AI in Finance Market Size, Share, Industry, overview, Growth, Latest Trends
Report Code
TC 9214
Published in
Feb, 2025, By MarketsandMarkets™
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
USD 190.33 BN
MARKET SIZE, 2030
CAGR 30.6%
(2025-2030)
399
REPORT PAGES
338
MARKET TABLES
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.
Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis
MARKET DYNAMICS
Drivers
Impact
Level
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
Level
-
Lack of model transparency and explainability in AI systems, leading to trust deficits and regulatory scrutiny
OPPORTUNITIES
Impact
Level
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
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.
Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.
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: 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.
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 |
|
| 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
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
1
INTRODUCTION
36
2
RESEARCH METHODOLOGY
41
3
EXECUTIVE SUMMARY
53
4
PREMIUM INSIGHTS
59
5
MARKET OVERVIEW AND INDUSTRY TRENDS
AI-driven personalized financial services reshape strategic planning and risk management in evolving finance market.
62
5.1
INTRODUCTION
5.2
MARKET DYNAMICS
5.2.1
DRIVERS
5.2.1.1
INCREASING DEMAND FOR PRECISE FORECASTS FOR STRATEGIC PLANNING AND INVESTMENT
5.2.1.2
GROWING ADOPTION OF AI ALGORITHMS TO ENHANCE RISK DETECTION AND MITIGATION
5.2.1.3
RISING POPULARITY OF PERSONALIZED FINANCIAL SERVICES
5.2.2
RESTRAINTS
5.2.2.1
OPACITIES IN FINANCIAL AI MODELS
5.2.3
OPPORTUNITIES
5.2.3.1
GROWING NEED FOR HYPER-PERSONALIZED FINANCIAL PRODUCTS FOR LONG-TERM CUSTOMER ENGAGEMENT AND TAILORED SERVICES
5.2.3.2
RISING DEMAND FOR ACCURATE CREDIT SCORING AND BETTER RISK MANAGEMENT
5.2.4
CHALLENGES
5.2.4.1
ALGORITHMIC BIAS IN FINANCIAL DECISION-MAKING
5.3
EVOLUTION OF AI IN FINANCE MARKET
5.4
SUPPLY CHAIN ANALYSIS
5.5
ECOSYSTEM
5.5.1
ERP & FINANCIAL SYSTEMS
5.5.2
CHATBOT AND VIRTUAL ASSISTANTS
5.5.3
AUTOMATED RECONCILIATION SYSTEMS
5.5.4
INTELLIGENT DOCUMENT PROCESSING
5.5.5
GOVERNMENT, RISK AND COMPLIANCE SOFTWARE
5.5.6
ACCOUNTS PAYABLE/RECEIVABLE AUTOMATION SOFTWARE
5.5.7
ROBO-ADVISORS
5.5.8
EXPENSE MANAGEMENT SYSTEMS
5.5.9
COMPLIANCE AUTOMATION PLATFORMS
5.5.10
ALGORITHMIC TRADING PLATFORMS
5.5.11
UNDERWRITING ENGINES/PLATFORMS
