AI in Finance Market Size, Share, Industry, overview, Growth, Latest Trends

Report Code TC 9214
Published in Feb, 2025, By MarketsandMarkets™
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AI in Finance Market by Product (Algorithmic Trading, Virtual Assistants, Robo-Advisors, GRC, IDP, Underwriting Tools), Technology, Application (Fraud Detection, Risk Management, Trend Analysis, Financial Planning, Forecasting) - Global Forecast to 2030

 

Overview

The global AI in Finance market was estimated at USD 38.36 billion in 2024 and is expected to reach USD 190.33 billion in 2030, with a compound annual growth rate (CAGR) of 30.6% during the period from 2024 to 2030.

AI is crucial in finance for boosting efficiency, enhancing decision-making, strengthening financial stability, automating tasks, and accelerating data processing to improve operations and customer service productivity. Financial institutions leverage AI to process large volumes of data, leading to better market forecasts and refined investment strategies. In asset management, AI algorithms integrate diverse data sources, which allow fund managers to identify trends that enhance traditional methods. According to NVIDIA's 2024 Financial Services Industry Survey, over 70% of financial institutions reported improved operational efficiency due to AI, while 60% noted a reduction in operational costs by up to 30%. Customer satisfaction improved for 75% of firms, and 80% plan to increase AI investments in the next two years, emphasizing the technology's critical role in shaping the future of finance. This trend emphasizes AI's role in shaping finance, driving innovation and fostering competitive advantages across the industry.

AI in Finance Market

Attractive Opportunities in the AI in Finance Market

ASIA PACIFIC

The region is experiencing rapid digital transformation in the finance sector, particularly in China, Japan, South Korea, and India. Financial institutions are adopting AI-powered tools for risk management, fraud detection, driven by a strong push for improved operational efficiency and regulatory compliance.

Robust data security is crucial in the AI finance market to prevent data breaches and regulatory violations, ensuring compliance and protecting sensitive financial information from potential threats.

The rise in AI-based financial tools, such as predictive analytics and automated trading, enabling more accurate decision-making and enhanced customer experiences in the finance sector.

AI-driven algorithms improve risk detection and mitigation, enabling more secure financial practices by accurately identifying potential threats and enhancing proactive measures to prevent issues.

The Artificial Intelligence in Finance market in the North American market is expected to be worth 73.83 USD billion by 2030, growing at a CAGR of 28.3% during the forecast period.

Impact of Generative AI on AI In Finance Market

Through increased user engagement and efficiency, generative Al is revolutionizing the finance industry by offering solutions that align with procedures for better customer experiences. Key factors include improved risk management via predictive analytics and automated financial reporting, which reduces errors. The technology also creates individualized financial services by analyzing customer data for communication and guidance. Customer interactions via chatbots are more efficient, and fraud detection ensures legal compliance. Finance professionals can use generative AI to make well-informed investment decisions by using projections based on market trends and historical data.

AI in Finance Market Impact

Global AI in Finance Market Dynamics

Driver: AI-driven algorithms enhance risk identification and mitigation, ensuring safer financial practices

Al-driven algorithms improve risk identification and mitigation in the financial industry for real-time data handling. Large volumes of both structured and unstructured data are analyzed by these algorithms to detect trends and abnormalities, such as fraud or variation in the AI in finance market. Al can forecast possible risks based on past trends by using predictive analytics, which enables organizations to take proactive measures. Al also automates risk monitoring, ensuring the supervision of risk exposure and sending real-time alerts for unusual activity. Risk management procedures are more accurate and effective as a result of Al integration. Its integration makes risk management procedures more accurate and effective, enabling well-informed decision-making, promoting safer financial practices, and enhancing operational resilience.

Restraints: Opacities in financial AI models

Opacities in financial AI models, often referred to as "black boxes," present significant challenges for the finance sector. According to a 2022 LendIt survey, 32% of financial executives cited lack of explainability as a major concern, second only to regulatory compliance. This opacity arises because many AI models, such as random forests and k-means clustering, involve complex algorithms that make it difficult to trace how decisions are made. The lack of transparency can lead to distrust among customers, especially when decisions impact critical financial outcomes like loan approvals or fraud detection. For instance, if a transaction is declined without clear reasoning, customers may feel frustrated and confused, potentially leading to a loss of business. Furthermore, regulatory bodies are increasingly demanding transparency and accountability in AI decision-making processes.

 

Opportunity: Rising demand for hyper-personalized financial products and tailored services drives long-term customer engagement

Customers seek specialized financial services and products that meet their specific needs. Al allows organizations to provide individualized experiences by analyzing large datasets. By using data analytics and machine learning, financial institutions can offer tailored services and suggest flexible investment plans and tailored recommendations. Long-term partnerships are fostered by personalization as customers experience a sense of worth and comprehension. Al-driven insights also enable businesses to be proactive and satisfy client needs. The use of hyper-personalization sets financial institutions apart, boosting client retention and attracting new businesses who seek specialized financial solutions.

Challenge: Algorithmic bias in financial decision-making

Algorithmic bias in financial decision-making poses significant challenges, particularly in lending practices. The Greenlining Institute highlights that algorithms can perpetuate historical inequities, resulting in higher interest rates for Black and Brown borrowers compared to equally qualified White borrowers. A study from UC Berkeley found that online lenders overcharge these minority groups by approximately USD 765 million annually for mortgage loans, despite claims of fairness in algorithmic lending practices. Furthermore, Barclays notes that biased data inputs can lead to discriminatory outcomes when algorithms predict creditworthiness, potentially denying loans based on flawed historical data. Finastra emphasizes that as reliance on algorithms increases, the risk of producing unfair results also escalates, affecting critical areas such as credit scoring and insurance pricing. The implications of such biases are profound, as they not only reinforce existing socioeconomic disparities but also risk legal repercussions for financial institutions.

AI in Finance Market Ecosystem

The AI in finance market ecosystem comprises a diverse range of stakeholders. Key providers include ERP & financial systems, chatbots and virtual assistants, automated reconciliation solutions, intelligent document processing, government, risk and compliance software, accounts payable/receivable automation software, robo-advisors, expense management systems, compliance automation platforms, algorithmic trading platforms, underwriting engines/platforms, and end users. These entities collaborate to develop, deliver, and utilize social media AI solutions, driving innovation and growth in the market.

Top Companies in AI in Finance Market

Note: The above diagram only shows the representation of the Artificial Intelligence in Finance market ecosystem; it is not limited to the companies represented above.
Source: Secondary Research, Interviews with Experts, and MarketsandMarkets Analysis

 

By deployment mode, cloud segment will lead the market during the forecast period.

The cloud segment is anticipated to take the lead in the AI in finance market because of its scalable and flexible nature. To increase data accessibility and enhance customer experiences, financial institutions depend on cloud-based Al solutions. Cloud enables integration with Al tools for tasks like risk management, fraud detection, and financial planning and provides strong data storage and security. In the Al-driven finance industry, the cloud segment has a significant market share as a result of its capacity to support real-time analytics and speed up the deployment of Al applications.

Finance as business function: By application, automated bookkeeping & reconciliation segment will register the highest CAGR during the forecast period.

Businesses use Al solutions to automate data entry and other repetitive tasks such as invoice processing and ledger matching, which used to require manual labor. By reducing human error and offering real-time financial insights, AI-driven tools improve accuracy and provide real-time data. These tools allow businesses to allocate resources more efficiently, facilitating groups to prioritize strategic decision-making over daily tasks. Businesses are recognizing the advantages of automated systems for cost reduction and optimizing financial operations. It is anticipated that bookkeeping solutions will increase, propelling their rapid market expansion. As companies increasingly recognize the benefits of automated systems for cost reduction and financial operations optimization, the demand for bookkeeping solutions is expected to grow, driving rapid market expansion.

Finance as business operation: By end user, fintech segment will register the highest CAGR during the forecast period.

