AI Agents in Finance: Banking, Insurance, and Investment
How autonomous AI systems are transforming fraud detection, claims processing, trading, and regulatory compliance
Key Takeaways
- The AI agents in finance market reached $1.79 billion in 2025 and is projected to hit $6.54 billion by 2035 with a 13.84% CAGR
- 91% of US banks now use AI for fraud detection, with JPMorgan reducing false positives by 50% and improving detection by 25%
- AI will not replace insurance agents—55% of insurance companies plan to hire more staff, with AI handling routine tasks while humans focus on complex cases
- DBS Bank created $750 million in economic value from AI in 2024 across 1,500+ models and 370 use cases
AI AGENTS IN FINANCIAL SERVICES 2026
Sources: Precedence Research, IBM AI Fraud Detection, Xenoss Banking Report
The Rise of AI Agents in Financial Services
AI agents in finance are transforming how banks, insurance companies, and investment firms operate. Unlike traditional rule-based automation, these autonomous systems can perceive complex financial data, reason through multi-step processes, and take actions—all while learning and adapting over time.
According to Precedence Research, the global AI agents in financial services market reached $1.79 billion in 2025 and is projected to grow to $6.54 billion by 2035—a compound annual growth rate of 13.84%. North America dominates with 46% market share, driven by a mature banking ecosystem and high cloud adoption.
Key Applications Across Financial Services
The adoption rate is accelerating rapidly. According to ElectroIQ's AI in Finance Statistics, AI use in finance shot up from 45% in 2022 to 85% in 2025. By 2025, 87% of global financial institutions have implemented AI-powered fraud detection systems—up from 72% in early 2024.
For deeper exploration of AI in financial services, see our guide on agentic AI in financial services. Large financial institutions are deploying enterprise AI agents at scale to transform operations across banking, insurance, and wealth management.
AI Agents for Fraud Detection in Banking
Fraud detection represents the largest application of AI agents for finance, accounting for 33.4% of global market revenue. In the United States alone, 91% of banks now rely on AI to detect and prevent fraud.
Up from $12.3B in 2023 due to deepfakes
RAG-enabled voice scam detection in 2024
JPMorgan Chase after AI adoption
The threat landscape is evolving rapidly. According to Deloitte's Center for Financial Services, generative AI is enabling sophisticated deepfake attacks. In January 2024, fraudsters used an AI-generated deepfake of a company CFO on a video call to steal $25 million from a Hong Kong-based firm.
How Agentic AI Transforms Fraud Detection
According to McKinsey's analysis on agentic AI in banking, traditional AI approaches handle individual steps in isolation. Agentic AI goes further—specialized agents break goals into sub-tasks, act across tools and data sources, self-check, and escalate to humans only for exceptions.
The results speak for themselves. According to Feedzai's AI Fraud Trends 2025 report, 90% of financial institutions now combat emerging fraud with AI-powered solutions. AI is used for scam detection (50%), transaction fraud (39%), and anti-money laundering (30%). Meanwhile, 43% of financial professionals report increased efficiency within fraud teams, allowing experts to focus on higher-value, complex fraud cases.
AI Agents in Insurance: Claims and Underwriting
The insurance segment is experiencing the highest growth rate in AI agents for finance. According to GlobeNewswire, the insurance analytics market is projected to grow from $13.29 billion in 2025 to $31.76 billion by 2031 at a 15.64% CAGR.
| Use Case | Market Share | Key Benefit |
|---|---|---|
| Claims Management | 34.12% | Automated FNOL and triage |
| Fraud Detection | 18.95% CAGR | Pattern recognition in claims |
| Underwriting Analysis | Growing segment | Risk assessment automation |
| Customer Service | 24/7 availability | Policy inquiries and renewals |
According to V7 Labs, Accenture found that up to 40% of claims underwriters' time is spent on non-core and administrative activities—representing an industry-wide efficiency loss of up to $160 billion over the next five years. AI agents are positioned to reclaim this value.
AI-Powered Claims Processing Workflow
Document Ingestion
AI accepts photos, PDFs, and scanned forms in any format. Uses computer vision and OCR to extract structured data including date of loss, location, parties involved, and damage description.
Policy Verification
Cross-references extracted data against policy records to verify coverage, check deductibles, and identify any exclusions that may apply to the claim.
Triage and Routing
Assigns a severity score based on complexity and urgency. Routes straightforward claims to automated systems and complicated cases to human adjusters.
Resolution
For simple claims, AI can approve and process payments. Complex cases receive AI-generated summaries and recommendations for human adjusters to review.
Platforms like Roots AI report 98%+ accuracy in automated premium audits. Their platform automates ACORD forms, provides efficient renewals with automated monitoring, and sends underwriter notifications for policies requiring attention.
Will AI Replace Insurance Agents?
The Short Answer: No, But Transformation is Underway
According to Insurance News Net, a 2025 Insurance Labor Market Study found that 55% of American insurance companies plan to hire more staff over the next 12 months, primarily in life and health insurance (60%). The largest growth is projected in technology, underwriting, and claims—not layoffs.
