Product Code: FBI113534
Growth Factors of AI agents in financial services Market
The global AI agents in financial services market is expanding rapidly as financial institutions accelerate their adoption of intelligent automation and advanced analytics. According to the latest report, the market was valued at USD 1,569.3 million in 2024, supported by rising digital banking usage, increased financial data generation, and growing demand for enhanced customer experiences. By 2025, the market is expected to reach USD 1,747.1 million, driven by investments in AI-driven risk management, fraud detection, compliance automation, and financial advisory solutions. With continued innovation and strong venture capital interest, the market is projected to achieve USD 4,280.0 million by 2032, showcasing strong long-term growth potential.
In 2024, financial institutions-including banks, insurers, wealth management firms, and NBFCs-relied heavily on AI agents to optimize workflows and strengthen cybersecurity. These agents performed core activities such as trade processing, audit automation, portfolio optimization, fraud detection, customer service, and marketing analytics. The shift toward mobile banking and digital onboarding boosted the adoption of conversational AI and autonomous agents capable of delivering real-time decision-making and improved client experiences. Increasing data volumes, especially in payment systems and credit operations, played a major role in accelerating demand for AI-powered monitoring and compliance systems.
The transition from 2024 to 2025 saw rapid expansion of venture capital funding in generative AI and agentic AI startups. According to OECD data, 938 VC investments were recorded in the global generative AI space in 2024, with an average deal size of USD 97 million, highlighting strong investor confidence. Financial institutions also adopted AI agents to reduce operational costs, improve regulatory compliance, and support high-volume digital transactions. These solutions strengthened anti-money laundering (AML) monitoring, improved KYC verification, and enhanced real-time fraud detection across global markets.
However, deployment challenges persisted in 2024-2025. High installation and infrastructure costs created barriers for smaller financial institutions, especially those operating on legacy IT systems. Additional constraints included limited availability of skilled AI professionals and delays in building cloud and on-premises AI infrastructure. Increased hardware pricing and reliance on cloud providers also influenced adoption timelines across developing economies, slowing the market's growth potential.
Despite these restraints, the industry is witnessing significant innovation in financial advisory and wealth management services. Young, financially aware demographics in emerging markets such as India and China are increasingly adopting automated financial planning and robo-advisory tools. AI agents now support asset diversification, portfolio monitoring, and personalized investment recommendations. New product developments-such as Morgan Stanley's GenAI suite for financial advisors announced in 2024-highlight the sector's shift toward data-driven advisory ecosystems.
Segment-wise, conversational AI agents dominated the market in 2024, driven by demand for personalized responses, virtual financial assistance, and automated customer engagement. Fraud detection agents are expected to record the fastest growth, powered by rising cybercrimes and advanced analytics required to identify suspicious transactions. In deployment, on-premises solutions held the largest share due to enhanced data security and compatibility with traditional banking systems, while cloud-based models saw strong interest because of their scalability and real-time integration capabilities.
Regionally, North America recorded USD 723.7 million in 2024, making it the leading market due to early AI adoption, investment momentum, and rising cybersecurity threats. The U.S. dominated the region, supported by over USD 15.26 billion in generative AI venture funding. Asia Pacific experienced rapid growth driven by digital banking expansion, young demographics, and rising demand for hyper-personalized financial services. Europe maintained steady momentum, though regulatory frameworks such as the EU AI Act created compliance challenges. South America and Middle East & Africa also saw rising adoption, supported by fintech expansion and increased cyber fraud incidents.
In conclusion, the global AI agents in financial services market is positioned for strong long-term growth. With the market advancing from USD 1,569.3 million in 2024 to USD 4,280.0 million by 2032, AI agents are set to become indispensable in enhancing financial decision-making, reducing fraud, optimizing operations, and transforming customer experiences across the global financial ecosystem.
Segmentation By Agent Type
- Conversational AI Agents
- Risk & Compliance Agents
- Fraud Detection Agents
- Credit & Lending Agents
- Investment & Wealth Agents
- Payments & Transaction Agents
- Others (Multi-Agent Systems, etc.)