Fintech companies increasingly leverage AI to automate financial services, enhance customer experiences, and improve operational efficiency. This technology enables real-time data analysis, which is crucial for personalized financial solutions and effective risk management. As consumers demand faster and more efficient services, fintech firms utilize AI for tasks such as fraud detection, credit scoring, and customer engagement through chatbots. The continuous innovation and competitive landscape in fintech drive the need for sophisticated AI solutions, positioning this segment for substantial growth in the coming years.

By region, North America will hold the largest market share of the AI in finance market during the forecast period.

North America leads the AI in finance market due to its advanced technological infrastructure and significant investments in innovation. The United States is a prominent player, with major fintech hubs like Silicon Valley and New York fostering a vibrant ecosystem for AI development. Canada also contributes to this landscape, promoting innovation through its growing fintech sector. Top vendors in this space include IBM, known for its Watson AI platform; Microsoft, which offers Azure AI services; and Salesforce, recognized for its AI-driven customer relationship management solutions. These companies leverage machine learning and data analytics to enhance financial services, improve customer experiences, and streamline operations across the industry.

HIGHEST CAGR MARKET DURING FORECAST PERIOD
CANADA FASTEST-GROWING MARKET IN THE REGION
AI in Finance Market Size and Share

Recent Developments of AI in Finance Market

  • In January 2025, Unicaja and Fiserv have entered a strategic payments agreement aimed at enhancing payment solutions and e-commerce capabilities in Spain. This agreement will integrate omnichannel payment processing with a focus on speed, security, and convenience. By combining Unicaja's financial strength with Fiserv's innovative technology, the initiative seeks to optimize customer experiences for merchants across various sectors. The partnership marks Fiserv's first significant venture in Spain and is designed to adapt to the increasing demand for digital financial services, benefiting Unicaja's clientele.
  • In January 2025, Pearson and Microsoft announced a multi-year partnership aimed at transforming education and workforce development through AI. The collaboration will leverage Microsoft’s Azure Cloud and AI technologies to enhance Pearson’s learning and assessment services. Key initiatives include personalized learning at scale, new AI credentials, and the deployment of Microsoft 365 Copilot across Pearson’s workforce. This partnership addresses the global skills gap in AI, with a focus on reskilling workers for the evolving job market. Both companies aim to empower learners and organizations to thrive in an AI-driven economy.
  • In December 2024, Fiserv has announced its acquisition of Payfare Inc. to enhance its embedded finance capabilities. Payfare, known for its innovative workforce payment solutions tailored for gig-economy companies, will complement Fiserv's existing embedded finance offerings. This strategic move aims to broaden Fiserv's technology and program management capabilities, enabling more efficient payment solutions for businesses and their employees. The acquisition underscores Fiserv's commitment to delivering advanced financial services that meet the evolving needs of the market, particularly in the growing gig economy sector. This integration is expected to create significant opportunities for both companies moving forward.
  • In November 2024, FIS and Oracle have partnered to enhance utility billing and payment capabilities for essential services like electricity, gas, and water. The collaboration features FIS's BillerIQ solution running on Oracle Cloud Infrastructure (OCI), enabling seamless electronic bill delivery and payment processing. This integration allows utility customers to manage their bills flexibly, offering multiple payment options such as ACH, credit, debit, and digital wallets. By digitizing the billing process, the partnership aims to improve operational efficiency and customer satisfaction while addressing the inefficiencies associated with traditional payment methods.
  • In October 2024, Google Pay, a digital wallet, and payment platform developed by Google, partnered with Muthoot Finance to offer gold-backed loans, enhancing financial accessibility for users in India. This collaboration allows customers to leverage their gold assets as collateral for quick loans. The process is designed to be user-friendly, enabling loans to be disbursed within 30 minutes through the GPay app. This initiative aims to cater to the growing demand for digital financial services in India and aligns with the government's push for digital inclusion, making it easier for individuals to access credit using their gold holdings.

Key Market Players

List of Top AI in Finance Market Companies

The Artificial Intelligence in Finance market is dominated by a few major players that have a wide regional presence. The major players in the AI in Finance Market are

  • Indata Labs
  • Trumid
  • Emagia
  • Zest AI
  • Underwrite.ai
  • Kasisto

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Scope of the Report

Report Attribute Details
Market size available for years 2019-2030
Base year considered 2023
Forecast period 2023
Forecast units (USD million/billion)
Segments Covered Product type, Technology, Application, End user, and Region
Regions covered North America, Europe, Asia Pacific, Middle East & Africa, Latin America

 

Key Questions Addressed by the Report

What are the opportunities for the AI in finance market?
There are various opportunities in the AI in finance market. AI enables hyper-personalization of financial products, tailoring services to individual customer needs and preferences, enhancing engagement and satisfaction. Financial institutions will harness AI to analyze vast datasets for actionable insights, driving strategic growth and innovation. This technology will also improve risk assessment models, enabling more accurate credit scoring and better management of financial risks.
Define the AI in finance market.
Artificial intelligence (AI) in finance is a set of technologies encompassing machine learning (ML), NLP, generative AI, and predictive analytics, which can replicate human intelligence and decision-making abilities to enhance how organizations analyze, manage, invest, and protect financial processes and systems. AI technology modernizes all finance-based business operations and functions by streamlining traditionally manual processes, unlocking deeper insights from generated data, and better managing delivery outcomes. AI in finance tools supports faster, contactless interactions, including real-time credit approvals and improved fraud protection and risk assessment. Moreover, AI is also changing how financial organizations engage with customers, predicting their behavior and understanding their purchase preferences. This enables more personalized interactions, faster and more accurate customer support, credit scoring refinements, and innovative products and services.
Which region is expected to have the largest share in the AI in finance market?
The North American region will acquire the largest share of the AI in finance market during the forecast period.
Which are the major market players covered in the report?
Some of the key companies in the AI in finance market are FIS (US), Fiserv (US), Google (US), Microsoft (US), Zoho (India), IBM (US), Socure (US), Workiva (US), Plaid (US), SAS Institute (US), C3 AI (US), HighRadius (US), AWS (US), SAP (Germany), Domo (US), Xero (Australia), HPE (US), Oracle (US), Intel (US), NVIDIA (US), Salesforce (US), DataRobot (US), Enova (US), AlphaSense (US), NetApp (US), Ocrolus (US), Vectra AI (US), Teradata (US), Pega (US), Vena Solutions (US), Affirm (US), SymphonyAI (US), Envestnet | Yodlee (US), Addepto (Poland), DataRails (US), SigFig (Australia), Deeper Insights (UK), H2O.ai (US), App0 (US), Underwrite AI (US), Deepgram (US), Emagia (US), InData Labs (US), Zest AI (US), Scienaptic AI (US), Gradient AI (US), Kasisto (US), Trumid (US), DataVisor (US), Kavout (US), and WealthBlock (US).
How big is the global AI in finance market today?
The global AI in finance market is projected to grow from USD 38.36 billion in 2024 to USD 190.33 billion by 2030, at a CAGR of 30.6% during the forecast period.