According to McKinsey's 2025 Insurance Outlook, roughly 25% of the insurance industry's total workforce tasks are now automated via AI—though that percentage is heavily skewed toward high-volume, standard lines.
What AI Automates
- After-hours calls via AI receptionists and voice bots
- Lead routing to the appropriate agent automatically
- Renewal reminders with smart timing notifications
- Data entry and document processing
- Simple policy questions and FAQs
Why Humans Remain Essential
- Complex claims involving emotional situations
- Building long-term client trust and relationships
- Legal liability—machines cannot be held accountable in court
- Advocacy during catastrophic claims
- Complex problem-solving requiring judgment
Key Insight
According to Strada's analysis, having a human agent handle complex issues increases customer retention by 6x compared to automated handling. The agent of record remains a legally mandated, human-centric role because a machine cannot be held liable in court, nor can it provide the “gut-feeling” advocacy required during catastrophic claims.
The future model is human + AI collaboration. According to Kommunicate, in the traditional model, revenue growth is linear—to handle 20% more clients, you need 20% more staff. In the hybrid AI model, revenue becomes decoupled from headcount, allowing for exponential scaling on a flat cost base.
AI Trading Agents and Investment
AI agents stocks and algorithmic trading represent one of the fastest-growing applications in finance. According to Tickeron, the AI trading market is projected to reach $75.5 billion by 2034, growing at 20.7% annually.
AI TRADING BOT PERFORMANCE (2025 DATA)
Source: Tickeron AI Trading Report. Past performance does not guarantee future results.
Top AI Trading Platforms for Finance
Trade Ideas
AI-powered scanner using machine learning to identify real-time trading opportunities. Their “Holly AI” analyzes millions of trade scenarios nightly to generate high-probability setups.
Best for: Day tradersQuantConnect
Open-source algorithmic trading platform for building, backtesting, and deploying strategies across multiple asset classes using Python or C#. Powers institutional-grade backtesting.
Best for: DevelopersAlpaca
Developer-focused platform offering commission-free trading via API, perfect for building custom trading bots without hefty infrastructure investment.
Best for: API integration3Commas
User-friendly platform offering both simple and advanced trading bots. Their dollar-cost averaging bots are particularly popular among long-term investors.
Best for: BeginnersAI Wealth Management and Robo-Advisors
According to Alpha AI Capital, over $1 trillion in assets is now managed globally by robo-advisor firms. The AI wealth management market is projected to grow at a CAGR of over 25% through 2030.
| Platform | Key Feature | Minimum |
|---|---|---|
| Wealthfront | Direct indexing, tax-loss harvesting | $500 |
| Betterment | Goal-based investing, portfolio rebalancing | $0 |
| Fidelity Go | Free management under $25k | $10 |
| PortfolioPilot | Fully AI-powered, $20B AUM | $0 |
Important: AI trading tools should be treated as a co-pilot, not a fiduciary. Markets are dynamic and influenced by unpredictable factors. Past performance does not guarantee future results.
Customer Service AI in Banking
AI chatbots and virtual assistants have become standard in banking, handling up to 50% of customer inquiries. According to MosaicX, these AI systems provide 24/7 support for daily financial needs including transaction history, account information, loan applications, and opening new accounts.
Leading Bank AI Assistants
Bank of America — Erica
AI-powered virtual financial assistant with over 20 million active users and 2.5+ billion client interactions since 2018. Offers personalized insights, duplicate charge alerts, bill reminders, and lost card replacement.
Capital One — Eno
Conversational AI assistant available 24/7 for credit card holders. Automatically messages customers about suspicious transactions and can generate virtual credit card numbers for secure online shopping.
HSBC — AI Assistant
Handles over 10 million chat conversations per year. Uses natural language processing to understand customer queries and provide tailored responses, reducing wait times significantly.
According to the Consumer Financial Protection Bureau, chatbots are programmed to resolve specific tasks but sometimes struggle with distressed customers. When customers face financial anxiety or complex situations, escalation to human agents remains critical for maintaining trust.
Regulatory Compliance and RegTech
Regulatory compliance is a critical application for AI agents in finance. According to SymphonyAI, the global RegTech market is projected to grow from $16 billion in 2025 to $62 billion by 2032—a CAGR of 21.3%.
Growing at 21.3% CAGR
HSBC ML platform results
Key AI Compliance Applications
KYC/AML Automation
AI agents automate client onboarding, KYC checks, transaction monitoring, and sanctions screening with human oversight for final decisions.
Regulatory Reporting
Barclays reduced regulatory document processing time from days to minutes using AI-powered analysis. Automated preparation of filings for Bank Secrecy Act, Dodd-Frank, and SOX requirements.
Policy Monitoring
AI agents continuously audit underwriting and claims for compliance, flagging issues proactively before regulators identify them.
According to Fintech Global, regulators worldwide are converging on the same fundamental questions: Can you explain your AI? Can you prove it is fair? Can you control it? The EU AI Act is setting the tone, with similar risk-based frameworks expected globally. Human-in-the-loop oversight has become a regulatory expectation, not just a best practice.
