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

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USD 190.33 BN
MARKET SIZE, 2030
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CAGR 30.6%
(2025-2030)
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399
REPORT PAGES
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338
MARKET TABLES

OVERVIEW

AI in Finance Market Overview

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

The 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%, driven by the sector’s shift toward AI-first operating models. Financial institutions are adopting cloud-native AI platforms, generative AI, and real-time analytics to modernize legacy systems, reduce costs, and deliver personalized services. Vendors like NVIDIA, Google Cloud, Microsoft, and AWS are enabling this transformation through industry-specific AI stacks and co-innovation programs. Key use cases include fraud detection, risk scoring, portfolio optimization, and AI-powered customer engagement. As over 80% of firms plan to increase AI investments, strategic priorities include building explainable AI (XAI) frameworks, enhancing model governance, and integrating predictive and generative AI to drive operational efficiency and innovation.

KEY TAKEAWAYS

  • North America dominates the AI in Finance Market by 35.3% market share in 2024.
  • By product, the compliance automation platforms segment is projected to have the fastest growth rate of 35.7%, during the forecast period.
  • By technology, the other AI technologies segment is expected to dominate the market, with share of 91.4% in 2024.
  • By application, the customer service & engagement segment is projected to have the highest CAGR, during the forecast period.
  • By end user, the Retail & E-commerce segment is expected to dominate the market during the forecast period.
  • Microsoft, Google and IBM are identified as some of the star players in the AI in Finance market, given their strong market share and product footprint.
  • DataRails, DataVisor and InData Labs, among others, have distinguished themselves among startups and SMEs by securing strong footholds in specialized niche areas, underscoring their potential as emerging leaders.

The AI in Finance market is rapidly transforming as institutions adopt AI for fraud detection, credit scoring, compliance automation, and algorithmic trading. The rise of robo-advisors, predictive analytics, and sentiment analysis is reshaping investment strategies. Key drivers include generative AI for portfolio optimization, machine learning and NLP for RegTech, and the expansion of digital banking. Vendors like Google Cloud, Microsoft, AWS, and NVIDIA are investing in financial-grade AI platforms, making AI central to modern banking, asset management, and financial services innovation.

TRENDS & DISRUPTIONS IMPACTING CUSTOMERS' CUSTOMERS

The AI in finance market is undergoing a significant transformation as businesses increasingly rely on AI-driven insights for decision-making and strategic planning. This evolution is primarily driven by the demand for real-time analytics, personalized user experiences, and tailored solutions that address the unique needs of various financial services. Clients in the AI finance sector span a range of industries, including banking, investment, and insurance. They utilize AI tools to optimize risk assessment, fraud detection, and customer service. By harnessing the power of AI, these clients aim to enhance operational efficiency, improve client engagement, and gain a competitive edge. Financial institutions depend on AI to analyze vast amounts of transactional data, predict market trends, and provide personalized investment recommendations that align with individual client goals. Businesses require real-time data to make agile decisions and quickly adapt to shifts in market dynamics. AI solutions enable firms to monitor financial transactions, derive insights from customer interactions, and enhance service delivery. With the increasing volume of user-generated content, privacy and data security are critical concerns in finance.

AI in Finance Market Disruptions

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

MARKET DYNAMICS

Drivers
Impact
Level
  • Rising demand for AI-powered financial forecasting to support strategic planning, portfolio optimization, and investment agility
  • Accelerated adoption of machine learning for risk analytics, enabling real-time fraud detection, credit scoring, and compliance automation
RESTRAINTS
Impact
Level
  • Lack of model transparency and explainability in AI systems, leading to trust deficits and regulatory scrutiny
OPPORTUNITIES
Impact
Level
  • Surge in demand for hyper-personalized financial products driven by AI-based customer segmentation, behavioral analytics, and dynamic pricing engines
  • Enhanced credit risk modeling and financial accuracy through AI-driven underwriting and alternative data utilization
CHALLENGES
Impact
Level
  • Persistent risks of algorithmic bias and ethical concerns in automated financial decision-making, impacting fairness and inclusivity