 

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Table Of Contents

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TITLE
PAGE NO
INTRODUCTION
36
RESEARCH METHODOLOGY
41
EXECUTIVE SUMMARY
53
PREMIUM INSIGHTS
59
MARKET OVERVIEW AND INDUSTRY TRENDS
62
  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
    DRIVERS
    - Increasing demand for precise forecasts for strategic planning and investment
    - Growing adoption of AI algorithms to enhance risk detection and mitigation
    - Rising popularity of personalized financial services
    RESTRAINTS
    - Opacities in financial AI models
    OPPORTUNITIES
    - Growing need for hyper-personalized financial products for long-term customer engagement and tailored services
    - Rising demand for accurate credit scoring and better risk management
    CHALLENGES
    - Algorithmic bias in financial decision-making
  • 5.3 EVOLUTION OF AI IN FINANCE MARKET
  • 5.4 SUPPLY CHAIN ANALYSIS
  • 5.5 ECOSYSTEM
    ERP & FINANCIAL SYSTEMS
    CHATBOT AND VIRTUAL ASSISTANTS
    AUTOMATED RECONCILIATION SYSTEMS
    INTELLIGENT DOCUMENT PROCESSING
    GOVERNMENT, RISK AND COMPLIANCE SOFTWARE
    ACCOUNTS PAYABLE/RECEIVABLE AUTOMATION SOFTWARE
    ROBO-ADVISORS
    EXPENSE MANAGEMENT SYSTEMS
    COMPLIANCE AUTOMATION PLATFORMS
    ALGORITHMIC TRADING PLATFORMS
    UNDERWRITING ENGINES/PLATFORMS
    END USERS
  • 5.6 CASE STUDY ANALYSIS
    PAYPAL ENHANCES FRAUD DETECTION CAPABILITIES WITH H2O.AI'S DRIVERLESS AI SOLUTION
    VENA SOLUTIONS TRANSFORMING FINANCIAL REPORTING AND PLANNING AT SHIFT4 PAYMENTS
    INVESTA ENHANCES FUND REPORTING EFFICIENCY WITH WORKIVA’S STREAMLINED SOLUTIONS
    DATAVISOR AND MICROSOFT AZURE COLLABORATE TO ENHANCE REAL-TIME FRAUD DETECTION
    ZOHO EMPOWERS PLENTI WITH UNIFIED CRM SOLUTION TO ENHANCE CUSTOMER ENGAGEMENT AND OPERATIONAL EFFICIENCY
  • 5.7 TECHNOLOGY ANALYSIS
    KEY TECHNOLOGIES
    - NLP & deep learning
    - Computer vision
    - Predictive analytics
    - Robotic process automation (RPA)
    - Reinforcement learning
    - Explainable AI (XAI)
    - Anomaly detection
    ADJACENT TECHNOLOGIES
    - Cybersecurity
    - IoT
    - AR/VR
    - Digital identity verification
    COMPLEMENTARY TECHNOLOGIES
    - Cloud computing
    - Edge computing
    - Quantum computing
    - Big data analytics
    - Blockchain
  • 5.8 KEY CONFERENCES AND EVENTS, 2025–2026
  • 5.9 INVESTMENT AND FUNDING SCENARIO
  • 5.10 REGULATORY LANDSCAPE
    REGULATORY BODIES, GOVERNMENT AGENCIES, FRAMEWORKS, AND OTHER ORGANIZATIONS
    REGULATORY LANDSCAPE, BY REGION
    - North America
    - Europe
    - Asia Pacific
    - Middle East & Africa
    - Latin America
  • 5.11 PATENT ANALYSIS
    METHODOLOGY
    PATENTS FILED, BY DOCUMENT TYPE
    INNOVATIONS AND PATENT APPLICATIONS
  • 5.12 PRICING ANALYSIS
    AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY APPLICATION
    INDICATIVE PRICING ANALYSIS, BY PRODUCT TYPE
  • 5.13 PORTER’S FIVE FORCES ANALYSIS
    THREAT OF NEW ENTRANTS
    THREAT OF SUBSTITUTES
    BARGAINING POWER OF SUPPLIERS
    BARGAINING POWER OF BUYERS
    INTENSITY OF COMPETITIVE RIVALRY
  • 5.14 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
  • 5.15 KEY STAKEHOLDERS AND BUYING CRITERIA
    KEY STAKEHOLDERS IN BUYING PROCESS
    BUYING CRITERIA
  • 5.16 IMPACT OF GENERATIVE AI ON AI IN FINANCE MARKET
    TOP USE CASES & MARKET POTENTIAL
    - Key use cases
    AUTOMATED FINANCIAL REPORTING
    ENHANCED RISK MANAGEMENT
    PERSONALIZED FINANCIAL SERVICES
    STREAMLINED CUSTOMER INTERACTIONS
    FRAUD DETECTION AND COMPLIANCE
    INNOVATIVE FINANCIAL PLANNING
AI IN FINANCE MARKET, BY PRODUCT
108
  • 6.1 INTRODUCTION
    PRODUCT: AI IN FINANCE MARKET DRIVERS
  • 6.2 TYPE
    ERP AND FINANCIAL SYSTEMS
    - Real-time analytics and automated reporting for improved financial management
    CHATBOTS & VIRTUAL ASSISTANTS
    - Enhancing operational efficiency and customer engagement in financial services
    AUTOMATED RECONCILIATION SOLUTIONS
    - Boosting operational agility for swift transaction processing
    INTELLIGENT DOCUMENT PROCESSING
    - Reducing manual errors, enabling quick decision-making, and accelerating processing time
    GOVERNANCE, RISK, AND COMPLIANCE (GRC) SOFTWARE
    - Facilitating seamless collaboration across departments
    ACCOUNTS PAYABLE/RECEIVABLE AUTOMATION SOFTWARE
    - Providing real-time insights for informed financial decisions
    ROBO-ADVISORS
    - Providing automated investment management and financial advisory services
    EXPENSE MANAGEMENT SYSTEMS
    - Streamlining financial operations and controlling costs
    COMPLIANCE AUTOMATION PLATFORMS
    - Identifying compliance risks and enabling real-time alerts
    ALGORITHMIC TRADING PLATFORMS
    - Automating trade execution and responding to market fluctuations
    UNDERWRITING ENGINES/PLATFORMS
    - Expediting loan approvals and promoting fair lending
    OTHER PRODUCT TYPES
  • 6.3 DEPLOYMENT MODE
    CLOUD
    - Cloud deployment offers scalability, flexibility, and cost-efficiency
    ON-PREMISES
    - On-premises deployment provides fast data processing and real-time analytics
AI IN FINANCE MARKET, BY TECHNOLOGY
127
  • 7.1 INTRODUCTION
    TECHNOLOGY: AI IN FINANCE MARKET DRIVERS
  • 7.2 GENERATIVE AI
    ENHANCES CUSTOMER ENGAGEMENT AND PROCESS AUTOMATION IN FINANCE
  • 7.3 OTHER AI TECHNOLOGIES
    NLP
    - NLP boosts data analysis, automates interactions, and enhances compliance
    PREDICTIVE ANALYTICS
    - AI-driven predictive analytics enables accurate forecasting
AI IN FINANCE MARKET, BY APPLICATION
133
  • 8.1 INTRODUCTION
    APPLICATION: AI IN FINANCE MARKET DRIVERS
  • 8.2 FINANCE AS BUSINESS OPERATIONS
    FRAUD DETECTION & PREVENTION
    - AI-driven fraud detection enhances security and reduces financial losses
    - Real-time transaction monitoring
    - Customer data security
    - Customer behavior analysis
    - Trend analysis
    - Others
    RISK MANAGEMENT
    - AI-driven risk management enhances decision-making in finance
    - Credit risk scoring
    - Market volatility prediction
    - Stress testing
    - Others
    CUSTOMER SERVICE & ENGAGEMENT
    - Customer service and engagement enhance personalization, leading to improved client satisfaction
    - Chatbots/Virtual assistants for customer support
    - Personalized financial product recommendations
    - Market segmentation
    - Personalized marketing messaging
    - New customer acquisition
    - Data-driven decision making
    - Customer retention management
    - Others
    FINANCIAL COMPLIANCE & REGULATORY REPORTING
    - Financial compliance streamlines accuracy and efficiency in meeting standards
    - Risk & compliance management
    - Audit & reporting
    - Others
    INVESTMENT & PORTFOLIO MANAGEMENT
    - AI optimizes investment and portfolio management for smarter decision-making and improved returns
    - Robo-advisors for wealth management
    - Portfolio rebalancing
    - Others
  • 8.3 FINANCE AS BUSINESS FUNCTIONS
    FINANCIAL PLANNING & FORECASTING
    - Financial planning enhances accuracy and decision-making in finance
    - Demand forecasting (CAPEX/OPEX)
    - Cash flow forecasting
    - Budgeting & expense management
    - Scenario planning
    - Others
    AUTOMATED BOOKKEEPING & RECONCILIATION
    - Automated bookkeeping and reconciliation streamline financial processes and enhance accuracy
    - Real-time ledger matching
    - Invoice processing
    - Variance detection
    - Others
    PROCUREMENT & SUPPLY CHAIN FINANCE
    - AI optimizes supply chain management by boosting efficiency and reducing costs
    - Invoice discounting
    - Supplier risk scoring
    - Dynamic payments
    - Payment automation
    - Others
    REVENUE CYCLE MANAGEMENT
    - Revenue cycle management automates processes and improves cash flow through enhanced accuracy in billing
    - Payment optimization
    - Subscription billing management
    - Invoice settlements/Automated invoice processing
    - Churn management
    - Others
AI IN FINANCE MARKET, BY END USER
158
  • 9.1 INTRODUCTION
    END USER: AI IN FINANCE MARKET DRIVERS