5.5.12
END USERS
5.6
CASE STUDY ANALYSIS
5.6.1
PAYPAL ENHANCES FRAUD DETECTION CAPABILITIES WITH H2O.AI'S DRIVERLESS AI SOLUTION
5.6.2
VENA SOLUTIONS TRANSFORMING FINANCIAL REPORTING AND PLANNING AT SHIFT4 PAYMENTS
5.6.3
INVESTA ENHANCES FUND REPORTING EFFICIENCY WITH WORKIVA’S STREAMLINED SOLUTIONS
5.6.4
DATAVISOR AND MICROSOFT AZURE COLLABORATE TO ENHANCE REAL-TIME FRAUD DETECTION
5.6.5
ZOHO EMPOWERS PLENTI WITH UNIFIED CRM SOLUTION TO ENHANCE CUSTOMER ENGAGEMENT AND OPERATIONAL EFFICIENCY
5.7
TECHNOLOGY ANALYSIS
5.7.1
KEY TECHNOLOGIES
5.7.1.1
NLP & DEEP LEARNING
5.7.1.2
COMPUTER VISION
5.7.1.3
PREDICTIVE ANALYTICS
5.7.1.4
ROBOTIC PROCESS AUTOMATION (RPA)
5.7.1.5
REINFORCEMENT LEARNING
5.7.1.6
EXPLAINABLE AI (XAI)
5.7.1.7
ANOMALY DETECTION
5.7.2
ADJACENT TECHNOLOGIES
5.7.2.1
CYBERSECURITY
5.7.2.2
IOT
5.7.2.3
AR/VR
5.7.2.4
DIGITAL IDENTITY VERIFICATION
5.7.3
COMPLEMENTARY TECHNOLOGIES
5.7.3.1
CLOUD COMPUTING
5.7.3.2
EDGE COMPUTING
5.7.3.3
QUANTUM COMPUTING
5.7.3.4
BIG DATA ANALYTICS
5.7.3.5
BLOCKCHAIN
5.8
KEY CONFERENCES AND EVENTS, 2025–2026
5.9
INVESTMENT AND FUNDING SCENARIO
5.10
REGULATORY LANDSCAPE
5.10.1
REGULATORY BODIES, GOVERNMENT AGENCIES, FRAMEWORKS, AND OTHER ORGANIZATIONS
5.10.2
REGULATORY LANDSCAPE, BY REGION
5.10.2.1
NORTH AMERICA
5.10.2.1.1
US
5.10.2.1.2
CANADA
5.10.2.2
EUROPE
5.10.2.2.1
EU
5.10.2.2.2
UK
5.10.2.3
ASIA PACIFIC
5.10.2.3.1
SINGAPORE
5.10.2.3.2
HONG KONG
5.10.2.3.3
CHINA
5.10.2.3.4
SOUTH KOREA
5.10.2.3.5
TAIWAN
5.10.2.4
MIDDLE EAST & AFRICA
5.10.2.4.1
UAE
5.10.2.4.2
SOUTH AFRICA
5.10.2.4.3
ISRAEL
5.10.2.4.4
SAUDI ARABIA
5.10.2.5
LATIN AMERICA
5.10.2.5.1
BRAZIL
5.10.2.5.2
MEXICO
5.10.2.5.3
CHILE
5.11
PATENT ANALYSIS
5.11.1
METHODOLOGY
5.11.2
PATENTS FILED, BY DOCUMENT TYPE
5.11.3
INNOVATIONS AND PATENT APPLICATIONS
5.12
PRICING ANALYSIS
5.12.1
AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY APPLICATION
5.12.2
INDICATIVE PRICING ANALYSIS, BY PRODUCT TYPE
5.13
PORTER’S FIVE FORCES ANALYSIS
5.13.1
THREAT OF NEW ENTRANTS
5.13.2
THREAT OF SUBSTITUTES
5.13.3
BARGAINING POWER OF SUPPLIERS
5.13.4
BARGAINING POWER OF BUYERS
5.13.5
INTENSITY OF COMPETITIVE RIVALRY
5.14
TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
5.15
KEY STAKEHOLDERS AND BUYING CRITERIA
5.15.1
KEY STAKEHOLDERS IN BUYING PROCESS
5.15.2
BUYING CRITERIA
5.16
IMPACT OF GENERATIVE AI ON AI IN FINANCE MARKET
5.16.1
TOP USE CASES & MARKET POTENTIAL
5.16.1.1
KEY USE CASES
5.16.2