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

Driver: Rising demand for AI-powered financial forecasting to support strategic planning, portfolio optimization, and investment agility

Financial institutions and fintech adopters are accelerating AI integration to enable accurate predictive analytics, supporting strategic investment planning and portfolio optimization in volatile markets. This demand is driven by the need to anticipate economic shifts and maximize returns. Indeed, predictive analytics for strategic planning is a top priority, with vendors like JP Morgan, Salesforce, and Affirm emphasizing AI's pivotal role in forecasting, portfolio optimization, and real-time decision support. AI is increasingly utilized to anticipate economic shifts, automate complex financial modeling, and enhance overall investment strategies. These advanced AI algorithms provide real-time insights, empowering financial decision-makers to make data-driven decisions, thereby positioning firms ahead in competitive AI finance trends.

Restraint: Lack of model transparency and explainability in AI systems, leading to trust deficits and regulatory scrutiny

A key restraint is the lack of transparency in financial AI models, which undermines trust in AI-driven decision-making and complicates regulatory compliance. This opacity is a widely acknowledged issue that creates challenges in auditing AI processes, increases scrutiny from regulators, and slows deployment. Consequently, vendors and regulators stress the need for Explainable AI (XAI) to ensure trust, auditability, and full regulatory compliance. Industry stakeholders are actively seeking clearer explanations of model outputs to align with rigorous governance standards in the evolving AI risk management landscape.

Opportunity: Surge in demand for hyper-personalized financial products driven by AI-based customer segmentation, behavioral analytics, and dynamic pricing engines

Financial service providers are increasingly investing in personalized banking AI solutions to foster long-term customer engagement through hyper-customized financial products and enhanced user experiences. Hyper-personalization is a major growth area, with vendors deploying AI to deliver tailored financial products, personalized investment advice, and dynamic pricing. Institutions are leveraging AI to analyze customer data, offer tailored loan products, and improve loyalty programs, driving growth by meeting the rising demand for individualized services in a competitive market.

Challenge: Persistent risks of algorithmic bias and ethical concerns in automated financial decision-making, impacting fairness and inclusivity

AI adopters in finance face significant challenges with algorithmic bias, which can lead to unfair outcomes such as skewed credit approvals or investment recommendations. Addressing this requires robust bias mitigation strategies, including advanced detection tools and diverse datasets, to ensure fairness, protect reputation, and maintain compliance with global regulatory frameworks in ethical fintech AI adoption.

AI in Finance Market: COMMERCIAL USE CASES ACROSS INDUSTRIES

COMPANY USE CASE DESCRIPTION BENEFITS
H2O.ai provided PayPal with a solution utilizing H2O Driverless AI, which enhanced fraud detection capabilities. By combining advanced ML with graph database techniques, PayPal was able to identify complex fraud patterns, such as collusion among buyers and sellers. Improved fraud detection model accuracy by ~6%, strengthening PayPal’s fraud prevention capabilities and reducing financial exposure.
Vena Solutions provided Shift4 Payments with a comprehensive financial planning platform that transformed their reporting and planning processes. By automating data flows from Shift4’s Oracle ERP Suite into a central database, Vena enabled the finance team to streamline monthly reporting and enhance flexibility in planning. Supported scalable financial planning, enhancing adaptability to business growth and dynamic market conditions.
Investa implemented Workiva's cloud-based platform, which facilitated real-time data collaboration and streamlined the reporting process. This transformation allowed Investa to produce timely and reliable reports, improving efficiency and reducing the workload for its finance team. Boosted operational efficiency by automating workflows, allowing finance teams to focus on strategic analysis and decision-making.
DataVisor and Microsoft azure collaborate to enhance real-time fraud detection. This architecture supports both public and private Azure deployments, ensuring comprehensive protection against sophisticated attacks. Achieved 35%+ uplift in threat detection, enabling proactive fraud prevention and minimizing financial losses.

Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.

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.