  • 9.2 END USER
    FINANCE AS BUSINESS FUNCTIONS
    - Government & public sector
    - Retail & e-commerce
    - Real estate
    - Manufacturing
    - Telecom & media
    - Healthcare & pharma
    - Utilities
    - Education
    - Technology & software
    - Other end users
  • 9.3 FINANCE AS BUSINESS OPERATIONS
    BANKING
    - AI enables better risk management and improves fraud detection
    - Corporate & commercial banking
    - Retail banking
    - Investment banking
    INSURANCE
    - AI automates claim processing, reduces fraud, and personalizes policies
    INVESTMENT & ASSET MANAGEMENT
    - AI enhances decision-making and optimizes portfolio management
    - Hedge funds
    - Private equity
    - Wealth management
    FINTECH
    - AI in fintech automates tasks, improves data analysis, and provides real-time insights
    - Blockchain & cryptocurrency providers
    - Lending platform providers/specialty lenders
    CAPITAL MARKETS/REGTECH
    - AI increases efficiency and reduces operational costs in capital markets
AI IN FINANCE MARKET, BY REGION
183
  • 10.1 INTRODUCTION
  • 10.2 NORTH AMERICA
    NORTH AMERICA: AI IN FINANCE MARKET DRIVERS
    NORTH AMERICA: MACROECONOMIC IMPACT
    US
    - Transforming brands with AI-driven personalization in social media
    CANADA
    - Accelerating AI adoption in finance through automation and digital transformation
  • 10.3 EUROPE
    EUROPE: AI IN FINANCE MARKET DRIVERS
    EUROPE: MACROECONOMIC IMPACT
    UK
    - Leveraging automation and data analytics for enhanced decision-making and compliance
    GERMANY
    - Focus on automation in risk management and personalized banking services to improve operational efficiency
    FRANCE
    - Robust government initiatives promote innovation and establish frameworks encouraging AI technology adoption
    ITALY
    - Promotion of digital transformation and rising investment in AI technologies across financial institutions
    SPAIN
    - Increased funding and strategic partnerships to enhance AI collaboration in financial services
    REST OF EUROPE
  • 10.4 ASIA PACIFIC
    ASIA PACIFIC: AI IN FINANCE MARKET DRIVERS
    ASIA PACIFIC: MACROECONOMIC IMPACT
    CHINA
    - Increasing focus on AI innovation for operational efficiency in financial sector to boost market
    JAPAN
    - Partnerships between financial institutions and tech firms accelerate AI integration for improved financial solutions
    INDIA
    - Increasing adoption of AI-powered solutions by financial institutions for risk management to drive market
    SOUTH KOREA
    - Government support enhances financial services and boosts competitiveness in fintech sector
    AUSTRALIA & NEW ZEALAND
    - Increasing adoption of AI by growing fintech companies to drive market
    ASEAN
    - Increasing digitalization of banking services to drive market
    REST OF ASIA PACIFIC
  • 10.5 MIDDLE EAST & AFRICA
    MIDDLE EAST & AFRICA: AI IN FINANCE MARKET DRIVERS
    MIDDLE EAST & AFRICA: MACROECONOMIC IMPACT
    MIDDLE EAST
    - KSA
    - UAE
    - Kuwait
    - Bahrain
    AFRICA
    - Increasing adoption of AI to enhance financial services to drive market
  • 10.6 LATIN AMERICA
    LATIN AMERICA: AI IN FINANCE MARKET DRIVERS
    LATIN AMERICA: MACROECONOMIC IMPACT
    BRAZIL
    - Government support and investments in AI to drive market
    MEXICO
    - Increased investment in fintech to drive AI adoption in finance market
    ARGENTINA
    - Fintech expansion and innovation to propel market growth
    REST OF LATIN AMERICA
COMPETITIVE LANDSCAPE
253
  • 11.1 OVERVIEW
  • 11.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2020–2024
  • 11.3 REVENUE ANALYSIS, 2019–2023
  • 11.4 MARKET SHARE ANALYSIS, 2023
    MARKET SHARE ANALYSIS OF KEY PLAYERS (FINANCE AS BUSINESS FUNCTIONS)
    MARKET RANKING ANALYSIS (FINANCE AS BUSINESS FUNCTIONS)
    MARKET SHARE ANALYSIS OF KEY PLAYERS (FINANCE AS BUSINESS OPERATIONS)
    MARKET RANKING ANALYSIS (FINANCE AS BUSINESS OPERATIONS)
  • 11.5 PRODUCT COMPARISON
    PRODUCT COMPARATIVE ANALYSIS, BY RISK ASSESSMENT
    - ZAML (Zest Automated Machine Learning) (Zest AI)
    - Kensho Risk (Kensho)
    - C3 AI Risk Management (C3 AI)
    - Finacle Treasury and Risk Management Solution (Infosys)
    PRODUCT COMPARATIVE ANALYSIS, BY FRAUD DETECTION & PREVENTION
    - Socure ID+ (Socure)
    - Dataminr Real-Time Risk Detection (Dataminr)
    - Google Cloud (Google)
    - Vectra Cognito (Vectra AI)
    PRODUCT COMPARATIVE ANALYSIS, BY CHATBOTS & PERSONAL ASSISTANTS
    - AlphaSense Search Chatbot (AlphaSense)
    - Oracle Digital Assistant (Oracle)
    - Watson Assistant (IBM)
  • 11.6 COMPANY VALUATION AND FINANCIAL METRICS OF KEY VENDORS
  • 11.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
    COMPANY EVALUATION MATRIX: KEY PLAYERS (FINANCE AS BUSINESS FUNCTIONS)
    - Stars
    - Emerging Leaders
    - Pervasive Players
    - Participants
    COMPANY EVALUATION MATRIX: KEY PLAYERS (FINANCE AS BUSINESS OPERATIONS)
    - Stars
    - Emerging leaders
    - Pervasive players
    - Participants
    COMPANY FOOTPRINT: KEY PLAYERS
    - Company footprint (1/2)
    - Company footprint (2/2)
    - Regional footprint
    - Product footprint
    - Application footprint
    - End-user footprint
  • 11.8 COMPANY EVALUATION MATRIX: START-UPS/SMES, 2023
    COMPANY EVALUATION MATRIX: START-UPS/SMES (FINANCE AS BUSINESS OPERATIONS)
    - Progressive companies
    - Responsive companies
    - Dynamic companies
    - Starting blocks
    COMPANY EVALUATION MATRIX: START-UPS/SMES (FINANCE AS BUSINESS FUNCTIONS)
    - Progressive companies
    - Responsive companies
    - Dynamic companies
    - Starting blocks
    COMPETITIVE BENCHMARKING: START-UPS/SMES, 2024
    - Detailed list of key start-ups/SMEs
    - Competitive benchmarking of key start-ups/SMEs
  • 11.9 COMPETITIVE SCENARIO
    PRODUCT LAUNCHES AND ENHANCEMENTS
    DEALS
COMPANY PROFILES
293
  • 12.1 INTRODUCTION
  • 12.2 KEY PLAYERS
    FIS
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    FISERV
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    GOOGLE
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    MICROSOFT
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    ZOHO
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    IBM
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    SOCURE
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    WORKIVA
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    PLAID
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    C3 AI
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    HIGHRADIUS
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    SAP
    DOMO
    XERO
    AWS
    HPE
    ORACLE
    SALESFORCE
    NETAPP
    DATAROBOT
    ENOVA INTERNATIONAL
    ALPHASENSE
    OCROLUS
    VECTRA AI
    TERADATA
    PEGA
    VENA SOLUTIONS
    AFFIRM
    SYMPHONYAI
    ENVESTNET | YODLEE
  • 12.3 START-UPS/SMES
    ADDEPTO
    DATARAILS
    SIGFIG
    DEEPER INSIGHTS
    H2O.AI
    APP0
    UNDERWRITE.AI
    DEEPGRAM
    EMAGIA
    INDATA LABS
    ZEST AI
    SCIENAPTIC AI
    GRADIENT AI
    KASISTO
    TRUMID
    DATAVISOR
    KAVOUT
    WEALTHBLOCK
ADJACENT AND RELATED MARKETS
379
  • 13.1 INTRODUCTION
  • 13.2 ARTIFICIAL INTELLIGENCE (AI) MARKET – GLOBAL FORECAST TO 2030
    MARKET DEFINITION
    MARKET OVERVIEW
    - Artificial intelligence market, by offering
    - Artificial intelligence market, by business function
    - Artificial intelligence market, by technology
    - Artificial intelligence market, by vertical
    - Artificial intelligence market, by region
  • 13.3 NLP IN FINANCE MARKET – GLOBAL FORECAST TO 2028
    MARKET DEFINITION
    MARKET OVERVIEW
    - NLP in finance market, by offering
    - NLP in finance market, by application
    - NLP in finance market, by technology
    - NLP in finance market, by vertical
    - NLP in finance market, by region
APPENDIX
393
  • 14.1 DISCUSSION GUIDE
  • 14.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
  • 14.3 CUSTOMIZATION OPTIONS
  • 14.4 RELATED REPORTS
  • 14.5 AUTHOR DETAILS
LIST OF TABLES
 