AUTOMATED FINANCIAL REPORTING
5.16.3
ENHANCED RISK MANAGEMENT
5.16.4
PERSONALIZED FINANCIAL SERVICES
5.16.5
STREAMLINED CUSTOMER INTERACTIONS
5.16.6
FRAUD DETECTION AND COMPLIANCE
5.16.7
INNOVATIVE FINANCIAL PLANNING
6
AI IN FINANCE MARKET, BY PRODUCT
Market Size & Growth Rate Forecast Analysis to 2030 in USD Million | 32 Data Tables
108
6.1
INTRODUCTION
6.1.1
PRODUCT: AI IN FINANCE MARKET DRIVERS
6.2
TYPE
6.2.1
ERP AND FINANCIAL SYSTEMS
6.2.1.1
REAL-TIME ANALYTICS AND AUTOMATED REPORTING FOR IMPROVED FINANCIAL MANAGEMENT
6.2.2
CHATBOTS & VIRTUAL ASSISTANTS
6.2.2.1
ENHANCING OPERATIONAL EFFICIENCY AND CUSTOMER ENGAGEMENT IN FINANCIAL SERVICES
6.2.3
AUTOMATED RECONCILIATION SOLUTIONS
6.2.3.1
BOOSTING OPERATIONAL AGILITY FOR SWIFT TRANSACTION PROCESSING
6.2.4
INTELLIGENT DOCUMENT PROCESSING
6.2.4.1
REDUCING MANUAL ERRORS, ENABLING QUICK DECISION-MAKING, AND ACCELERATING PROCESSING TIME
6.2.5
GOVERNANCE, RISK, AND COMPLIANCE (GRC) SOFTWARE
6.2.5.1
FACILITATING SEAMLESS COLLABORATION ACROSS DEPARTMENTS
6.2.6
ACCOUNTS PAYABLE/RECEIVABLE AUTOMATION SOFTWARE
6.2.6.1
PROVIDING REAL-TIME INSIGHTS FOR INFORMED FINANCIAL DECISIONS
6.2.7
ROBO-ADVISORS
6.2.7.1
PROVIDING AUTOMATED INVESTMENT MANAGEMENT AND FINANCIAL ADVISORY SERVICES
6.2.8
EXPENSE MANAGEMENT SYSTEMS
6.2.8.1
STREAMLINING FINANCIAL OPERATIONS AND CONTROLLING COSTS
6.2.9
COMPLIANCE AUTOMATION PLATFORMS
6.2.9.1
IDENTIFYING COMPLIANCE RISKS AND ENABLING REAL-TIME ALERTS
6.2.10
ALGORITHMIC TRADING PLATFORMS
6.2.10.1
AUTOMATING TRADE EXECUTION AND RESPONDING TO MARKET FLUCTUATIONS
6.2.11
UNDERWRITING ENGINES/PLATFORMS
6.2.11.1
EXPEDITING LOAN APPROVALS AND PROMOTING FAIR LENDING
6.2.12
OTHER PRODUCT TYPES
6.3
DEPLOYMENT MODE
6.3.1
CLOUD
6.3.1.1
CLOUD DEPLOYMENT OFFERS SCALABILITY, FLEXIBILITY, AND COST-EFFICIENCY
6.3.2
ON-PREMISES
6.3.2.1
ON-PREMISES DEPLOYMENT PROVIDES FAST DATA PROCESSING AND REAL-TIME ANALYTICS
7
AI IN FINANCE MARKET, BY TECHNOLOGY
Market Size & Growth Rate Forecast Analysis to 2030 in USD Million | 6 Data Tables
127
7.1
INTRODUCTION
7.1.1
TECHNOLOGY: AI IN FINANCE MARKET DRIVERS
7.2
GENERATIVE AI
7.2.1
ENHANCES CUSTOMER ENGAGEMENT AND PROCESS AUTOMATION IN FINANCE
7.3
OTHER AI TECHNOLOGIES
7.3.1
NLP
7.3.1.1
NLP BOOSTS DATA ANALYSIS, AUTOMATES INTERACTIONS, AND ENHANCES COMPLIANCE
7.3.2
PREDICTIVE ANALYTICS
7.3.2.1
AI-DRIVEN PREDICTIVE ANALYTICS ENABLES ACCURATE FORECASTING
8
AI IN FINANCE MARKET, BY APPLICATION