AI in Finance Market Ecosystem

Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.

MARKET SEGMENTS

AI in Finance Market Segments

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

AI in finance Market, By Product Type

The compliance automation platforms segment is emerging as the fastest-growing product category in the AI in finance market. This growth is driven by intensifying regulatory scrutiny and the increasing complexity of financial compliance obligations. AI-enabled platforms are transforming how institutions manage anti-money laundering (AML) checks, Know Your Customer (KYC) verification, transaction monitoring, and audit trails—delivering higher accuracy and operational efficiency. The surge in RegTech adoption, integration with real-time risk management systems, and the need for scalable, regulation-ready frameworks are fueling strong demand for AI-based compliance automation across banking, insurance, and capital markets.

AI in finance Market, By Deployment Mode

While cloud deployment continues to dominate the AI in finance landscape, on-premises AI systems are witnessing accelerated growth in high-security financial environments. Institutions such as investment banks, central banks, and trading firms are increasingly adopting on-prem AI for use cases like algorithmic trading, fraud detection, and risk analytics—where ultra-low latency, data sovereignty, and maximum security are non-negotiable. Rising concerns around cybersecurity, regulatory mandates for data localization, and the need for proprietary control over AI infrastructure are driving this shift. Vendors are responding by offering modular, high-performance AI stacks tailored for sensitive financial operations.

AI in finance Market, By Use Case (Business Operations Applications)

Customer service and engagement applications are experiencing rapid growth, fueled by the expansion of digital banking platforms and omni-channel financial services. AI-driven tools such as chatbots, virtual assistants, and sentiment analysis engines are enabling hyper-personalized customer interactions, proactive issue resolution, and real-time financial guidance. The rise of conversational AI, integration of generative AI for client onboarding, and a growing emphasis on frictionless customer journeys are reshaping how financial institutions engage with clients. Enhanced customer experience is becoming a strategic lever for retention, cross-selling, and differentiation in highly competitive markets.

AI in finance Market, By End User (Business Function)

The healthcare and pharma sector is emerging as a high-growth vertical for AI in finance, driven by the adoption of AI-powered financial solutions for healthcare payments, claims management, and insurance underwriting. Pharmaceutical firms are leveraging AI for credit risk scoring, supply chain financing, and compliance analytics to support global operations. The sector’s complex regulatory landscape, high transaction volumes, and increasing demand for secure, fraud-resistant payment systems make it a significant driver of AI adoption in finance. Vendors are targeting this space with tailored solutions for insurance-linked financing and digital health payment ecosystems.

REGION

Asia Pacific to be the fastest-growing region in the AI in finance Market during the forecast period

Asia Pacific is emerging as the fastest-growing region in the AI in Finance market, propelled by rapid adoption of digital payments, fintech innovation, and AI-driven financial infrastructure. Countries such as India, China, and Singapore are at the forefront of integrating AI into core financial functions including fraud detection, risk analytics, credit scoring, and wealth management. The region’s growth is further supported by government-backed fintech initiatives, rising mobile-first financial ecosystems, and increasing demand for secure, intelligent financial platforms. Asia Pacific’s momentum positions it as a global hub for AI innovation in financial services, with vendors actively investing in localized solutions to meet regulatory and market-specific needs.

AI in Finance Market Region

AI in Finance Market: COMPANY EVALUATION MATRIX

In the AI in finance market matrix, Fiserv (Star) leads with a strong market presence and a comprehensive suite of AI-driven financial capabilities, enabling large-scale adoption in areas such as fraud detection, real-time payments monitoring, credit risk assessment, and customer analytics. Brighterion (Emerging Leader) is gaining traction with its AI-powered anomaly detection, behavioral biometrics, and adaptive learning models, helping financial institutions strengthen compliance and reduce fraud in real time. While Fiserv dominates with scale, innovation, and enterprise-wide integration, Brighterion demonstrates strong growth potential, steadily advancing toward the star quadrant.

