE 126 EUROPE: NLP IN FINANCE MARKET, BY APPLICATION, 2019–2022 (USD MILLION) 226
TABLE 127 EUROPE: NLP IN FINANCE MARKET, BY APPLICATION, 2023–2028 (USD MILLION) 226
TABLE 128 EUROPE: NLP IN FINANCE MARKET, BY VERTICAL, 2019–2022 (USD MILLION) 227
TABLE 129 EUROPE: NLP IN FINANCE MARKET, BY VERTICAL, 2023–2028 (USD MILLION) 227
TABLE 130 EUROPE: NLP IN FINANCE MARKET, BY COUNTRY, 2019–2022 (USD MILLION) 227
TABLE 131 EUROPE: NLP IN FINANCE MARKET, BY COUNTRY, 2023–2028 (USD MILLION) 228
10.3.3 UK 228
10.3.3.1 UK companies to leverage NLP to improve operations and gain competitive edge 228
TABLE 132 UK: NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 228
TABLE 133 UK: NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 229
10.3.4 GERMANY 229
10.3.4.1 Adoption of NLP to be driven by regulatory compliance, cost reduction, and better customer experience 229
TABLE 134 GERMANY: NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 229
TABLE 135 GERMANY: NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 229
10.3.5 FRANCE 230
10.3.5.1 France to witness emergence of AI-based chatbots using NLP 230
TABLE 136 FRANCE: NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 230
TABLE 137 FRANCE: NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 230
10.3.6 ITALY 231
10.3.6.1 NLP to help financial institutions analyze large volumes of data efficiently and accurately 231
TABLE 138 ITALY: NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 231
TABLE 139 ITALY: NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 231
10.3.7 SPAIN 232
10.3.7.1 NLP to significantly improve customer service and reduce operating costs in banking 232
TABLE 140 SPAIN: NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 232
TABLE 141 SPAIN: NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 232
 
10.3.8 SWITZERLAND 233
10.3.8.1 Swiss banks and financial institutions to invest in NLP to gain competitive advantage 233
TABLE 142 SWITZERLAND: NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 233
TABLE 143 SWITZERLAND: NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 233
10.3.9 REST OF EUROPE 234
TABLE 144 REST OF EUROPE: NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION) 234
TABLE 145 REST OF EUROPE: NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION) 234