세계의 BFSI 분야 생성형 AI 시장 : 규모, 점유율, 성장 및 산업 분석, 유형별, 용도별, 지역별 인사이트 및 예측(2024-2032년)

Growth Factors of generative AI in BFSI Market

The global generative AI in BFSI market is witnessing rapid expansion as financial institutions increasingly adopt advanced artificial intelligence technologies to enhance efficiency, personalization, and regulatory compliance. In 2024, the global generative AI in BFSI market size was valued at USD 1.38 billion, reflecting early but accelerating adoption across banking, financial services, and insurance organizations. Generative AI in BFSI involves the use of advanced AI models to create, analyze, and optimize financial operations, including automated reporting, fraud detection, customer engagement, and risk assessment.

The market is projected to grow to USD 1.90 billion in 2025, supported by rising investments in digital transformation and increasing collaboration between financial institutions and technology providers. By 2032, the generative AI in BFSI market value is expected to reach USD 13.57 billion, demonstrating a strong growth trajectory as AI-driven automation becomes integral to core financial operations.

In 2024, North America dominated the global generative AI in BFSI market, accounting for 40.57% of the total market share. This dominance is attributed to the region's advanced digital infrastructure, early adoption of AI technologies, and strong presence of major technology and consulting firms.

Market Drivers and Growth Factors

A key driver of the generative AI in BFSI market is the increasing need for operational efficiency and cost reduction among financial institutions. Banks and insurers manage massive volumes of data and transactions daily. Generative AI automates routine processes such as data entry, compliance reporting, and documentation, significantly reducing manual effort and operational expenses. AI-driven systems also enhance the speed and accuracy of data processing, enabling institutions to scale operations efficiently.

Another major growth factor is the rising demand for enhanced customer service and personalization. AI-powered chatbots and virtual assistants leverage natural language processing and generative models to provide real-time, personalized customer interactions. These tools handle inquiries, offer financial advice, and recommend customized products, improving customer satisfaction and loyalty.

Additionally, generative AI supports risk management and compliance by continuously monitoring transactions and operations to ensure adherence to regulatory standards. Automated compliance reporting reduces errors and minimizes regulatory risks, which is increasingly critical in highly regulated financial environments.

Market Trends

One of the most prominent trends in the generative AI in BFSI market is the use of AI for personalized financial products and services. Financial institutions are deploying generative AI to design customized insurance policies, investment portfolios, and lending products based on individual customer profiles and preferences.

Another important trend is the application of generative AI in fraud detection and scenario simulation. AI models analyze transaction patterns in real time and generate synthetic data to simulate fraud scenarios, helping institutions stay ahead of evolving threats. These capabilities are strengthening trust and security across financial ecosystems.

Furthermore, generative AI is being used to innovate new financial products, such as dynamic pricing models in insurance and advanced algorithmic trading strategies, which further expands its adoption across BFSI organizations.

Market Restraints

Despite strong growth prospects, the market faces challenges related to data security and privacy concerns. Financial institutions handle highly sensitive personal and transactional data, and the use of AI introduces potential cybersecurity vulnerabilities. Ensuring robust data protection and system security requires substantial investment, which may restrain adoption in some institutions.

Another restraint is the shortage of skilled professionals with expertise in AI, machine learning, and data science. Recruiting and training talent capable of managing generative AI systems requires time and resources, which can slow implementation.

Segmentation Insights

By application, the fraud detection segment held the largest market share in 2024, driven by the need for real-time identification and prevention of fraudulent activities. Generative AI continuously learns from new data, improving detection accuracy over time.

The algorithmic trading segment is expected to grow at the highest rate through 2032, as AI-driven automation reduces human error, optimizes trade execution, and lowers transaction costs.

By end user, the banks segment dominated the market in 2024, supported by extensive adoption of AI-powered chatbots, virtual assistants, and personalized advisory tools. Meanwhile, financial service providers are expected to witness the fastest growth, driven by increasing use of AI for risk assessment and compliance automation.

Regional Outlook

North America reached a generative AI in BFSI market size of USD 0.56 billion in 2024, maintaining its leadership position. Asia Pacific is projected to grow at the fastest rate through 2032, driven by fintech innovation hubs and supportive regulatory frameworks. Europe is also expected to experience strong growth, supported by partnerships between traditional banks and fintech companies and increased investment in AI research.

Competitive Landscape

Leading players such as Accenture, Microsoft, IBM, NVIDIA, Salesforce, OpenAI, SAS Institute, and DataRobot are strengthening their market presence through partnerships, acquisitions, and continuous product innovation. With the market expanding from USD 1.38 billion in 2024 to USD 13.57 billion by 2032, generative AI is set to become a transformative force across the global BFSI industry.