AI in Finance Market Evaluation Metrics

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

KEY MARKET PLAYERS

MARKET SCOPE

REPORT METRIC DETAILS
Market Size in 2024 (Value) USD 38.36 Billion
Market Forecast in 2030 USD 190.33 Billion
Growth Rate CAGR of 30.6% during 2024-2030
Years Considered 2019-2030
Base Year 2023
Forecast Period 2024-2030
Units Considered Value (USD Million)
Report Coverage Revenue forecast, company ranking, competitive landscape, growth factors, and trends
Segments Covered
  • Product - Type
  • Deployment Mode Product Type - ERP and Financial Systems
  • Chatbots & Virtual Assistants
  • Automated Reconciliation Solutions
  • Intelligent Document Processing
  • Governance, Risk, And Compliance (GRC) Software
  • Accounts Payable/Receivable Automation Software
  • Robo-Advisors
  • Expense Management Systems
  • Compliance Automation Platforms
  • Algorithmic Trading Platforms
  • Underwriting Engines/Platforms
  • Other Product Types Deployment Mode - Cloud
  • On-Premises Technology - Generative AI
  • Other AI Application - Finance as Business Operations
  • Finance as Business Functions Finance as Business Operations (Fraud Detection & Prevention
  • Risk Management
  • Customer Service & Engagement
  • Financial Compliance & Regulatory Reporting
  • Investment & Portfolio Management ) Finance as Business Functions (Financial Planning & Forecasting
  • Automated Bookkeeping & Reconciliation
  • Procurement & Supply Chain Finance
  • Revenue Cycle Management) End User - Finance as Business Operations
  • Finance as Business Functions Finance as Business Operations (Government & Public Sector
  • Retail & E-commerce
  • Real Estate
  • Manufacturing
  • Telecom & media
  • Healthcare & pharma
  • Utilities
  • Education
  • Technology & software
  • Other end users) Finance as Business Functions (Banking
  • Insurance
  • Investment & Asset Management
  • Fintech
  • Capital Markets/Regtech)
Regions Covered North America, Asia Pacific, Europe, the Middle East & Africa, and Latin America

WHAT IS IN IT FOR YOU: AI in Finance Market REPORT CONTENT GUIDE

AI in Finance Market Content Guide

DELIVERED CUSTOMIZATIONS

We have successfully delivered the following deep-dive customizations:

CLIENT REQUEST CUSTOMIZATION DELIVERED VALUE ADDS
Leading Solution Provider (US) Delivered competitive profiling of additional vendors, brand comparative analysis, and a drill-down of country-level segmentation across key markets. Enabled competitive positioning insights, product differentiation clarity, and multi-country market intelligence, supporting go-to-market strategy refinement and stakeholder alignment.
Leading Solution Provider (Europe) Provided competitive profiling, brand benchmarking, and segmentation analysis across additional geographies. Delivered in-depth market insights, comparative brand positioning, and segment-level intelligence, empowering strategic decision-making and regional growth planning.

RECENT DEVELOPMENTS

  • January 2025 : Unicaja and Fiserv entered a strategic partnership to enhance omnichannel payment processing in Spain, focusing on speed, security, and convenience. This marks Fiserv’s first major venture in the Spanish market, combining Unicaja’s financial reach with Fiserv’s technology to optimize merchant experiences across sectors. The initiative responds to rising demand for digital financial services and aims to strengthen e-commerce capabilities for Unicaja’s clientele.
  • January 2025 : Pearson and Microsoft launched a multi-year partnership to revolutionize education and workforce development using Azure Cloud and AI technologies. Key initiatives include personalized learning at scale, AI credentials, and the deployment of Microsoft 365 Copilot across Pearson platforms. The collaboration targets the global AI skills gap, focusing on reskilling and empowering learners for an AI-driven economy.
  • December 2024 : Fiserv acquired Payfare Inc. to strengthen its embedded finance capabilities, particularly for the gig economy. Payfare’s workforce payment solutions complement Fiserv’s existing offerings, enhancing technology and program management for efficient business payments. This move reflects Fiserv’s commitment to innovative financial services and opens new growth avenues in digital workforce payments.
  • November 2024 : FIS partnered with Oracle to modernize utility billing via the BillerIQ solution on Oracle Cloud Infrastructure (OCI). The integration supports electronic bill delivery and multi-channel payment options (ACH, cards, digital wallets), improving operational efficiency and customer satisfaction. This collaboration addresses legacy billing inefficiencies and advances digital transformation in essential services.
  • October 2024 : Google Pay partnered with Muthoot Finance to offer gold-backed loans, enhancing financial accessibility for users in India. This collaboration leverages digital wallet infrastructure to expand credit access and support inclusive finance through asset-backed lending.