Market Size & Growth Rate Forecast Analysis to 2030 in USD Million | 22 Data Tables
133
8.1
INTRODUCTION
8.1.1
APPLICATION: AI IN FINANCE MARKET DRIVERS
8.2
FINANCE AS BUSINESS OPERATIONS
8.2.1
FRAUD DETECTION & PREVENTION
8.2.1.1
AI-DRIVEN FRAUD DETECTION ENHANCES SECURITY AND REDUCES FINANCIAL LOSSES
8.2.1.2
REAL-TIME TRANSACTION MONITORING
8.2.1.3
CUSTOMER DATA SECURITY
8.2.1.4
CUSTOMER BEHAVIOR ANALYSIS
8.2.1.5
TREND ANALYSIS
8.2.1.6
OTHERS
8.2.2
RISK MANAGEMENT
8.2.2.1
AI-DRIVEN RISK MANAGEMENT ENHANCES DECISION-MAKING IN FINANCE
8.2.2.2
CREDIT RISK SCORING
8.2.2.3
MARKET VOLATILITY PREDICTION
8.2.2.4
STRESS TESTING
8.2.2.5
OTHERS
8.2.3
CUSTOMER SERVICE & ENGAGEMENT
8.2.3.1
CUSTOMER SERVICE AND ENGAGEMENT ENHANCE PERSONALIZATION, LEADING TO IMPROVED CLIENT SATISFACTION
8.2.3.2
CHATBOTS/VIRTUAL ASSISTANTS FOR CUSTOMER SUPPORT
8.2.3.3
PERSONALIZED FINANCIAL PRODUCT RECOMMENDATIONS
8.2.3.4
MARKET SEGMENTATION
8.2.3.5
PERSONALIZED MARKETING MESSAGING
8.2.3.6
NEW CUSTOMER ACQUISITION
8.2.3.7
DATA-DRIVEN DECISION MAKING
8.2.3.8
CUSTOMER RETENTION MANAGEMENT
8.2.3.9
OTHERS
8.2.4
FINANCIAL COMPLIANCE & REGULATORY REPORTING
8.2.4.1
FINANCIAL COMPLIANCE STREAMLINES ACCURACY AND EFFICIENCY IN MEETING STANDARDS
8.2.4.2
RISK & COMPLIANCE MANAGEMENT
8.2.4.3
AUDIT & REPORTING
8.2.4.4
OTHERS
8.2.5
INVESTMENT & PORTFOLIO MANAGEMENT
8.2.5.1
AI OPTIMIZES INVESTMENT AND PORTFOLIO MANAGEMENT FOR SMARTER DECISION-MAKING AND IMPROVED RETURNS
8.2.5.2
ROBO-ADVISORS FOR WEALTH MANAGEMENT
8.2.5.3
PORTFOLIO REBALANCING
8.2.5.4
OTHERS
8.3
FINANCE AS BUSINESS FUNCTIONS
8.3.1
FINANCIAL PLANNING & FORECASTING
8.3.1.1
FINANCIAL PLANNING ENHANCES ACCURACY AND DECISION-MAKING IN FINANCE
8.3.1.2
DEMAND FORECASTING (CAPEX/OPEX)
8.3.1.3
CASH FLOW FORECASTING
8.3.1.4
BUDGETING & EXPENSE MANAGEMENT
8.3.1.5
SCENARIO PLANNING
8.3.1.6
OTHERS
8.3.2
AUTOMATED BOOKKEEPING & RECONCILIATION
8.3.2.1
AUTOMATED BOOKKEEPING AND RECONCILIATION STREAMLINE FINANCIAL PROCESSES AND ENHANCE ACCURACY
8.3.2.2
REAL-TIME LEDGER MATCHING
8.3.2.3
INVOICE PROCESSING
8.3.2.4
VARIANCE DETECTION
8.3.2.5
OTHERS
8.3.3
PROCUREMENT & SUPPLY CHAIN FINANCE
8.3.3.1
AI OPTIMIZES SUPPLY CHAIN MANAGEMENT BY BOOSTING EFFICIENCY AND REDUCING COSTS
8.3.3.2
INVOICE DISCOUNTING
8.3.3.3
SUPPLIER RISK SCORING
8.3.3.4
DYNAMIC PAYMENTS
8.3.3.5
PAYMENT AUTOMATION
8.3.3.6
OTHERS
8.3.4
REVENUE CYCLE MANAGEMENT
8.3.4.1
REVENUE CYCLE MANAGEMENT AUTOMATES PROCESSES AND IMPROVES CASH FLOW THROUGH ENHANCED ACCURACY IN BILLING