Segmentation By Application

• Fraud Detection
• Risk Assessment
• Customer Experience
• Algorithmic Trading
• Others (Portfolio Optimization)

By End-User

• Banks
• Insurance Companies
• Financial Service Providers

By Region

• North America (By Application, End-User, and Country)
  • U.S.
  • Canada
  • Mexico
• South America (By Application, End-User, and Country)
  • Brazil
  • Argentina
  • Rest of South America
• Europe (By Application, End-User, and Country)
  • U.K.
  • Germany
  • France
  • Italy
  • Spain
  • Russia
  • Benelux
  • Nordics
  • Rest of Europe
• Middle East & Africa (By Application, End-User, and Country)
  • Turkey
  • Israel
  • GCC
  • North Africa
  • South Africa
  • Rest of the Middle East & Africa
• Asia Pacific (By Application, End-User, and Country)
  • China
  • India
  • Japan
  • South Korea
  • ASEAN
  • Oceania
  • Rest of Asia Pacific

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

4. Competition Landscape

• 4.1. Business Strategies Adopted by Key Players
• 4.2. Consolidated SWOT Analysis of Key Players
• 4.3. Global Generative AI in BFSI Key Players Market Share/Ranking, 2024

5. Global Generative AI in BFSI Market Size Estimates and Forecasts, By Segments, 2022-2032

• 5.1. Key Findings
• 5.2. By Application (USD)
  • 5.2.1. Fraud Detection
  • 5.2.2. Risk Assessment
  • 5.2.3. Customer Experience
  • 5.2.4. Algorithmic Trading
  • 5.2.5. Others (Portfolio Optimization, etc.)
• 5.3. By End User (USD)
  • 5.3.1. Banks
  • 5.3.2. Insurance Companies
  • 5.3.3. Financial Service Providers
• 5.4. By Region (USD)
  • 5.4.1. North America
  • 5.4.2. South America
  • 5.4.3. Europe
  • 5.4.4. Middle East & Africa
  • 5.4.5. Asia Pacific

6. North America Generative AI in BFSI Market Size Estimates and Forecasts, By Segments, 2022-2032

• 6.1. Key Findings
• 6.2. By Application (USD)
  • 6.2.1. Fraud Detection
  • 6.2.2. Risk Assessment
  • 6.2.3. Customer Experience
  • 6.2.4. Algorithmic Trading
  • 6.2.5. Others (Portfolio Optimization, etc.)
• 6.3. By End User (USD)
  • 6.3.1. Banks
  • 6.3.2. Insurance Companies
  • 6.3.3. Financial Service Providers
• 6.4. By Country (USD)
  • 6.4.1. United States
  • 6.4.2. Canada
  • 6.4.3. Mexico

7. South America Generative AI in BFSI Market Size Estimates and Forecasts, By Segments, 2022-2032

• 7.1. Key Findings
• 7.2. By Application (USD)
  • 7.2.1. Fraud Detection
  • 7.2.2. Risk Assessment
  • 7.2.3. Customer Experience
  • 7.2.4. Algorithmic Trading
  • 7.2.5. Others (Portfolio Optimization, etc.)
• 7.3. By End User (USD)
  • 7.3.1. Banks
  • 7.3.2. Insurance Companies
  • 7.3.3. Financial Service Providers
• 7.4. By Country (USD)
  • 7.4.1. Brazil
  • 7.4.2. Argentina
  • 7.4.3. Rest of South America

8. Europe Generative AI in BFSI Market Size Estimates and Forecasts, By Segments, 2022-2032

• 8.1. Key Findings
• 8.2. By Application (USD)
  • 8.2.1. Fraud Detection
  • 8.2.2. Risk Assessment
  • 8.2.3. Customer Experience
  • 8.2.4. Algorithmic Trading
  • 8.2.5. Others (Portfolio Optimization, etc.)
• 8.3. By End User (USD)
  • 8.3.1. Banks
  • 8.3.2. Insurance Companies
  • 8.3.3. Financial Service Providers
• 8.4. By Country (USD)
  • 8.4.1. United Kingdom
  • 8.4.2. Germany
  • 8.4.3. France
  • 8.4.4. Italy
  • 8.4.5. Spain
  • 8.4.6. Russia
  • 8.4.7. Benelux
  • 8.4.8. Nordics
  • 8.4.9. Rest of Europe

9. Middle East & Africa Generative AI in BFSI Market Size Estimates and Forecasts, By Segments, 2022-2032

• 9.1. Key Findings
• 9.2. By Application (USD)
  • 9.2.1. Fraud Detection
  • 9.2.2. Risk Assessment
  • 9.2.3. Customer Experience
  • 9.2.4. Algorithmic Trading
  • 9.2.5. Others (Portfolio Optimization, etc.)
• 9.3. By End User (USD)
  • 9.3.1. Banks
  • 9.3.2. Insurance Companies
  • 9.3.3. Financial Service Providers
• 9.4. By Country (USD)
  • 9.4.1. Turkey
  • 9.4.2. Israel
  • 9.4.3. GCC
  • 9.4.4. North Africa
  • 9.4.5. South Africa
  • 9.4.6. Rest of MEA