Table of Contents

Exclusive indicates content/data unique to MarketsandMarkets and not available with any competitors.

TITLE
PAGE NO
INTRODUCTION
36
RESEARCH METHODOLOGY
41
EXECUTIVE SUMMARY
53
PREMIUM INSIGHTS
59
MARKET OVERVIEW AND INDUSTRY TRENDS (STRATEGIC DRIVERS WITH QUANTITATIVE IMPLICATIONS)
Unpacking the Forces Shaping AI in Finance Adoption & Future Growth Opportunities
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 (MARKET SIZE & FORECAST TO 2030 – IN VALUE (USD))
Detailed breakdown of market share and growth across AI in Finance product types
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 (MARKET SIZE & FORECAST TO 2030 – IN VALUE (USD))
Detailed breakdown of market share and growth across AI in Finance 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 (MARKET SIZE & FORECAST TO 2030 – IN VALUE (USD))
Detailed breakdown of market share and growth across AI in Finance 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 (MARKET SIZE & FORECAST TO 2030 – IN VALUE (USD))
Industry-specific market sizing, growth, and key trends
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 (MARKET SIZE & FORECAST TO 2030 – IN VALUE (USD))
Regional market sizing, forecasts, and regulatory landscapes
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
Strategic Profiles of Leading Players & Their Playbooks for Market Dominance
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
In-depth look at their Strengths, Weaknesses, Product Portfolios, Recent Developments, and Strategic Moves
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 MARKET SIZE AND GROWTH RATE, 2024–2030 (USD MILLION, Y-O-Y %)
  • TABLE 6 ROLE OF COMPANIES IN ECOSYSTEM
  • TABLE 7 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 MARKET: LIST OF PATENTS GRANTED, 2024–2025
  • TABLE 15 AVERAGE SELLING PRICE OF KEY PLAYERS FOR TOP 3 APPLICATIONS
  • TABLE 16 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 MARKET, BY PRODUCT, 2019–2023 (USD MILLION)
  • TABLE 21 MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 22 ERP & FINANCIAL SYSTEMS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 23 ERP & FINANCIAL SYSTEMS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 24 CHATBOTS & VIRTUAL ASSISTANTS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 25 CHATBOTS & VIRTUAL ASSISTANTS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 26 AUTOMATED RECONCILIATION SOLUTIONS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 27 AUTOMATED RECONCILIATION SOLUTIONS: 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: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 30 GOVERNANCE, RISK, AND COMPLIANCE (GRC)
    SOFTWARE: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 31 GOVERNANCE, RISK, AND COMPLIANCE (GRC)
    SOFTWARE: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 32 ACCOUNTS PAYABLE/RECEIVABLE AUTOMATION SOFTWARE: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 33 ACCOUNTS PAYABLE/RECEIVABLE AUTOMATION SOFTWARE: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 34 ROBO-ADVISORS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 35 ROBO-ADVISORS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 36 EXPENSE MANAGEMENT SYSTEMS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 37 EXPENSE MANAGEMENT SYSTEMS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 38 COMPLIANCE AUTOMATION PLATFORMS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 39 COMPLIANCE AUTOMATION PLATFORMS: 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: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 42 UNDERWRITING ENGINES/PLATFORMS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 43 UNDERWRITING ENGINES/PLATFORMS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 44 OTHER PRODUCT TYPES: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 45 OTHER PRODUCT TYPES: MARKET, BY REGION,2024–2030 (USD MILLION)
  • TABLE 46 MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 47 MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 48 CLOUD: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 49 CLOUD: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 50 ON-PREMISES: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 51 ON-PREMISES: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 52 MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 53 MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 54 GENERATIVE AI: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 55 GENERATIVE AI: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 56 OTHER AI: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 57 OTHER AI: 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 MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 60 FRAUD DETECTION & PREVENTION: MARKET, BY REGION,2019–2023 (USD MILLION)
  • TABLE 61 FRAUD DETECTION & PREVENTION: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 62 RISK MANAGEMENT: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 63 RISK MANAGEMENT: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 64 CUSTOMER SERVICE & ENGAGEMENT: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 65 CUSTOMER SERVICE & ENGAGEMENT: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 66 FINANCIAL COMPLIANCE & REGULATORY REPORTING: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 67 FINANCIAL COMPLIANCE & REGULATORY REPORTING: 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: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 70 MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 71 MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 72 FINANCIAL PLANNING & FORECASTING: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 73 FINANCIAL PLANNING & FORECASTING: MARKET BY REGION, 2024–2030 (USD MILLION)