8.3.4.2
PAYMENT OPTIMIZATION
8.3.4.3
SUBSCRIPTION BILLING MANAGEMENT
8.3.4.4
INVOICE SETTLEMENTS/AUTOMATED INVOICE PROCESSING
8.3.4.5
CHURN MANAGEMENT
8.3.4.6
OTHERS
9
AI IN FINANCE MARKET, BY END USER
Market Size & Growth Rate Forecast Analysis to 2030 in USD Million | 40 Data Tables
158
9.1
INTRODUCTION
9.1.1
END USER: AI IN FINANCE MARKET DRIVERS
9.2
END USER
9.2.1
FINANCE AS BUSINESS FUNCTIONS
9.2.1.1
GOVERNMENT & PUBLIC SECTOR
9.2.1.1.1
STRENGTHENING GOVERNANCE AND TRUST IN AI IN FINANCE
9.2.1.2
RETAIL & E-COMMERCE
9.2.1.2.1
DRIVING SALES AND SATISFACTION WITH AI-ENHANCED RETAIL
9.2.1.3
REAL ESTATE
9.2.1.3.1
REVOLUTIONIZING REAL ESTATE WITH AI-DRIVEN FINANCE SOLUTIONS
9.2.1.4
MANUFACTURING
9.2.1.4.1
TRANSFORMING FINANCIAL PROCESSES OF MANUFACTURING SECTOR FOR ENHANCED EFFICIENCY AND GROWTH
9.2.1.5
TELECOM & MEDIA
9.2.1.5.1
LEVERAGING AI IN TELECOM & MEDIA FOR OPTIMIZED NETWORK MANAGEMENT AND ENHANCED SERVICE QUALITY
9.2.1.6
HEALTHCARE & PHARMA
9.2.1.6.1
AI PROVIDES ENHANCED AND PATIENT-CENTRIC SOLUTIONS IN FINANCE
9.2.1.7
UTILITIES
9.2.1.7.1
AI TRANSFORMS UTILITIES SECTOR BY ENHANCING OPERATIONAL EFFICIENCY AND IMPROVING PREDICTIVE MAINTENANCE
9.2.1.8
EDUCATION
9.2.1.8.1
HARNESSING AI TO TRANSFORM EDUCATION FINANCE BY STREAMLINING OPERATIONS AND ENHANCING FINANCIAL LITERACY
9.2.1.9
TECHNOLOGY & SOFTWARE
9.2.1.9.1
TECHNOLOGY AND SOFTWARE ENABLE AUTOMATION AND IMPROVE DECISION-MAKING PROCESSES
9.2.1.10
OTHER END USERS
9.3
FINANCE AS BUSINESS OPERATIONS
9.3.1
BANKING
9.3.1.1
AI ENABLES BETTER RISK MANAGEMENT AND IMPROVES FRAUD DETECTION
9.3.1.2
CORPORATE & COMMERCIAL BANKING
9.3.1.3
RETAIL BANKING
9.3.1.4
INVESTMENT BANKING
9.3.2
INSURANCE
9.3.2.1
AI AUTOMATES CLAIM PROCESSING, REDUCES FRAUD, AND PERSONALIZES POLICIES
9.3.3
INVESTMENT & ASSET MANAGEMENT
9.3.3.1
AI ENHANCES DECISION-MAKING AND OPTIMIZES PORTFOLIO MANAGEMENT
9.3.3.2
HEDGE FUNDS
9.3.3.3
PRIVATE EQUITY
9.3.3.4
WEALTH MANAGEMENT
9.3.4
FINTECH
9.3.4.1
AI IN FINTECH AUTOMATES TASKS, IMPROVES DATA ANALYSIS, AND PROVIDES REAL-TIME INSIGHTS
9.3.4.2
BLOCKCHAIN & CRYPTOCURRENCY PROVIDERS
9.3.4.3
LENDING PLATFORM PROVIDERS/SPECIALTY LENDERS
9.3.5
CAPITAL MARKETS/REGTECH
9.3.5.1
AI INCREASES EFFICIENCY AND REDUCES OPERATIONAL COSTS IN CAPITAL MARKETS
10
AI IN FINANCE MARKET, BY REGION
Comprehensive coverage of 7 Regions with country-level deep-dive of 17 Countries | 144 Data Tables.