  • TABLE 1 USD EXCHANGE RATES, 2019–2023
  • TABLE 2 PRIMARY INTERVIEWS
  • TABLE 3 FACTOR ANALYSIS
  • TABLE 4 AI IN FINANCE MARKET SIZE AND GROWTH RATE, 2019–2023 (USD MILLION, Y-O-Y %)
  • TABLE 5 AI IN FINANCE MARKET SIZE AND GROWTH RATE, 2024–2030 (USD MILLION, Y-O-Y %)
  • TABLE 6 ROLE OF COMPANIES IN ECOSYSTEM
  • TABLE 7 AI IN FINANCE MARKET: DETAILED LIST OF KEY CONFERENCES AND EVENTS, 2025–2026
  • TABLE 8 NORTH AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 9 EUROPE: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 10 ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 11 MIDDLE EAST & AFRICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 12 LATIN AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 13 PATENTS FILED, 2013–2024
  • TABLE 14 AI IN FINANCE MARKET: LIST OF PATENTS GRANTED, 2024–2025
  • TABLE 15 AVERAGE SELLING PRICE OF KEY PLAYERS FOR TOP 3 APPLICATIONS
  • TABLE 16 AI IN FINANCE MARKET: INDICATIVE PRICING OF PRODUCT TYPES
  • TABLE 17 IMPACT OF PORTER’S FIVE FORCES ON AI IN FINANCE MARKET
  • TABLE 18 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP 3 APPLICATIONS
  • TABLE 19 KEY BUYING CRITERIA FOR TOP 3 APPLICATIONS
  • TABLE 20 AI IN FINANCE MARKET, BY PRODUCT, 2019–2023 (USD MILLION)
  • TABLE 21 AI IN FINANCE MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 22 ERP & FINANCIAL SYSTEMS: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 23 ERP & FINANCIAL SYSTEMS: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 24 CHATBOTS & VIRTUAL ASSISTANTS: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 25 CHATBOTS & VIRTUAL ASSISTANTS: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 26 AUTOMATED RECONCILIATION SOLUTIONS: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 27 AUTOMATED RECONCILIATION SOLUTIONS: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 28 INTELLIGENT DOCUMENT PROCESSING: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 29 INTELLIGENT DOCUMENT PROCESSING: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 30 GOVERNANCE, RISK, AND COMPLIANCE (GRC) SOFTWARE: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 31 GOVERNANCE, RISK, AND COMPLIANCE (GRC) SOFTWARE: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 32 ACCOUNTS PAYABLE/RECEIVABLE AUTOMATION SOFTWARE: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 33 ACCOUNTS PAYABLE/RECEIVABLE AUTOMATION SOFTWARE: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 34 ROBO-ADVISORS: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 35 ROBO-ADVISORS: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 36 EXPENSE MANAGEMENT SYSTEMS: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 37 EXPENSE MANAGEMENT SYSTEMS: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 38 COMPLIANCE AUTOMATION PLATFORMS: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 39 COMPLIANCE AUTOMATION PLATFORMS: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 40 ALGORITHMIC TRADING PLATFORMS: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 41 ALGORITHMIC TRADING PLATFORMS: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 42 UNDERWRITING ENGINES/PLATFORMS: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 43 UNDERWRITING ENGINES/PLATFORMS: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 44 OTHER PRODUCT TYPES: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 45 OTHER PRODUCT TYPES: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 46 AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 47 AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 48 CLOUD: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 49 CLOUD: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 50 ON-PREMISES: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 51 ON-PREMISES: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 52 AI IN FINANCE MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 53 AI IN FINANCE MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 54 GENERATIVE AI: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 55 GENERATIVE AI: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 56 OTHER AI: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 57 OTHER AI: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 58 AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 59 AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 60 FRAUD DETECTION & PREVENTION: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 61 FRAUD DETECTION & PREVENTION: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 62 RISK MANAGEMENT: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 63 RISK MANAGEMENT: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 64 CUSTOMER SERVICE & ENGAGEMENT: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 65 CUSTOMER SERVICE & ENGAGEMENT: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 66 FINANCIAL COMPLIANCE & REGULATORY REPORTING: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 67 FINANCIAL COMPLIANCE & REGULATORY REPORTING: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 68 INVESTMENT & PORTFOLIO MANAGEMENT: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 69 INVESTMENT & PORTFOLIO MANAGEMENT: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 70 AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 71 AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 72 FINANCIAL PLANNING & FORECASTING: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 73 FINANCIAL PLANNING & FORECASTING: AI IN FINANCE MARKET BY REGION, 2024–2030 (USD MILLION)
  • TABLE 74 AUTOMATED BOOKKEEPING & RECONCILIATION: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 75 AUTOMATED BOOKKEEPING & RECONCILIATION: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 76 PROCUREMENT & SUPPLY CHAIN FINANCE: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 77 PROCUREMENT & SUPPLY CHAIN FINANCE: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 78 REVENUE CYCLE MANAGEMENT: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 79 REVENUE CYCLE MANAGEMENT: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 80 AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 81 AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 82 FINANCE AS BUSINESS FUNCTIONS: AI IN FINANCE MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 83 FINANCE AS BUSINESS FUNCTIONS: AI IN FINANCE MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 84 FINANCE AS BUSINESS FUNCTIONS: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 85 FINANCE AS BUSINESS FUNCTIONS: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 86 GOVERNMENT & PUBLIC SECTOR: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 87 GOVERNMENT & PUBLIC SECTOR: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 88 RETAIL & E-COMMERCE: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 89 RETAIL & E-COMMERCE: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 90 REAL ESTATE: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 91 REAL ESTATE: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 92 MANUFACTURING: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 93 MANUFACTURING: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 94 TELECOM & MEDIA: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 95 TELECOM & MEDIA: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 96 HEALTHCARE & PHARMA: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 97 HEALTHCARE & PHARMA: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 98 UTILITIES: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 99 UTILITIES: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 100 EDUCATION: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 101 EDUCATION: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 102 TECHNOLOGY & SOFTWARE: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 103 TECHNOLOGY & SOFTWARE: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 104 OTHER END USERS: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 105 OTHER END USERS: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 106 FINANCE AS BUSINESS OPERATIONS: AI IN FINANCE MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 107 FINANCE AS BUSINESS OPERATIONS: AI IN FINANCE MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 108 FINANCE AS BUSINESS OPERATIONS: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 109 FINANCE AS BUSINESS OPERATIONS: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 110 BANKING: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 111 BANKING: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 112 INSURANCE: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 113 INSURANCE: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 114 INVESTMENT & ASSET MANAGEMENT: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 115 INVESTMENT & ASSET MANAGEMENT: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 116 FINTECH: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 117 FINTECH: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 118 CAPITAL MARKETS/REGTECH: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 119 CAPITAL MARKETS/REGTECH: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 120 AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 121 AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 122 NORTH AMERICA: AI IN FINANCE MARKET, BY PRODUCT, 2019–2023 (USD MILLION)
  • TABLE 123 NORTH AMERICA: AI IN FINANCE MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 124 NORTH AMERICA: AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 125 NORTH AMERICA: AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 126 NORTH AMERICA: AI IN FINANCE MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 127 NORTH AMERICA: AI IN FINANCE MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 128 NORTH AMERICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 129 NORTH AMERICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 130 NORTH AMERICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 131 NORTH AMERICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 132 NORTH AMERICA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 133 NORTH AMERICA: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 134 NORTH AMERICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 135 NORTH AMERICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 136 NORTH AMERICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 137 NORTH AMERICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 138 NORTH AMERICA: AI IN FINANCE MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 139 NORTH AMERICA: AI IN FINANCE MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 140 US: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 141 US: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 142 CANADA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 143 CANADA: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 144 EUROPE: AI IN FINANCE MARKET, BY PRODUCT, 2019–2023 (USD MILLION)