  • TABLE 74 AUTOMATED BOOKKEEPING & RECONCILIATION: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 75 AUTOMATED BOOKKEEPING & RECONCILIATION: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 76 PROCUREMENT & SUPPLY CHAIN FINANCE: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 77 PROCUREMENT & SUPPLY CHAIN FINANCE: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 78 REVENUE CYCLE MANAGEMENT: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 79 REVENUE CYCLE MANAGEMENT: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 80 AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 81 MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 82 FINANCE AS BUSINESS FUNCTIONS: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 83 FINANCE AS BUSINESS FUNCTIONS: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 84 FINANCE AS BUSINESS FUNCTIONS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 85 FINANCE AS BUSINESS FUNCTIONS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 86 GOVERNMENT & PUBLIC SECTOR: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 87 GOVERNMENT & PUBLIC SECTOR: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 88 RETAIL & E-COMMERCE: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 89 RETAIL & E-COMMERCE: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 90 REAL ESTATE: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 91 REAL ESTATE: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 92 MANUFACTURING: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 93 MANUFACTURING: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 94 TELECOM & MEDIA: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 95 TELECOM & MEDIA: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 96 HEALTHCARE & PHARMA: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 97 HEALTHCARE & PHARMA: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 98 UTILITIES: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 99 UTILITIES: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 100 EDUCATION: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 101 EDUCATION: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 102 TECHNOLOGY & SOFTWARE: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 103 TECHNOLOGY & SOFTWARE: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 104 OTHER END USERS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 105 OTHER END USERS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 106 FINANCE AS BUSINESS OPERATIONS: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 107 FINANCE AS BUSINESS OPERATIONS: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 108 FINANCE AS BUSINESS OPERATIONS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 109 FINANCE AS BUSINESS OPERATIONS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 110 BANKING: AI IN FINANCE MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 111 BANKING: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 112 INSURANCE: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 113 INSURANCE: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 114 INVESTMENT & ASSET MANAGEMENT: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 115 INVESTMENT & ASSET MANAGEMENT: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 116 FINTECH: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 117 FINTECH: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 118 CAPITAL MARKETS/REGTECH: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 119 CAPITAL MARKETS/REGTECH: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 120 MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 121 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: MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 124 NORTH AMERICA: MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 125 NORTH AMERICA: MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 126 NORTH AMERICA: MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 127 NORTH AMERICA: MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 128 NORTH AMERICA: MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 129 NORTH AMERICA: MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 130 NORTH AMERICA: 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: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 133 NORTH AMERICA: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 134 NORTH AMERICA: MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 135 NORTH AMERICA: MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 136 NORTH AMERICA: MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 137 NORTH AMERICA: MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 138 NORTH AMERICA: MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 139 NORTH AMERICA: MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 140 US: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 141 US: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 142 CANADA: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 143 CANADA: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 144 EUROPE: MARKET, BY PRODUCT, 2019–2023 (USD MILLION)
