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Industry Research
AI Fraud Detection in Banking Industry Research Report 2026
Market perspective
The global AI Fraud Detection in Banking market was valued at US$ million in 2025 and is projected to reach US$ million by 2032, implying a CAGR of % over 2026–2032.
North America: the AI Fraud Detection in Banking market is projected to increase from US$ million in 2026 to US$ million by 2032, reflecting a CAGR of % over 2026–2032. Europe: the AI Fraud Detection in Banking market is projected to rise from US$ million in 2026 to US$ million by 2032, registering a CAGR of % over 2026–2032. Asia Pacific: the AI Fraud Detection in Banking market is expected to grow from US$ million in 2026 to US$ million by 2032, at a CAGR of % over 2026–2032. Leading global service providers of AI Fraud Detection in Banking include Eastnets, Feedzai, Resistant AI, NetGuardians, ADVANCE, Sift, Fraud.net, SEON and Sardine, among others; in 2025, the top three vendors together accounted for approximately % of global revenue.
Report Scope
Read the full market overview
This report quantifies the global AI Fraud Detection in Banking market in terms of revenue (US$ million) and, where applicable, service volume (k units), using 2024 as the base year and providing annual historical and forecast data for 2021–2032.
It standardizes definitions of service Types and end-use Applications, harmonizes provider attribution, and delivers comparable time series by company, Type, Application, and region or country, including indicative price bands (US$/k units) and concentration ratios (CR5/CR10). Outputs are intended to support service design, budgeting, capacity planning, and benchmarking for providers, platforms, channel partners, and investors; the report also reviews technology shifts and notable service innovations relevant to AI Fraud Detection in Banking.
Key Companies & Market Share Insights
This section profiles leading service providers with 2021–2025 results and a 2026–2032 outlook—covering revenue, market share, price bands, service portfolio and client mix, regional and channel mix, and key developments (M&A, network expansion, certifications). It also provides global revenue, average price, and—where applicable—volume metrics by provider, and calculates CR5/CR10 and rank changes to support comparative benchmarking.
AI Fraud Detection in Banking Market by Company
Eastnets
Feedzai
Resistant AI
NetGuardians
ADVANCE
Sift
Fraud.net
SEON
Sardine
Mastercard Consumer Fraud Risk
Cifas
GFT
Hawk
SymphonyAI
SB Payment Service
KPMG
NICE Actimize
DataVisor
4Paradigm
Shanghai Shengteng Data Technology
Iflytek
AI Fraud Detection in Banking Segment by Type
Supervised Learning-based Fraud Detection
Unsupervised Learning-based Fraud Detection
AI Fraud Detection in Banking Segment by Application
Real-Time Transaction Monitoring
Credit Card & Payment Fraud Prevention
Identity Verification & Biometric Authentication
Others
AI Fraud Detection in Banking Segment by Region
North America
United States
Canada
Mexico
Europe
Germany
France
U.K.
Italy
Spain
Russia
Netherlands
Nordic Countries
Asia-Pacific
China
Japan
South Korea
India
Australia
Taiwan
Southeast Asia
South America
Brazil
Argentina
Chile
Middle East & Africa
Saudi Arabia
Israel
United Arab Emirates
Turkey
Iran
Egypt
Key Drivers & Barriers
High-impact rendering factors and drivers have been studied in this report to aid the readers to understand the general development. Moreover, the report includes restraints and challenges that may act as stumbling blocks on the way of the players. This will assist the users to be attentive and make informed decisions related to business. Specialists have also laid their focus on the upcoming business prospects.
Reasons to Buy This Report
1. This report will help the readers to understand the competition within the industries and strategies for the competitive environment to enhance the potential profit. The report also focuses on the competitive landscape of the global AI Fraud Detection in Banking market, and introduces in detail the market share, industry ranking, competitor ecosystem, market performance, new product development, operation situation, expansion, and acquisition. etc. of the main players, which helps the readers to identify the main competitors and deeply understand the competition pattern of the market.
2. This report will help stakeholders to understand the global industry status and trends of AI Fraud Detection in Banking and provides them with information on key market drivers, restraints, challenges, and opportunities.
3. This report will help stakeholders to understand competitors better and gain more insights to strengthen their position in their businesses. The competitive landscape section includes the market share and rank (in volume and value), competitor ecosystem, new product development, expansion, and acquisition.
4. This report stays updated with novel technology integration, features, and the latest developments in the market
5. This report helps stakeholders to gain insights into which regions to target globally
6. This report helps stakeholders to gain insights into the end-user perception concerning the adoption of AI Fraud Detection in Banking.
7. This report helps stakeholders to identify some of the key players in the market and understand their valuable contribution.
Chapter Outline
Chapter 1: Research objectives, research methods, data sources, data cross-validation;
Chapter 2: Introduces the report scope of the report, executive summary of different market segments (product type, application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 3: Provides the analysis of various market segments product types, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 6: Detailed analysis of AI Fraud Detection in Banking companies’ competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 7, 8, 9, 10, 11: North America, Europe, Asia Pacific, South America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 12: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including revenue, gross margin, product introduction, recent development, etc.