By Deployment Type
- On-Premises
- Cloud-based
- Hybrid
By End User
- Banks
- Insurance
- Non-banking Financial Institutions
By Region
- North America (By Agent Type, By Deployment Type, By End User, and By Country)
- U.S. (By End User)
- Canada (By End User)
- Mexico (By End User)
- Europe (By Agent Type, By Deployment Type, By End User, and By Country)
- Germany (By End User)
- U.K. (By End User)
- France (By End User)
- Italy (By End User)
- BENELUX (By End User)
- Nordics (By End User)
- Russia (By End User)
- Rest of Europe
- Asia Pacific (By Agent Type, By Deployment Type, By End User, and By Country)
- China (By End User)
- India (By End User)
- Japan (By End User)
- South Korea (By End User)
- ASEAN (By End User)
- Oceania (By End User)
- Rest of Asia Pacific
- South America (By Agent Type, By Deployment Type, By End User, and By Country)
- Brazil (By End User)
- Argentina (By End User)
- Rest of South America
- Middle East and Africa (By Agent Type, By Deployment Type, By End User, and By Country)
- GCC Countries (By End User)
- South Africa (By End User)
- Israel (By End User)
- Rest of MEA
Companies Profiled in the Report IBM Corporation (U.S.), Accenture (Ireland), Microsoft (U.S.), Google Cloud (U.S.), Cognizant (U.S.), H2O.ai (U.S.), Verint Systems (U.S.), UiPath (U.S.), Darktrace (U.K.), FICO (U.S.)
Table of Content
1. Introduction
- 1.1. Definition, By Segment
- 1.2. Research Methodology/Approach
- 1.3. Data Sources
2. Executive Summary
3. Market Dynamics
- 3.1. Macro and Micro Economic Indicators
- 3.2. Drivers, Restraints, Opportunities, and Trends
- 3.3. Impact of Reciprocal Tariffs on the Market
4. Competition Landscape
- 4.1. Business Strategies Adopted by Key Players
- 4.2. Consolidated SWOT Analysis of Key Players
- 4.3. Global AI Agents in Financial Services Key Players Market Share/Ranking, 2024
5. Global AI Agents in Financial Services Market Size Estimates and Forecasts, By Segments, 2019-2032
- 5.1. Key Findings
- 5.2. By Agent Type (USD Mn)
- 5.2.1. Conversational AI Agents
- 5.2.2. Risk & Compliance Agents
- 5.2.3. Fraud Detection Agents
- 5.2.4. Credit & Lending Agents
- 5.2.5. Investment & Wealth Agents
- 5.2.6. Payments & Transaction Agents
- 5.2.7. Others (Molti-Agent Systems, etc.)
- 5.3. By Deployment Type (USD Mn)
- 5.3.1. On-Premises
- 5.3.2. Cloud -based
- 5.3.3. Hybrid
- 5.4. By End User (USD Mn)
- 5.4.1. Banks
- 5.4.2. Insurance
- 5.4.3. Non-banking Financial Institutions
- 5.5. By Region (USD Mn)
- 5.5.1. North America
- 5.5.2. South America
- 5.5.3. Europe
- 5.5.4. Middle East & Africa
- 5.5.5. Asia Pacific
6. North America AI Agents in Financial Services Market Size Estimates and Forecasts, By Segments, 2019-2032
- 6.1. Key Findings
- 6.2. By Agent Type (USD Mn)
- 6.2.1. Conversational AI Agents
- 6.2.2. Risk & Compliance Agents
- 6.2.3. Fraud Detection Agents
- 6.2.4. Credit & Lending Agents
- 6.2.5. Investment & Wealth Agents
- 6.2.6. Payments & Transaction Agents
- 6.2.7. Others (Molti-Agent Systems, etc.)
- 6.3. By Deployment Type (USD Mn)
- 6.3.1. On-Premises
- 6.3.2. Cloud -based
- 6.3.3. Hybrid
- 6.4. By End User (USD Mn)
- 6.4.1. Banks
- 6.4.2. Insurance
- 6.4.3. Non-banking Financial Institutions
- 6.5. By Country (USD Mn)
- 6.5.1. United States
- 6.5.1.1. By End User (USD Mn)
- 6.5.2. Canada
- 6.5.2.1. By End User (USD Mn)
- 6.5.3. Mexico
- 6.5.3.1. By End User (USD Mn)
7. South America AI Agents in Financial Services Market Size Estimates and Forecasts, By Segments, 2019-2032
- 7.1. Key Findings
- 7.2. By Agent Type (USD Mn)
- 7.2.1. Conversational AI Agents
- 7.2.2. Risk & Compliance Agents
- 7.2.3. Fraud Detection Agents
- 7.2.4. Credit & Lending Agents
- 7.2.5. Investment & Wealth Agents
- 7.2.6. Payments & Transaction Agents
- 7.2.7. Others (Molti-Agent Systems, etc.)
- 7.3. By Deployment Type (USD Mn)
- 7.3.1. On-Premises
- 7.3.2. Cloud -based
- 7.3.3. Hybrid
- 7.4. By End User (USD Mn)
- 7.4.1. Banks
- 7.4.2. Insurance
- 7.4.3. Non-banking Financial Institutions
- 7.5. By Country (USD Mn)
- 7.5.1. Brazil
- 7.5.1.1. By End User (USD Mn)
- 7.5.2. Argentina
- 7.5.2.1. By End User (USD Mn)
- 7.5.3. Rest of South America
8. Europe AI Agents in Financial Services Market Size Estimates and Forecasts, By Segments, 2019-2032
- 8.1. Key Findings
- 8.2. By Agent Type (USD Mn)
- 8.2.1. Conversational AI Agents
- 8.2.2. Risk & Compliance Agents
- 8.2.3. Fraud Detection Agents
- 8.2.4. Credit & Lending Agents
- 8.2.5. Investment & Wealth Agents
- 8.2.6. Payments & Transaction Agents
- 8.2.7. Others (Molti-Agent Systems, etc.)