  • TABLE 145 EUROPE: MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 146 EUROPE: MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 147 EUROPE: MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 148 EUROPE: MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 149 EUROPE: MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 150 EUROPE: MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 151 EUROPE: 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: MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 154 EUROPE: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 155 EUROPE: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 156 EUROPE: MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 157 EUROPE: MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 158 EUROPE: MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 159 EUROPE: MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 160 EUROPE: MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 161 EUROPE: MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 162 UK: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 163 UK: 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: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 166 FRANCE: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 167 FRANCE: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 168 ITALY: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 169 ITALY: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 170 SPAIN: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 171 SPAIN: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 172 REST OF EUROPE: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 173 REST OF EUROPE: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 174 ASIA PACIFIC: AI IN FINANCE ARKET, BY PRODUCT, 2019–2023 (USD MILLION)
  • TABLE 175 ASIA PACIFIC: MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 176 ASIA PACIFIC: MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 177 ASIA PACIFIC: MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 178 ASIA PACIFIC: MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 179 ASIA PACIFIC: MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 180 ASIA PACIFIC: MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 181 ASIA PACIFIC: MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 182 ASIA PACIFIC: 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: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 185 ASIA PACIFIC: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 186 ASIA PACIFIC: MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 187 ASIA PACIFIC: MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 188 ASIA PACIFIC: MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 189 ASIA PACIFIC: MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 190 ASIA PACIFIC: MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 191 ASIA PACIFIC: MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 192 CHINA: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 193 CHINA: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 194 JAPAN: 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: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 197 INDIA: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 198 SOUTH KOREA: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 199 SOUTH KOREA: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 200 AUSTRALIA & NEW ZEALAND: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 201 AUSTRALIA & NEW ZEALAND: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 202 ASEAN: MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 203 ASEAN: MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 204 ASEAN: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 205 ASEAN: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 206 REST OF ASIA PACIFIC: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 207 REST OF ASIA PACIFIC: 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: MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 210 MIDDLE EAST & AFRICA: MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 211 MIDDLE EAST & AFRICA: MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 212 MIDDLE EAST & AFRICA: MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 213 MIDDLE EAST & AFRICA: MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 214 MIDDLE EAST & AFRICA: MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 215 MIDDLE EAST & AFRICA: MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 216 MIDDLE EAST & AFRICA: MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 217 MIDDLE EAST & AFRICA: 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: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 220 MIDDLE EAST & AFRICA: MARKET, BY END USER(FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 221 MIDDLE EAST & AFRICA: MARKET, BY END USER(FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 222 MIDDLE EAST & AFRICA: MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 223 MIDDLE EAST & AFRICA: MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 