Chapter 13: The main points and conclusions of the report.
More report detail
Tables and figures
Scope & coverage.
Types
- Supervised Learning-based Fraud Detection
- Unsupervised Learning-based Fraud Detection
Applications
- Real-Time Transaction Monitoring
- Credit Card & Payment Fraud Prevention
- Identity Verification & Biometric Authentication
- Others
Companies covered
- Eastnets
- Feedzai
- Resistant AI
- NetGuardians
- ADVANCE
- Sift
- Fraud.net
- SEON
- Sardine
- Mastercard Consumer Fraud Risk
- Cifas
- GFT
- Hawk
- SymphonyAI
- SB Payment Service
- KPMG
- NICE Actimize
- DataVisor
- 4Paradigm
- Shanghai Shengteng Data Technology
- Iflytek
Inside the report.
1 Preface
- 1.1 Scope of Report
- 1.2 Reasons for Doing This Study
- 1.3 Research Methodology
- 1.4 Research Process
- 1.5 Data Source
- 1.5.1 Secondary Sources
- 1.5.2 Primary Sources
2 Market Overview
- 2.1 Product Definition
- 2.2 AI Fraud Detection in Banking by Type
- 2.2.1 Market Value Comparison by Type (2021 VS 2025 VS 2032)
- 2.2.2 Supervised Learning-based Fraud Detection
- 2.2.3 Unsupervised Learning-based Fraud Detection
- 2.3 AI Fraud Detection in Banking by Application
- 2.3.1 Market Value Comparison by Application (2021 VS 2025 VS 2032)
- 2.3.2 Real-Time Transaction Monitoring
- 2.3.3 Credit Card & Payment Fraud Prevention
- 2.3.4 Identity Verification & Biometric Authentication
- 2.3.5 Others
- 2.4 Assumptions and Limitations
3 AI Fraud Detection in Banking Breakdown Data by Type
- 3.1 Global AI Fraud Detection in Banking Historic Market Size by Type (2021-2026)
- 3.2 Global AI Fraud Detection in Banking Forecasted Market Size by Type (2027-2032)
4 AI Fraud Detection in Banking Breakdown Data by Application
- 4.1 Global AI Fraud Detection in Banking Historic Market Size by Application (2021-2026)
- 4.2 Global AI Fraud Detection in Banking Forecasted Market Size by Application (2027-2032)
5 Global Growth Trends
- 5.1 Global AI Fraud Detection in Banking Market Perspective (2021-2032)
- 5.2 Global AI Fraud Detection in Banking Growth Trends by Region
- 5.2.1 Global AI Fraud Detection in Banking Market Size by Region: 2021 VS 2025 VS 2032
- 5.2.2 AI Fraud Detection in Banking Historic Market Size by Region (2021-2026)
- 5.2.3 AI Fraud Detection in Banking Forecasted Market Size by Region (2027-2032)
- 5.3 AI Fraud Detection in Banking Market Dynamics
- 5.3.1 AI Fraud Detection in Banking Industry Trends
- 5.3.2 AI Fraud Detection in Banking Market Drivers
- 5.3.3 AI Fraud Detection in Banking Market Challenges
- 5.3.4 AI Fraud Detection in Banking Market Restraints
6 Market Competitive Landscape by Players
- 6.1 Global Top AI Fraud Detection in Banking Players by Revenue
- 6.1.1 Global Top AI Fraud Detection in Banking Players by Revenue (2021-2026)
- 6.1.2 Global AI Fraud Detection in Banking Revenue Market Share by Players (2021-2026)
- 6.2 Global AI Fraud Detection in Banking Industry Players Ranking, 2023 VS 2024 VS 2025
- 6.3 Global Key Players of AI Fraud Detection in Banking Head Office and Area Served
- 6.4 Global AI Fraud Detection in Banking Players, Product Type & Application
- 6.5 Global AI Fraud Detection in Banking Manufacturers Established Date
- 6.6 Global AI Fraud Detection in Banking Market CR5 and HHI
- 6.7 Global Players Mergers & Acquisition
7 North America
- 7.1 North America AI Fraud Detection in Banking Market Size (2021-2032)
- 7.2 North America AI Fraud Detection in Banking Market Growth Rate by Country: 2021 VS 2025 VS 2032
- 7.3 North America AI Fraud Detection in Banking Market Size by Country (2021-2026)
- 7.4 North America AI Fraud Detection in Banking Market Size by Country (2027-2032)
- 7.5 United States
- 7.5 United States
- 7.6 Canada
- 7.7 Mexico
8 Europe
- 8.1 Europe AI Fraud Detection in Banking Market Size (2021-2032)
- 8.2 Europe AI Fraud Detection in Banking Market Growth Rate by Country: 2021 VS 2025 VS 2032
- 8.3 Europe AI Fraud Detection in Banking Market Size by Country (2021-2026)
- 8.4 Europe AI Fraud Detection in Banking Market Size by Country (2027-2032)
- 8.5 Germany
- 8.6 France
- 8.7 U.K.