- 8.3. By Deployment Type (USD Mn)
- 8.3.1. On-Premises
- 8.3.2. Cloud -based
- 8.3.3. Hybrid
- 8.4. By End User (USD Mn)
- 8.4.1. Banks
- 8.4.2. Insurance
- 8.4.3. Non-banking Financial Institutions
- 8.5. By Country (USD Mn)
- 8.5.1. United Kingdom
- 8.5.1.1. By End User (USD Mn)
- 8.5.2. Germany
- 8.5.2.1. By End User (USD Mn)
- 8.5.3. France
- 8.5.3.1. By End User (USD Mn)
- 8.5.4. Italy
- 8.5.4.1. By End User (USD Mn)
- 8.5.5. BENELUX
- 8.5.5.1. By End User (USD Mn)
- 8.5.6. Nordics
- 8.5.6.1. By End User (USD Mn)
- 8.5.7. Russia
- 8.5.7.1. By End User (USD Mn)
- 8.5.8. Rest of Europe
9. Middle East & Africa AI Agents in Financial Services Market Size Estimates and Forecasts, By Segments, 2019-2032
- 9.1. Key Findings
- 9.2. By Agent Type (USD Mn)
- 9.2.1. Conversational AI Agents
- 9.2.2. Risk & Compliance Agents
- 9.2.3. Fraud Detection Agents
- 9.2.4. Credit & Lending Agents
- 9.2.5. Investment & Wealth Agents
- 9.2.6. Payments & Transaction Agents
- 9.2.7. Others (Molti-Agent Systems, etc.)
- 9.3. By Deployment Type (USD Mn)
- 9.3.1. On-Premises
- 9.3.2. Cloud -based
- 9.3.3. Hybrid
- 9.4. By End User (USD Mn)
- 9.4.1. Banks
- 9.4.2. Insurance
- 9.4.3. Non-banking Financial Institutions
- 9.5. By Country (USD Mn)
- 9.5.1. GCC Countries
- 9.5.1.1. By End User (USD Mn)
- 9.5.2. South Africa
- 9.5.2.1. By End User (USD Mn)
- 9.5.3. Israel
- 9.5.3.1. By End User (USD Mn)
- 9.5.4. Rest of MEA
10. Asia Pacific AI Agents in Financial Services Market Size Estimates and Forecasts, By Segments, 2019-2032
- 10.1. Key Findings
- 10.2. By Agent Type (USD Mn)
- 10.2.1. Conversational AI Agents
- 10.2.2. Risk & Compliance Agents
- 10.2.3. Fraud Detection Agents
- 10.2.4. Credit & Lending Agents
- 10.2.5. Investment & Wealth Agents
- 10.2.6. Payments & Transaction Agents
- 10.2.7. Others (Molti-Agent Systems, etc.)
- 10.3. By Deployment Type (USD Mn)
- 10.3.1. On-Premises
- 10.3.2. Cloud -based
- 10.3.3. Hybrid
- 10.4. By End User (USD Mn)
- 10.4.1. Banks
- 10.4.2. Insurance
- 10.4.3. Non-banking Financial Institutions
- 10.5. By Country (USD Mn)
- 10.5.1. China
- 10.5.1.1. By End User (USD Mn)
- 10.5.2. India
- 10.5.2.1. By End User (USD Mn)
- 10.5.3. Japan
- 10.5.3.1. By End User (USD Mn)
- 10.5.4. South Korea
- 10.5.4.1. By End User (USD Mn)
- 10.5.5. ASEAN
- 10.5.5.1. By End User (USD Mn)
- 10.5.6. Oceania
- 10.5.6.1. By End User (USD Mn)
- 10.5.7. Rest of Asia Pacific
11. Company Profiles for Top 10 Players (Based on data availability in public domain and/or on paid databases)
- 11.1. IBM Corporation
- 11.1.1. Overview
- 11.1.1.1. Key Management
- 11.1.1.2. Headquarters
- 11.1.1.3. Offerings/Business Segments
- 11.1.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.1.2.1. Employee Size
- 11.1.2.2. Past and Current Revenue
- 11.1.2.3. Geographical Share
- 11.1.2.4. Business Segment Share
- 11.1.2.5. Recent Developments
- 11.1.3. Accenture
- 11.1.3.1. Overview
- 11.1.3.1.1. Key Management
- 11.1.3.1.2. Headquarters
- 11.1.3.1.3. Offerings/Business Segments
- 11.1.3.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.1.3.2.1. Employee Size
- 11.1.3.2.2. Past and Current Revenue
- 11.1.3.2.3. Geographical Share
- 11.1.3.2.4. Business Segment Share