183
10.1
INTRODUCTION
10.2
NORTH AMERICA
10.2.1
NORTH AMERICA: AI IN FINANCE MARKET DRIVERS
10.2.2
NORTH AMERICA: MACROECONOMIC IMPACT
10.2.3
US
10.2.3.1
TRANSFORMING BRANDS WITH AI-DRIVEN PERSONALIZATION IN SOCIAL MEDIA
10.2.4
CANADA
10.2.4.1
ACCELERATING AI ADOPTION IN FINANCE THROUGH AUTOMATION AND DIGITAL TRANSFORMATION
10.3
EUROPE
10.3.1
EUROPE: AI IN FINANCE MARKET DRIVERS
10.3.2
EUROPE: MACROECONOMIC IMPACT
10.3.3
UK
10.3.3.1
LEVERAGING AUTOMATION AND DATA ANALYTICS FOR ENHANCED DECISION-MAKING AND COMPLIANCE
10.3.4
GERMANY
10.3.4.1
FOCUS ON AUTOMATION IN RISK MANAGEMENT AND PERSONALIZED BANKING SERVICES TO IMPROVE OPERATIONAL EFFICIENCY
10.3.5
FRANCE
10.3.5.1
ROBUST GOVERNMENT INITIATIVES PROMOTE INNOVATION AND ESTABLISH FRAMEWORKS ENCOURAGING AI TECHNOLOGY ADOPTION
10.3.6
ITALY
10.3.6.1
PROMOTION OF DIGITAL TRANSFORMATION AND RISING INVESTMENT IN AI TECHNOLOGIES ACROSS FINANCIAL INSTITUTIONS
10.3.7
SPAIN
10.3.7.1
INCREASED FUNDING AND STRATEGIC PARTNERSHIPS TO ENHANCE AI COLLABORATION IN FINANCIAL SERVICES
10.3.8
REST OF EUROPE
10.4
ASIA PACIFIC
10.4.1
ASIA PACIFIC: AI IN FINANCE MARKET DRIVERS
10.4.2
ASIA PACIFIC: MACROECONOMIC IMPACT
10.4.3
CHINA
10.4.3.1
INCREASING FOCUS ON AI INNOVATION FOR OPERATIONAL EFFICIENCY IN FINANCIAL SECTOR TO BOOST MARKET
10.4.4
JAPAN
10.4.4.1
PARTNERSHIPS BETWEEN FINANCIAL INSTITUTIONS AND TECH FIRMS ACCELERATE AI INTEGRATION FOR IMPROVED FINANCIAL SOLUTIONS
10.4.5
INDIA
10.4.5.1
INCREASING ADOPTION OF AI-POWERED SOLUTIONS BY FINANCIAL INSTITUTIONS FOR RISK MANAGEMENT TO DRIVE MARKET
10.4.6
SOUTH KOREA
10.4.6.1
GOVERNMENT SUPPORT ENHANCES FINANCIAL SERVICES AND BOOSTS COMPETITIVENESS IN FINTECH SECTOR
10.4.7
AUSTRALIA & NEW ZEALAND
10.4.7.1
INCREASING ADOPTION OF AI BY GROWING FINTECH COMPANIES TO DRIVE MARKET
10.4.8
ASEAN
10.4.8.1
INCREASING DIGITALIZATION OF BANKING SERVICES TO DRIVE MARKET
10.4.9
REST OF ASIA PACIFIC
10.5
MIDDLE EAST & AFRICA
10.5.1
MIDDLE EAST & AFRICA: AI IN FINANCE MARKET DRIVERS
10.5.2
MIDDLE EAST & AFRICA: MACROECONOMIC IMPACT
10.5.3
MIDDLE EAST
10.5.3.1
KSA
10.5.3.1.1
GOVERNMENT VISION 2030 INITIATIVE PROMOTING DIGITAL TRANSFORMATION AND AI ADOPTION IN FINANCIAL SERVICES TO DRIVE MARKET
10.5.3.2
UAE
10.5.3.2.1
INCREASED INVESTMENTS IN AI-POWERED FINANCIAL TECHNOLOGIES TO DRIVE MARKET
10.5.3.3
KUWAIT
10.5.3.3.1
GROWING FOCUS ON DIGITAL TRANSFORMATION TO FUEL AI ADOPTION IN FINANCE MARKET
10.5.3.4
BAHRAIN
10.5.3.4.1
INCREASING ADOPTION OF AI TECHNOLOGIES IN BANKING SECTOR TO DRIVE MARKET
10.5.4
AFRICA
10.5.4.1
INCREASING ADOPTION OF AI TO ENHANCE FINANCIAL SERVICES TO DRIVE MARKET
10.6
LATIN AMERICA
10.6.1
LATIN AMERICA: AI IN FINANCE MARKET DRIVERS
10.6.2
LATIN AMERICA: MACROECONOMIC IMPACT
10.6.3
BRAZIL
10.6.3.1
GOVERNMENT SUPPORT AND INVESTMENTS IN AI TO DRIVE MARKET
10.6.4
MEXICO
10.6.4.1
INCREASED INVESTMENT IN FINTECH TO DRIVE AI ADOPTION IN FINANCE MARKET
10.6.5
ARGENTINA
10.6.5.1
FINTECH EXPANSION AND INNOVATION TO PROPEL MARKET GROWTH
10.6.6
REST OF LATIN AMERICA
11
COMPETITIVE LANDSCAPE
Discover how top players dominate finance markets with strategic insights and product comparisons.