Case Studies: Real-World Results
Here are documented results from financial institutions deploying AI agents for finance at scale:
DBS Bank — $750 Million in AI Value
Singapore's DBS Bank created $750 million in economic value from AI in 2024, with fraud detection being a key component of their 1,500+ AI models deployed across 370 use cases. Their comprehensive AI strategy spans customer service, risk management, and operational efficiency.
JPMorgan Chase — 50% False Positive Reduction
After adopting AI for fraud detection, JPMorgan Chase reduced false positives by 50% and improved fraud detection accuracy by 25%. This dual improvement—catching more real fraud while bothering fewer legitimate customers—demonstrates the power of modern AI agents in balancing security and customer experience.
Mastercard — 300% Fraud Detection Improvement
Mastercard deployed a RAG-enabled voice scam detection system in 2024, achieving a 300% boost in fraud detection rates. This demonstrates how retrieval-augmented generation (RAG) can dramatically improve AI agent performance in real-time fraud scenarios.
Barclays — Days to Minutes Processing
Barclays reduced regulatory document processing time from days to minutes using AI-powered analysis. Combined with JPMorgan's blockchain settlement system maintaining compliance across multiple jurisdictions simultaneously, this shows the transformative potential of AI in compliance operations.
Related Articles
Frequently Asked Questions
Will AI replace insurance agents?
No, AI will not fully replace insurance agents. A 2025 Insurance Labor Market Study found that 55% of American insurance companies plan to hire more staff. AI automates routine tasks like data entry and claims triage, but human agents remain essential for complex cases, emotional situations, and building client trust. Having a human agent handle complex issues increases retention by 6x. The future is a hybrid model where AI handles administrative work while agents focus on relationships and complex problem-solving.
How are AI agents used for fraud detection in banking?
AI agents detect fraud by analyzing millions of transactions in real-time using machine learning algorithms and pattern recognition. 91% of US banks now use AI for fraud detection. JPMorgan Chase reduced false positives by 50% and improved detection by 25% using AI. Mastercard achieved a 300% boost in fraud detection rates with their RAG-enabled system. AI agents identify anomalies, impersonation attempts, and money laundering patterns that would be impossible for humans to catch at scale.
What is the market size for AI agents in financial services?
The AI agents in financial services market reached $1.79 billion in 2025 and is projected to grow to $6.54 billion by 2035, representing a CAGR of 13.84%. North America dominates with 46% market share. The banks segment holds 40.5% of the market, with fraud detection agents accounting for 33.4% of global revenue. Insurance analytics is growing at 15.64% CAGR, reaching $31.76 billion by 2031.
Can AI trading bots really beat the market?
AI trading bots have shown impressive returns in 2025, with some achieving annualized returns between 43% and 362%. However, past performance does not guarantee future results. Markets are dynamic and influenced by unpredictable factors like geopolitical events. Experts recommend treating AI trading tools as a co-pilot rather than a fully autonomous system. The AI trading market is projected to reach $75.5 billion by 2034, indicating strong institutional confidence.
What are the regulatory considerations for AI in finance?
Financial institutions must comply with frameworks like the EU AI Act, Bank Secrecy Act, Dodd-Frank, SOX, DORA, and upcoming AMLA regulations. Key requirements include explainable AI, fairness audits, and human-in-the-loop oversight. The RegTech market is growing from $16 billion in 2025 to $62 billion by 2032 to help manage these requirements. Regulators worldwide are converging on questions about AI transparency, fairness, and control.
Conclusion: The Future of AI Agents in Finance
AI agents in finance are no longer experimental—they are deployed at scale across the world's largest financial institutions, delivering measurable results in fraud detection, claims processing, customer service, and regulatory compliance.
The data is clear: 91% of US banks use AI for fraud detection, DBS Bank has created $750 million in AI value, and the market is projected to reach $6.54 billion by 2035. For insurance, AI will not replace agents but will transform their roles—automating routine tasks while elevating human skills like empathy and complex problem-solving.
Financial institutions that embrace AI agents today are positioning themselves for a competitive advantage. Those that delay risk falling behind as the technology matures and customer expectations shift toward the instant, personalized service that AI enables.
Ready to Implement AI Agents?
Explore how Planetary Labour can help your financial institution deploy AI agents for fraud detection, customer service, and operational efficiency.
Learn MoreSources
- Precedence Research — AI Agents in Financial Services Market
- IBM — AI Fraud Detection in Banking
- McKinsey — How Agentic AI Can Change the Way Banks Fight Financial Crime
- Feedzai — AI Fraud Trends 2025
- Deloitte — Deepfake Banking Fraud Risk
- Insurance News Net — Is AI Replacing Insurance Agents?
- McKinsey — The Future of AI in the Insurance Industry
- V7 Labs — AI in Insurance Use Cases
- Tickeron — AI Trading Revolution
- SymphonyAI — 2025 RegTech Trends
- MosaicX — Examples of AI in Banking
- Xenoss — Real-time AI Fraud Detection in Banking