- 11.1.3.2.5. Recent Developments
- 11.1.3.3. Microsoft
- 11.1.3.3.1. Overview
- 11.1.3.3.1.1. Key Management
- 11.1.3.3.1.2. Headquarters
- 11.1.3.3.1.3. Offerings/Business Segments
- 11.1.3.3.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.1.3.3.2.1. Employee Size
- 11.1.3.3.2.2. Past and Current Revenue
- 11.1.3.3.2.3. Geographical Share
- 11.1.3.3.2.4. Business Segment Share
- 11.1.3.3.2.5. Recent Developments
- 11.1.3.4. Google Cloud
- 11.1.3.4.1. Overview
- 11.1.3.4.1.1. Key Management
- 11.1.3.4.1.2. Headquarters
- 11.1.3.4.1.3. Offerings/Business Segments
- 11.1.3.4.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.1.3.4.2.1. Employee Size
- 11.1.3.4.2.2. Past and Current Revenue
- 11.1.3.4.2.3. Geographical Share
- 11.1.3.4.2.4. Business Segment Share
- 11.1.3.4.2.5. Recent Developments
- 11.1.3.5. Cognizant
- 11.1.3.5.1. Overview
- 11.1.3.5.1.1. Key Management
- 11.1.3.5.1.2. Headquarters
- 11.1.3.5.1.3. Offerings/Business Segments
- 11.1.3.5.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.1.3.5.2.1. Employee Size
- 11.1.3.5.2.2. Past and Current Revenue
- 11.1.3.5.2.3. Geographical Share
- 11.1.3.5.2.4. Business Segment Share
- 11.1.3.5.2.5. Recent Developments
- 11.1.3.6. H2Oai
- 11.1.3.6.1. Overview
- 11.1.3.6.1.1. Key Management
- 11.1.3.6.1.2. Headquarters
- 11.1.3.6.1.3. Offerings/Business Segments
- 11.1.3.6.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.1.3.6.2.1. Employee Size
- 11.1.3.6.2.2. Past and Current Revenue
- 11.1.3.6.2.3. Geographical Share
- 11.1.3.6.2.4. Business Segment Share
- 11.1.3.6.2.5. Recent Developments
- 11.1.3.7. Verint Systems
- 11.1.3.7.1. Overview
- 11.1.3.7.1.1. Key Management
- 11.1.3.7.1.2. Headquarters
- 11.1.3.7.1.3. Offerings/Business Segments
- 11.1.3.7.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.1.3.7.2.1. Employee Size
- 11.1.3.7.2.2. Past and Current Revenue
- 11.1.3.7.2.3. Geographical Share
- 11.1.3.7.2.4. Business Segment Share
- 11.1.3.7.2.5. Recent Developments
- 11.1.3.8. UiPath
- 11.1.3.8.1. Overview
- 11.1.3.8.1.1. Key Management
- 11.1.3.8.1.2. Headquarters
- 11.1.3.8.1.3. Offerings/Business Segments
- 11.1.3.8.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.1.3.8.2.1. Employee Size
- 11.1.3.8.2.2. Past and Current Revenue
- 11.1.3.8.2.3. Geographical Share
- 11.1.3.8.2.4. Business Segment Share
- 11.1.3.8.2.5. Recent Developments
- 11.1.3.9. Darktrace
- 11.1.3.9.1. Overview
- 11.1.3.9.1.1. Key Management
- 11.1.3.9.1.2. Headquarters
- 11.1.3.9.1.3. Offerings/Business Segments
- 11.1.3.9.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.1.3.9.2.1. Employee Size
- 11.1.3.9.2.2. Past and Current Revenue
- 11.1.3.9.2.3. Geographical Share
- 11.1.3.9.2.4. Business Segment Share
- 11.1.3.9.2.5. Recent Developments
- 11.1.3.10. FICO
- 11.1.3.10.1. Overview
- 11.1.3.10.1.1. Key Management
- 11.1.3.10.1.2. Headquarters
- 11.1.3.10.1.3. Offerings/Business Segments
- 11.1.3.10.2. Key Details (Key details are consolidated data and not product/service specific)
- 11.1.3.10.2.1. Employee Size
- 11.1.3.10.2.2. Past and Current Revenue
- 11.1.3.10.2.3. Geographical Share
- 11.1.3.10.2.4. Business Segment Share
- 11.1.3.10.2.5. Recent Developments