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
11.4.1
MARKET SHARE ANALYSIS OF KEY PLAYERS (FINANCE AS BUSINESS FUNCTIONS)
11.4.2
MARKET RANKING ANALYSIS (FINANCE AS BUSINESS FUNCTIONS)
11.4.3
MARKET SHARE ANALYSIS OF KEY PLAYERS (FINANCE AS BUSINESS OPERATIONS)
11.4.4
MARKET RANKING ANALYSIS (FINANCE AS BUSINESS OPERATIONS)
11.5
PRODUCT COMPARISON
11.5.1
PRODUCT COMPARATIVE ANALYSIS, BY RISK ASSESSMENT
11.5.1.1
ZAML (ZEST AUTOMATED MACHINE LEARNING) (ZEST AI)
11.5.1.2
KENSHO RISK (KENSHO)
11.5.1.3
C3 AI RISK MANAGEMENT (C3 AI)
11.5.1.4
FINACLE TREASURY AND RISK MANAGEMENT SOLUTION (INFOSYS)
11.5.2
PRODUCT COMPARATIVE ANALYSIS, BY FRAUD DETECTION & PREVENTION
11.5.2.1
SOCURE ID+ (SOCURE)
11.5.2.2
DATAMINR REAL-TIME RISK DETECTION (DATAMINR)
11.5.2.3
GOOGLE CLOUD (GOOGLE)
11.5.2.4
VECTRA COGNITO (VECTRA AI)
11.5.3
PRODUCT COMPARATIVE ANALYSIS, BY CHATBOTS & PERSONAL ASSISTANTS
11.5.3.1
ALPHASENSE SEARCH CHATBOT (ALPHASENSE)
11.5.3.2
ORACLE DIGITAL ASSISTANT (ORACLE)
11.5.3.3
WATSON ASSISTANT (IBM)
11.6
COMPANY VALUATION AND FINANCIAL METRICS OF KEY VENDORS
11.7
COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
11.7.1
COMPANY EVALUATION MATRIX: KEY PLAYERS (FINANCE AS BUSINESS FUNCTIONS)
11.7.1.1
STARS
11.7.1.2
EMERGING LEADERS
11.7.1.3
PERVASIVE PLAYERS
11.7.1.4
PARTICIPANTS
11.7.2
COMPANY EVALUATION MATRIX: KEY PLAYERS (FINANCE AS BUSINESS OPERATIONS)
11.7.2.1
STARS
11.7.2.2
EMERGING LEADERS
11.7.2.3
PERVASIVE PLAYERS
11.7.2.4
PARTICIPANTS
11.7.3
COMPANY FOOTPRINT: KEY PLAYERS
11.7.3.1
COMPANY FOOTPRINT (1/2)
11.7.3.2
COMPANY FOOTPRINT (2/2)
11.7.3.3
REGIONAL FOOTPRINT
11.7.3.4
PRODUCT FOOTPRINT
11.7.3.5
APPLICATION FOOTPRINT
11.7.3.6
END-USER FOOTPRINT
11.8
COMPANY EVALUATION MATRIX: START-UPS/SMES, 2023
11.8.1
COMPANY EVALUATION MATRIX: START-UPS/SMES (FINANCE AS BUSINESS OPERATIONS)
11.8.1.1
PROGRESSIVE COMPANIES
11.8.1.2
RESPONSIVE COMPANIES
11.8.1.3
DYNAMIC COMPANIES
11.8.1.4
STARTING BLOCKS
11.8.2
COMPANY EVALUATION MATRIX: START-UPS/SMES (FINANCE AS BUSINESS FUNCTIONS)
11.8.2.1
PROGRESSIVE COMPANIES
11.8.2.2
RESPONSIVE COMPANIES
11.8.2.3
DYNAMIC COMPANIES
11.8.2.4
STARTING BLOCKS
11.8.3
COMPETITIVE BENCHMARKING: START-UPS/SMES, 2024
11.8.3.1
DETAILED LIST OF KEY START-UPS/SMES
11.8.3.2
COMPETITIVE BENCHMARKING OF KEY START-UPS/SMES
11.9
COMPETITIVE SCENARIO
11.9.1
PRODUCT LAUNCHES AND ENHANCEMENTS
11.9.2
DEALS
12
COMPANY PROFILES