  • TABLE 145 EUROPE: AI IN FINANCE MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 146 EUROPE: AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 147 EUROPE: AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 148 EUROPE: AI IN FINANCE MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 149 EUROPE: AI IN FINANCE MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 150 EUROPE: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 151 EUROPE: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 152 EUROPE: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 153 EUROPE: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 154 EUROPE: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 155 EUROPE: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 156 EUROPE: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 157 EUROPE: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 158 EUROPE: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 159 EUROPE: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 160 EUROPE: AI IN FINANCE MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 161 EUROPE: AI IN FINANCE MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 162 UK: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 163 UK: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 164 GERMANY: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 165 GERMANY: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 166 FRANCE: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 167 FRANCE: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 168 ITALY: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 169 ITALY: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 170 SPAIN: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 171 SPAIN: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 172 REST OF EUROPE: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 173 REST OF EUROPE: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 174 ASIA PACIFIC: AI IN FINANCE MARKET, BY PRODUCT, 2019–2023 (USD MILLION)
  • TABLE 175 ASIA PACIFIC: AI IN FINANCE MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 176 ASIA PACIFIC: AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 177 ASIA PACIFIC: AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 178 ASIA PACIFIC: AI IN FINANCE MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 179 ASIA PACIFIC: AI IN FINANCE MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 180 ASIA PACIFIC: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 181 ASIA PACIFIC: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 182 ASIA PACIFIC: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 183 ASIA PACIFIC: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 184 ASIA PACIFIC: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 185 ASIA PACIFIC: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 186 ASIA PACIFIC: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 187 ASIA PACIFIC: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 188 ASIA PACIFIC: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 189 ASIA PACIFIC: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 190 ASIA PACIFIC: AI IN FINANCE MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 191 ASIA PACIFIC: AI IN FINANCE MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 192 CHINA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 193 CHINA: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 194 JAPAN: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 195 JAPAN: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 196 INDIA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 197 INDIA: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 198 SOUTH KOREA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 199 SOUTH KOREA: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 200 AUSTRALIA & NEW ZEALAND: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 201 AUSTRALIA & NEW ZEALAND: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 202 ASEAN: AI IN FINANCE MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 203 ASEAN: AI IN FINANCE MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 204 ASEAN: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 205 ASEAN: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 206 REST OF ASIA PACIFIC: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 207 REST OF ASIA PACIFIC: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 208 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY PRODUCT, 2019–2023 (USD MILLION)
  • TABLE 209 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 210 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 211 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 212 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 213 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 214 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 215 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 216 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 217 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 218 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 219 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 220 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 221 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 222 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 223 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 224 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 225 MIDDLE EAST & AFRICA: AI IN FINANCE MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 226 MIDDLE EAST: AI IN FINANCE MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 227 MIDDLE EAST: AI IN FINANCE MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 228 KSA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 229 KSA: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 230 UAE: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 231 UAE: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 232 KUWAIT: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 233 KUWAIT: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 234 BAHRAIN: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 235 BAHRAIN: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 236 AFRICA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 237 AFRICA: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 238 LATIN AMERICA: AI IN FINANCE MARKET, BY PRODUCT, 2019–2023 (USD MILLION)
  • TABLE 239 LATIN AMERICA: AI IN FINANCE MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 240 LATIN AMERICA: AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 241 LATIN AMERICA: AI IN FINANCE MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 242 LATIN AMERICA: AI IN FINANCE MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 243 LATIN AMERICA: AI IN FINANCE MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 244 LATIN AMERICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 245 LATIN AMERICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 246 LATIN AMERICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 247 LATIN AMERICA: AI IN FINANCE MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 248 LATIN AMERICA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 249 LATIN AMERICA: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 250 LATIN AMERICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 251 LATIN AMERICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 252 LATIN AMERICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 253 LATIN AMERICA: AI IN FINANCE MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 254 LATIN AMERICA: AI IN FINANCE MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 255 LATIN AMERICA: AI IN FINANCE MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 256 BRAZIL: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 257 BRAZIL: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 258 MEXICO: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 259 MEXICO: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 260 ARGENTINA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 261 ARGENTINA: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 262 REST OF LATIN AMERICA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 263 REST OF LATIN AMERICA: AI IN FINANCE MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 264 AI IN FINANCE MARKET: OVERVIEW OF STRATEGIES ADOPTED BY KEY VENDORS, 2020–2024
  • TABLE 265 AI IN FINANCE MARKET (FINANCE AS BUSINESS FUNCTIONS): DEGREE OF COMPETITION, 2023
  • TABLE 266 AI IN FINANCE MARKET (FINANCE AS BUSINESS OPERATIONS): DEGREE OF COMPETITION, 2023
  • TABLE 267 AI IN FINANCE MARKET: REGION FOOTPRINT
  • TABLE 268 AI IN FINANCE MARKET: PRODUCT FOOTPRINT
  • TABLE 269 AI IN FINANCE MARKET: APPLICATION FOOTPRINT (BUSINESS OPERATIONS)
  • TABLE 270 AI IN FINANCE MARKET: END-USER FOOTPRINT (BUSINESS OPERATIONS)
  • TABLE 271 AI IN FINANCE MARKET: DETAILED LIST OF KEY START-UPS/SMES
  • TABLE 272 AI IN FINANCE MARKET: COMPETITIVE BENCHMARKING OF START-UPS/SMES
  • TABLE 273 AI IN FINANCE MARKET: PRODUCT LAUNCHES AND ENHANCEMENTS, AUGUST 2024 – DECEMBER 2024
  • TABLE 274 AI IN FINANCE MARKET: DEALS, OCTOBER 2024 – JANUARY 2025
  • TABLE 275 FIS: COMPANY OVERVIEW
  • TABLE 276 FIS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 277 FIS: PRODUCT LAUNCHES AND ENHANCEMENTS
  • TABLE 278 FIS: DEALS
  • TABLE 279 FISERV: COMPANY OVERVIEW
  • TABLE 280 FISERV: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 281 FISERV: PRODUCT ENHANCEMENTS
  • TABLE 282 FISERV: DEALS
  • TABLE 283 FISERV: DEALS
  • TABLE 284 GOOGLE: COMPANY OVERVIEW
  • TABLE 285 GOOGLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 286 GOOGLE: PRODUCT LAUNCHES AND ENHANCEMENTS
  • TABLE 287 GOOGLE: DEALS
  • TABLE 288 MICROSOFT: COMPANY OVERVIEW
  • TABLE 289 MICROSOFT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 290 MICROSOFT: PRODUCT LAUNCHES AND ENHANCEMENTS
  • TABLE 291 MICROSOFT: DEALS
  • TABLE 292 ZOHO: COMPANY OVERVIEW
  • TABLE 293 ZOHO: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 294 ZOHO: PRODUCT LAUNCHES AND ENHANCEMENTS
  • TABLE 295 ZOHO: DEALS
  • TABLE 296 IBM: COMPANY OVERVIEW
  • TABLE 297 IBM: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 298 IBM: PRODUCT LAUNCHES AND ENHANCEMENTS
  • TABLE 299 IBM: DEALS
  • TABLE 300 SOCURE: COMPANY OVERVIEW
  • TABLE 301 SOCURE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 302 SOCURE: DEALS
  • TABLE 303 SOCURE: EXPANSIONS
  • TABLE 304 SOCURE: OTHERS
  • TABLE 305 WORKIVA: COMPANY OVERVIEW
  • TABLE 306 WORKIVA: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 307 WORKIVA: DEALS
  • TABLE 308 WORKIVA: EXPANSIONS
  • TABLE 309 PLAID: COMPANY OVERVIEW
  • TABLE 310 PLAID: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 311 PLAID: DEALS
  • TABLE 312 C3 AI: COMPANY OVERVIEW
  • TABLE 313 C3 AI: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 314 C3 AI: DEALS
  • TABLE 315 HIGHRADIUS: COMPANY OVERVIEW
  • TABLE 316 HIGHRADIUS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 317 HIGHRADIUS: PRODUCT LAUNCHES AND ENHANCEMENTS
  • TABLE 318 HIGHRADIUS: DEALS
  • TABLE 319 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2019–2023 (USD BILLION)
  • TABLE 320 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2024–2030 (USD BILLION)
  • TABLE 321 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD BILLION)
  • TABLE 322 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD BILLION)
  • TABLE 323 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2019–2023 (USD BILLION)
  • TABLE 324 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2024–2030 (USD BILLION)
  • TABLE 325 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2019–2023 (USD BILLION)
  • TABLE 326 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2024–2030 (USD BILLION)
  • TABLE 327 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2019–2023 (USD BILLION)
  • TABLE 328 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2024–2030 (USD BILLION)
  • TABLE 329 NLP IN FINANCE MARKET, BY OFFERING, 2019–2022 (USD MILLION)
  • TABLE 330 NLP IN FINANCE MARKET, BY OFFERING, 2023–2028 (USD MILLION)
  • TABLE 331 NLP IN FINANCE MARKET, BY APPLICATION, 2019–2022 (USD MILLION)
  • TABLE 332 NLP IN FINANCE MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
  • TABLE 333 NLP IN FINANCE MARKET, BY TECHNOLOGY, 2019–2022 (USD MILLION)
  • TABLE 334 NLP IN FINANCE MARKET, BY TECHNOLOGY, 2023–2028 (USD MILLION)
  • TABLE 335 NLP IN FINANCE MARKET, BY VERTICAL, 2019–2022 (USD MILLION)
  • TABLE 336 NLP IN FINANCE MARKET, BY VERTICAL, 2023–2028 (USD MILLION)
  • TABLE 337 NLP IN FINANCE MARKET, BY REGION, 2019–2022 (USD MILLION)
  • TABLE 338 NLP IN FINANCE MARKET, BY REGION, 2023–2028 (USD MILLION)
LIST OF FIGURES
 