10. Asia Pacific Generative AI in BFSI Market Size Estimates and Forecasts, By Segments, 2022-2032

• 10.1. Key Findings
• 10.2. By Application (USD)
  • 10.2.1. Fraud Detection
  • 10.2.2. Risk Assessment
  • 10.2.3. Customer Experience
  • 10.2.4. Algorithmic Trading
  • 10.2.5. Others (Portfolio Optimization, etc.)
• 10.3. By End User (USD)
  • 10.3.1. Banks
  • 10.3.2. Insurance Companies
  • 10.3.3. Financial Service Providers
• 10.4. By Country (USD)
  • 10.4.1. China
  • 10.4.2. India
  • 10.4.3. Japan
  • 10.4.4. South Korea
  • 10.4.5. ASEAN
  • 10.4.6. Oceania
  • 10.4.7. 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. Accenture
  • 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
• 11.2. SAS Institute, Inc.
  • 11.2.1. Overview
    • 11.2.1.1. Key Management
    • 11.2.1.2. Headquarters
    • 11.2.1.3. Offerings/Business Segments
  • 11.2.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.2.2.1. Employee Size
    • 11.2.2.2. Past and Current Revenue
    • 11.2.2.3. Geographical Share
    • 11.2.2.4. Business Segment Share
    • 11.2.2.5. Recent Developments
• 11.3. Quantifind
  • 11.3.1. Overview
    • 11.3.1.1. Key Management
    • 11.3.1.2. Headquarters
    • 11.3.1.3. Offerings/Business Segments
  • 11.3.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.3.2.1. Employee Size
    • 11.3.2.2. Past and Current Revenue
    • 11.3.2.3. Geographical Share
    • 11.3.2.4. Business Segment Share
    • 11.3.2.5. Recent Developments
• 11.4. Microsoft
  • 11.4.1. Overview
    • 11.4.1.1. Key Management
    • 11.4.1.2. Headquarters
    • 11.4.1.3. Offerings/Business Segments
  • 11.4.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.4.2.1. Employee Size
    • 11.4.2.2. Past and Current Revenue
    • 11.4.2.3. Geographical Share
    • 11.4.2.4. Business Segment Share
    • 11.4.2.5. Recent Developments
• 11.5. OpenAI
  • 11.5.1. Overview
    • 11.5.1.1. Key Management
    • 11.5.1.2. Headquarters
    • 11.5.1.3. Offerings/Business Segments
  • 11.5.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.5.2.1. Employee Size
    • 11.5.2.2. Past and Current Revenue
    • 11.5.2.3. Geographical Share
    • 11.5.2.4. Business Segment Share
    • 11.5.2.5. Recent Developments
• 11.6. DataRobot, Inc.
  • 11.6.1. Overview
    • 11.6.1.1. Key Management
    • 11.6.1.2. Headquarters
    • 11.6.1.3. Offerings/Business Segments
  • 11.6.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.6.2.1. Employee Size
    • 11.6.2.2. Past and Current Revenue
    • 11.6.2.3. Geographical Share
    • 11.6.2.4. Business Segment Share
    • 11.6.2.5. Recent Developments
• 11.7. NVIDIA Corporation
  • 11.7.1. Overview
    • 11.7.1.1. Key Management
    • 11.7.1.2. Headquarters
    • 11.7.1.3. Offerings/Business Segments
  • 11.7.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.7.2.1. Employee Size
    • 11.7.2.2. Past and Current Revenue
    • 11.7.2.3. Geographical Share
    • 11.7.2.4. Business Segment Share
    • 11.7.2.5. Recent Developments
• 11.8. Google LLC
  • 11.8.1. Overview
    • 11.8.1.1. Key Management
    • 11.8.1.2. Headquarters
    • 11.8.1.3. Offerings/Business Segments
  • 11.8.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.8.2.1. Employee Size
    • 11.8.2.2. Past and Current Revenue
    • 11.8.2.3. Geographical Share
    • 11.8.2.4. Business Segment Share
    • 11.8.2.5. Recent Developments
• 11.9. IBM Corporation
  • 11.9.1. Overview
    • 11.9.1.1. Key Management
    • 11.9.1.2. Headquarters
    • 11.9.1.3. Offerings/Business Segments
  • 11.9.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.9.2.1. Employee Size
    • 11.9.2.2. Past and Current Revenue
    • 11.9.2.3. Geographical Share
    • 11.9.2.4. Business Segment Share
    • 11.9.2.5. Recent Developments
• 11.10. Salesforce, Inc.
  • 11.10.1. Overview
    • 11.10.1.1. Key Management
    • 11.10.1.2. Headquarters
    • 11.10.1.3. Offerings/Business Segments
  • 11.10.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.10.2.1. Employee Size
    • 11.10.2.2. Past and Current Revenue
    • 11.10.2.3. Geographical Share
    • 11.10.2.4. Business Segment Share
    • 11.10.2.5. Recent Developments

12. Key Takeaways