In-depth Company Profiles of Leading Market Players with detailed Business Overview, Product and Service Portfolio, Recent Developments, and Unique Analyst Perspective (MnM View)
288
12.1
INTRODUCTION
12.2
KEY PLAYERS
12.2.1
FIS
12.2.1.1
BUSINESS OVERVIEW
12.2.1.2
PRODUCTS/SOLUTIONS/SERVICES OFFERED
12.2.1.3
RECENT DEVELOPMENTS
12.2.1.3.1
PRODUCT LAUNCHES AND ENHANCEMENTS
12.2.1.3.2
DEALS
12.2.1.4
MNM VIEW
12.2.1.4.1
KEY STRENGTHS
12.2.1.4.2
STRATEGIC CHOICES
12.2.1.4.3
WEAKNESSES AND COMPETITIVE THREATS
12.2.2
FISERV
12.2.3
GOOGLE
12.2.4
MICROSOFT
12.2.5
ZOHO
12.2.6
IBM
12.2.7
SOCURE
12.2.8
WORKIVA
12.2.9
PLAID
12.2.10
C3 AI
12.2.11
HIGHRADIUS
12.2.12
SAP
12.2.13
DOMO
12.2.14
XERO
12.2.15
AWS
12.2.16
HPE
12.2.17
ORACLE
12.2.18
SALESFORCE
12.2.19
NETAPP
12.2.20
DATAROBOT
12.2.21
ENOVA INTERNATIONAL
12.2.22
ALPHASENSE
12.2.23
OCROLUS
12.2.24
VECTRA AI
12.2.25
TERADATA
12.2.26
PEGA
12.2.27
VENA SOLUTIONS
12.2.28
AFFIRM
12.2.29
SYMPHONYAI
12.2.30
ENVESTNET | YODLEE
12.3
START-UPS/SMES
12.3.1
ADDEPTO
12.3.2
DATARAILS
12.3.3
SIGFIG
12.3.4
DEEPER INSIGHTS
12.3.5
H2O.AI
12.3.6
APP0
12.3.7
UNDERWRITE.AI
12.3.8
DEEPGRAM
12.3.9
EMAGIA
12.3.10
INDATA LABS
12.3.11
ZEST AI
12.3.12
SCIENAPTIC AI
12.3.13
GRADIENT AI
12.3.14
KASISTO
12.3.15
TRUMID
12.3.16
DATAVISOR
12.3.17
KAVOUT
12.3.18
WEALTHBLOCK
13
ADJACENT AND RELATED MARKETS
375
13.1
INTRODUCTION
13.2
ARTIFICIAL INTELLIGENCE (AI) MARKET – GLOBAL FORECAST TO 2030
13.2.1
MARKET DEFINITION
13.2.2
MARKET OVERVIEW
13.2.2.1
ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING
13.2.2.2
ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION
13.2.2.3
ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY
13.2.2.4
ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL
13.2.2.5
ARTIFICIAL INTELLIGENCE MARKET, BY REGION
13.3
NLP IN FINANCE MARKET – GLOBAL FORECAST TO 2028
13.3.1
MARKET DEFINITION
13.3.2
MARKET OVERVIEW
13.3.2.1
NLP IN FINANCE MARKET, BY OFFERING
13.3.2.2
NLP IN FINANCE MARKET, BY APPLICATION
13.3.2.3
NLP IN FINANCE MARKET, BY TECHNOLOGY
13.3.2.4
NLP IN FINANCE MARKET, BY VERTICAL
13.3.2.5
NLP IN FINANCE MARKET, BY REGION
14
APPENDIX
389
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
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.
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
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.
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Growth opportunities and latent adjacency in AI in Finance Market