  • FIGURE 1 AI IN FINANCE MARKET: RESEARCH DESIGN
  • FIGURE 2 DATA TRIANGULATION
  • FIGURE 3 AI IN FINANCE MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES
  • FIGURE 4 APPROACH 1, BOTTOM-UP (SUPPLY-SIDE): REVENUE FROM SOFTWARE/SERVICES OF AI IN FINANCE MARKET
  • FIGURE 5 APPROACH 2, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL SOFTWARE/SERVICES OF AI IN FINANCE MARKET
  • FIGURE 6 APPROACH 3, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL PRODUCTS OF AI IN FINANCE MARKET
  • FIGURE 7 APPROACH 4, BOTTOM-UP (DEMAND-SIDE): SHARE OF AI IN FINANCE MARKET THROUGH OVERALL SPENDING
  • FIGURE 8 ALGORITHMIC TRADING PLATFORMS SEGMENT TO LEAD MARKET IN 2024
  • FIGURE 9 CLOUD SEGMENT TO DOMINATE MARKET IN 2024
  • FIGURE 10 OTHER AI TECHNOLOGIES SEGMENT TO DOMINATE MARKET IN 2024
  • FIGURE 11 FRAUD DETECTION & PREVENTION SEGMENT TO HOLD LARGEST MARKET SHARE IN 2024
  • FIGURE 12 FINANCIAL PLANNING & FORECASTING SEGMENT TO LEAD MARKET IN 2024
  • FIGURE 13 FINANCE AS BUSINESS OPERATIONS SEGMENT TO HAVE LARGER MARKET SHARE THAN FINANCE AS BUSINESS FUNCTIONS SEGMENT IN 2024
  • FIGURE 14 BANKING SEGMENT TO DOMINATE MARKET IN 2024
  • FIGURE 15 RETAIL & ECOMMERCE SEGMENT TO HOLD LARGEST MARKET SIZE IN 2024
  • FIGURE 16 ASIA PACIFIC TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 17 RISING DEMAND FOR PRECISE FORECASTS FOR STRATEGIC PLANNING AND INVESTMENT TO DRIVE MARKET
  • FIGURE 18 CUSTOMER SERVICE & ENGAGEMENT SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 19 CLOUD AND FINANCE AS BUSINESS OPERATIONS SEGMENTS TO HOLD LARGEST MARKET SHARES IN NORTH AMERICA IN 2024
  • FIGURE 20 NORTH AMERICA TO ACCOUNT FOR LARGEST MARKET SHARE IN 2024
  • FIGURE 21 AI IN FINANCE MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
  • FIGURE 22 EVOLUTION OF AI IN FINANCE MARKET
  • FIGURE 23 AI IN FINANCE MARKET: SUPPLY CHAIN ANALYSIS
  • FIGURE 24 AI IN FINANCE MARKET: ECOSYSTEM
  • FIGURE 25 AI IN FINANCE MARKET: INVESTMENT AND FUNDING SCENARIO (USD MILLION AND NUMBER OF FUNDING ROUNDS)
  • FIGURE 26 NUMBER OF PATENTS GRANTED TO VENDORS IN LAST 10 YEARS
  • FIGURE 27 REGIONAL ANALYSIS OF PATENTS GRANTED, 2013–2024
  • FIGURE 28 AVERAGE SELLING PRICE OF KEY PLAYERS FOR TOP 3 APPLICATIONS
  • FIGURE 29 AI IN FINANCE MARKET: PORTER’S FIVE FORCES ANALYSIS
  • FIGURE 30 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
  • FIGURE 31 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP 3 APPLICATIONS
  • FIGURE 32 KEY BUYING CRITERIA FOR TOP 3 APPLICATIONS
  • FIGURE 33 MARKET POTENTIAL OF GENERATIVE AI TO ADVANCE AI IN FINANCE ACROSS KEY END USERS
  • FIGURE 34 COMPLIANCE AUTOMATION PLATFORMS SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 35 ON-PREMISES SEGMENT TO REGISTER HIGHER CAGR THAN CLOUD SEGMENT DURING FORECAST PERIOD
  • FIGURE 36 GENERATIVE AI SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 37 CUSTOMER SERVICE & ENGAGEMENT SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 38 AUTOMATED BOOKKEEPING & RECONCILIATION SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 39 FINANCE AS BUSINESS OPERATIONS SEGMENT TO REGISTER HIGHER CAGR THAN FINANCE AS BUSINESS FUNCTIONS SEGMENT DURING FORECAST PERIOD
  • FIGURE 40 HEALTHCARE & PHARMA SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 41 INVESTMENT & ASSET MANAGEMENT SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 42 INDIA TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 43 ASIA PACIFIC TO WITNESS HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 44 NORTH AMERICA: AI IN FINANCE MARKET SNAPSHOT
  • FIGURE 45 ASIA PACIFIC: AI IN FINANCE MARKET SNAPSHOT
  • FIGURE 46 AI IN FINANCE MARKET: REVENUE ANALYSIS OF FIVE KEY PLAYERS (FINANCE AS BUSINESS FUNCTIONS), 2019–2023
  • FIGURE 47 AI IN FINANCE MARKET: REVENUE ANALYSIS OF FIVE KEY PLAYERS (FINANCE AS BUSINESS OPERATIONS), 2019–2023
  • FIGURE 48 SHARE ANALYSIS OF LEADING COMPANIES IN AI IN FINANCE MARKET (FINANCE AS BUSINESS FUNCTIONS), 2023
  • FIGURE 49 SHARE ANALYSIS OF LEADING COMPANIES IN AI IN FINANCE MARKET (FINANCE AS BUSINESS OPERATIONS), 2023
  • FIGURE 50 PRODUCT COMPARATIVE ANALYSIS (FINANCE AS BUSINESS FUNCTIONS)
  • FIGURE 51 PRODUCT COMPARATIVE ANALYSIS (FINANCE AS BUSINESS OPERATIONS)
  • FIGURE 52 COMPANY VALUATION AND FINANCIAL METRICS OF KEY VENDORS
  • FIGURE 53 YEAR-TO-DATE (YTD) PRICE TOTAL RETURN AND 5-YEAR STOCK BETA OF KEY VENDORS
  • FIGURE 54 AI IN FINANCE MARKET: COMPANY EVALUATION MATRIX (KEY PLAYERS, FINANCE AS BUSINESS FUNCTIONS), 2023
  • FIGURE 55 AI IN FINANCE MARKET: COMPANY EVALUATION MATRIX (KEY PLAYERS, FINANCE AS BUSINESS OPERATIONS), 2023
  • FIGURE 56 AI IN FINANCE MARKET: COMPANY FOOTPRINT (1/2)
  • FIGURE 57 AI IN FINANCE MARKET: COMPANY FOOTPRINT (2/2)
  • FIGURE 58 AI IN FINANCE MARKET: COMPANY EVALUATION MATRIX (START-UPS/SMES, FINANCE AS BUSINESS OPERATIONS), 2023
  • FIGURE 59 AI IN FINANCE MARKET: COMPANY EVALUATION MATRIX (START-UPS/SMES, FINANCE AS BUSINESS FUNCTIONS), 2023
  • FIGURE 60 FIS: COMPANY SNAPSHOT
  • FIGURE 61 FISERV: COMPANY SNAPSHOT
  • FIGURE 62 GOOGLE: COMPANY SNAPSHOT
  • FIGURE 63 MICROSOFT: COMPANY SNAPSHOT
  • FIGURE 64 IBM: COMPANY SNAPSHOT
  • FIGURE 65 WORKIVA: COMPANY SNAPSHOT
  • FIGURE 66 C3 AI: COMPANY SNAPSHOT