224 MIDDLE EAST & AFRICA: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 225 MIDDLE EAST & AFRICA: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 226 MIDDLE EAST: MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 227 MIDDLE EAST: MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 228 KSA: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 229 KSA: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 230 UAE: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 231 UAE: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 232 KUWAIT: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 233 KUWAIT: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 234 BAHRAIN: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 235 BAHRAIN: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 236 AFRICA: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 237 AFRICA: 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: MARKET, BY PRODUCT, 2024–2030 (USD MILLION)
  • TABLE 240 LATIN AMERICA: MARKET, BY DEPLOYMENT MODE, 2019–2023 (USD MILLION)
  • TABLE 241 LATIN AMERICA: MARKET, BY DEPLOYMENT MODE, 2024–2030 (USD MILLION)
  • TABLE 242 LATIN AMERICA: MARKET, BY TECHNOLOGY, 2019–2023 (USD MILLION)
  • TABLE 243 LATIN AMERICA: MARKET, BY TECHNOLOGY, 2024–2030 (USD MILLION)
  • TABLE 244 LATIN AMERICA: MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 245 LATIN AMERICA: MARKET, BY APPLICATION (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 246 LATIN AMERICA: MARKET, BY APPLICATION (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 247 LATIN AMERICA: 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: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 250 LATIN AMERICA: MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2019–2023 (USD MILLION)
  • TABLE 251 LATIN AMERICA: MARKET, BY END USER (FINANCE AS BUSINESS FUNCTIONS), 2024–2030 (USD MILLION)
  • TABLE 252 LATIN AMERICA: MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2019–2023 (USD MILLION)
  • TABLE 253 LATIN AMERICA: MARKET, BY END USER (FINANCE AS BUSINESS OPERATIONS), 2024–2030 (USD MILLION)
  • TABLE 254 LATIN AMERICA: MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 255 LATIN AMERICA: MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 256 BRAZIL: AI IN FINANCE MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 257 BRAZIL: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 258 MEXICO: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 259 MEXICO: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 260 ARGENTINA: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 261 ARGENTINA: MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 262 REST OF LATIN AMERICA: MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 263 REST OF LATIN AMERICA: 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 MARKET (FINANCE AS BUSINESS FUNCTIONS): DEGREE OF COMPETITION, 2023
  • TABLE 266 MARKET (FINANCE AS BUSINESS OPERATIONS):DEGREE OF COMPETITION, 2023
  • TABLE 267 MARKET: REGION FOOTPRINT
  • TABLE 268 MARKET: PRODUCT FOOTPRINT
  • TABLE 269 MARKET: APPLICATION FOOTPRINT (BUSINESS OPERATIONS)
  • TABLE 270 MARKET: END-USER FOOTPRINT (BUSINESS OPERATIONS)
  • TABLE 271 MARKET: DETAILED LIST OF KEY START-UPS/SMES
  • TABLE 272 MARKET: COMPETITIVE BENCHMARKING OF START-UPS/SMES
  • TABLE 273 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 MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES
  • FIGURE 4 APPROACH 1, BOTTOM-UP (SUPPLY-SIDE): REVENUE FROM SOFTWARE/SERVICES OF MARKET
  • FIGURE 5 APPROACH 2, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL SOFTWARE/SERVICES OF MARKET
  • FIGURE 6 APPROACH 3, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL PRODUCTS OF MARKET
  • FIGURE 7 APPROACH 4, BOTTOM-UP (DEMAND-SIDE): SHARE OF 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 LARGESTMARKET 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 MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
  • FIGURE 22 EVOLUTION OF MARKET
  • FIGURE 23 AI IN FINANCE MARKET: SUPPLY CHAIN ANALYSIS
  • FIGURE 24 MARKET: ECOSYSTEM
  • FIGURE 25 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 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 AI IN FINANCE 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: MARKET SNAPSHOT
  • FIGURE 45 ASIA PACIFIC: MARKET SNAPSHOT
  • FIGURE 46 AI IN FINANCE MARKET: REVENUE ANALYSIS OF FIVE KEY PLAYERS (FINANCE AS BUSINESS FUNCTIONS), 2019–2023
  • FIGURE 47 MARKET: REVENUE ANALYSIS OF FIVE KEY PLAYERS (FINANCE AS BUSINESS OPERATIONS), 2019–2023
  • FIGURE 48 SHARE ANALYSIS OF LEADING COMPANIES IN MARKET (FINANCE AS BUSINESS FUNCTIONS), 2023
  • FIGURE 49 SHARE ANALYSIS OF LEADING COMPANIES IN 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 MARKET: COMPANY EVALUATION MATRIX (KEY PLAYERS, FINANCE AS BUSINESS FUNCTIONS), 2023
  • FIGURE 55 MARKET: COMPANY EVALUATION MATRIX (KEY PLAYERS, FINANCE AS BUSINESS OPERATIONS), 2023
  • FIGURE 56 MARKET: COMPANY FOOTPRINT (1/2)
  • FIGURE 57 MARKET: COMPANY FOOTPRINT (2/2)
  • FIGURE 58 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

 

Methodology

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)

 

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.

TABLE OF CONTENTS

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