The study involved major activities in estimating the current market size for the AI in Finance market. Exhaustive secondary research was done to collect information on the AI in Finance market. The next step was to validate these findings, assumptions, and sizing with industry experts across the value chain using primary research. Different approaches, such as top-down and bottom-up, were employed to estimate the total market size. After that, the market breakup and data triangulation procedures were used to estimate the market size of the segments and subsegments of the AI in Finance market.

Secondary Research

The market for the companies offering AI in Finance solutions is arrived at by secondary data available through paid and unpaid sources, analyzing the product portfolios of the major companies in the ecosystem, and rating the companies by their performance and quality. Various sources were referred to in the secondary research process to identify and collect information for this study. The secondary sources include annual reports, press releases, investor presentations of companies, white papers, journals, certified publications, and articles from recognized authors, directories, and databases.

In the secondary research process, various secondary sources were referred to for identifying and collecting information related to the study. Secondary sources included annual reports, press releases, and investor presentations of AI in Finance vendors, forums, certified publications, and whitepapers. The secondary research was used to obtain critical information on the industry’s value chain, the total pool of key players, market classification, and segmentation from the market and technology-oriented perspectives.

Primary Research

In the primary research process, various primary sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information for this report. The primary sources from the supply side included industry experts, such as Chief Executive Officers (CEOs), Vice Presidents (VPs), marketing directors, technology and innovation directors, and related key executives from various key companies and organizations operating in the AI in Finance market. After the complete market engineering (calculations for market statistics, market breakdown, market size estimations, market forecasting, and data triangulation), extensive primary research was conducted to gather information and verify and validate the critical numbers arrived at. Primary research was also conducted to identify the segmentation types, industry trends, competitive landscape of AI in Finance solutions offered by various market players, and key market dynamics, such as drivers, restraints, opportunities, challenges, industry trends, and key player strategies. In the complete market engineering process, the top-down and bottom-up approaches were extensively used, along with several data triangulation methods, to perform the market estimation and market forecasting for the overall market segments and subsegments listed in this report. Extensive qualitative and quantitative analysis was performed on the complete market engineering process to list the key information/insights throughout the report.

Al In Finance Market Size, and Share

Note: Tier 1 companies account for annual revenue of >USD 10 billion; tier 2 companies’ revenue ranges
between USD 1 and 10 billion; and tier 3 companies’ revenue ranges between USD 500 million–USD 1 billion

To know about the assumptions considered for the study, download the pdf brochure

Market Size Estimation

Both top-down and bottom-up approaches were used to estimate and validate the total size of the cell culture market. These methods were also used extensively to estimate the size of various subsegments in the market. The research methodology used to estimate the market size includes the following:

AI In Finance Market : Top-Down and Bottom-Up Approach

Al In Finance Market Top Down and Bottom Up Approach

Data Triangulation

After arriving at the overall market size using the market size estimation processes explained above, the market was split into various segments and subsegments. The data triangulation and market breakup procedures were employed, wherever applicable, to complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment. The data was triangulated by studying various factors and trends from both the demand and supply sides.

Market Definition

Artificial intelligence (AI) in finance helps drive insights for data analytics, performance measurement, predictions and forecasting, real-time calculations, customer servicing, intelligent data retrieval, and more. It is a set of technologies that enables financial services organizations to better understand markets and customers, analyze and learn from digital journeys, and engage in a way that mimics human intelligence and interactions at scale.

Stakeholders

  • Risk Assessment and Compliance Software Developers
  • AI in Finance Software Vendors
  • Financial Analysts and Managers
  • AI in Finance Service Providers
  • Financial Marketers
  • Business Owners and Executives
  • Distributors and Value-Added Resellers (VARs)
  • Independent Software Vendors (ISVs)
  • Managed Service Providers
  • Support and Maintenance Service Providers
  • System Integrators (SIs)/Migration Service Providers
  • Original Equipment Manufacturers (OEMs)
  • Technology Providers

Report Objectives

  • To define, describe, and predict the AI in Finance market by product (by type and deployment mode), technology, application (by business operation and business function), end user (by business function and business operation) and region
  • To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
  • To analyze the micro markets with respect to individual growth trends, prospects, and their contributions to the total market
  • To analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the AI in Finance market
  • To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
  • To forecast the market size of five main regions: North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America
  • To profile key players and comprehensively analyze their market rankings and core competencies
  • To analyze competitive developments, such as partnerships, new product launches, and mergers & acquisitions, in the market
  • To analyze the impact of the recession across all regions in the AI in Finance market

Available Customizations

With the given market data, MarketsandMarkets offers customizations as per your company’s specific needs. The following customization options are available for the report:

Product Analysis

  • Product quadrant, which gives a detailed comparison of the product portfolio of each company.

Geographic Analysis as per Feasibility

  • Further breakup of the North American AI in Finance market
  • Further breakup of the European market
  • Further breakup of the Asia Pacific market
  • Further breakup of the Middle Eastern & African market
  • Further breakup of the Latin America AI in Finance market

Company Information

  • Detailed analysis and profiling of additional market players (up to five)

 

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