- 8.8 Italy
- 8.9 Spain
- 8.10 Russia
- 8.11 Netherlands
- 8.12 Nordic Countries
9 Asia-Pacific
- 9.1 Asia-Pacific AI Fraud Detection in Banking Market Size (2021-2032)
- 9.2 Asia-Pacific AI Fraud Detection in Banking Market Growth Rate by Country: 2021 VS 2025 VS 2032
- 9.3 Asia-Pacific AI Fraud Detection in Banking Market Size by Country (2021-2026)
- 9.4 Asia-Pacific AI Fraud Detection in Banking Market Size by Country (2027-2032)
- 9.5 China
- 9.6 Japan
- 9.7 South Korea
- 9.8 India
- 9.9 Australia
- 9.10 China Taiwan
- 9.11 Southeast Asia
10 South America
- 10.1 South America AI Fraud Detection in Banking Market Size (2021-2032)
- 10.2 South America AI Fraud Detection in Banking Market Growth Rate by Country: 2021 VS 2025 VS 2032
- 10.3 South America AI Fraud Detection in Banking Market Size by Country (2021-2026)
- 10.4 South America AI Fraud Detection in Banking Market Size by Country (2027-2032)
- 10.5 Brazil
- 10.6 Argentina
- 10.7 Chile
- 10.8 Colombia
- 10.9 Peru
11 Middle East & Africa
- 11.1 Middle East & Africa AI Fraud Detection in Banking Market Size (2021-2032)
- 11.2 Middle East & Africa AI Fraud Detection in Banking Market Growth Rate by Country: 2021 VS 2025 VS 2032
- 11.3 Middle East & Africa AI Fraud Detection in Banking Market Size by Country (2021-2026)
- 11.4 Middle East & Africa AI Fraud Detection in Banking Market Size by Country (2027-2032)
- 11.5 Saudi Arabia
- 11.6 Israel
- 11.7 United Arab Emirates
- 11.8 Turkey
- 11.9 Iran
- 11.10 Egypt
12 Players Profiled
- 12.1 Eastnets
- 12.1.1 Eastnets Company Information
- 12.1.2 Eastnets Business Overview
- 12.1.3 Eastnets Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.1.4 Eastnets AI Fraud Detection in Banking Product Portfolio
- 12.1.5 Eastnets Recent Developments
- 12.2 Feedzai
- 12.2.1 Feedzai Company Information
- 12.2.2 Feedzai Business Overview
- 12.2.3 Feedzai Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.2.4 Feedzai AI Fraud Detection in Banking Product Portfolio
- 12.2.5 Feedzai Recent Developments
- 12.3 Resistant AI
- 12.3.1 Resistant AI Company Information
- 12.3.2 Resistant AI Business Overview
- 12.3.3 Resistant AI Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.3.4 Resistant AI AI Fraud Detection in Banking Product Portfolio
- 12.3.5 Resistant AI Recent Developments
- 12.4 NetGuardians
- 12.4.1 NetGuardians Company Information
- 12.4.2 NetGuardians Business Overview
- 12.4.3 NetGuardians Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.4.4 NetGuardians AI Fraud Detection in Banking Product Portfolio
- 12.4.5 NetGuardians Recent Developments
- 12.5 ADVANCE
- 12.5.1 ADVANCE Company Information
- 12.5.2 ADVANCE Business Overview
- 12.5.3 ADVANCE Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.5.4 ADVANCE AI Fraud Detection in Banking Product Portfolio
- 12.5.5 ADVANCE Recent Developments
- 12.6 Sift
- 12.6.1 Sift Company Information
- 12.6.2 Sift Business Overview
- 12.6.3 Sift Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.6.4 Sift AI Fraud Detection in Banking Product Portfolio
- 12.6.5 Sift Recent Developments
- 12.7 Fraud.net
- 12.7.1 Fraud.net Company Information
- 12.7.2 Fraud.net Business Overview
- 12.7.3 Fraud.net Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.7.4 Fraud.net AI Fraud Detection in Banking Product Portfolio
- 12.7.5 Fraud.net Recent Developments
- 12.8 SEON
- 12.8.1 SEON Company Information
- 12.8.2 SEON Business Overview
- 12.8.3 SEON Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.8.4 SEON AI Fraud Detection in Banking Product Portfolio
- 12.8.5 SEON Recent Developments
- 12.9 Sardine
- 12.9.1 Sardine Company Information
- 12.9.2 Sardine Business Overview
- 12.9.3 Sardine Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.9.4 Sardine AI Fraud Detection in Banking Product Portfolio
- 12.9.5 Sardine Recent Developments
- 12.10 Mastercard Consumer Fraud Risk
- 12.10.1 Mastercard Consumer Fraud Risk Company Information
- 12.10.2 Mastercard Consumer Fraud Risk Business Overview
- 12.10.3 Mastercard Consumer Fraud Risk Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.10.4 Mastercard Consumer Fraud Risk AI Fraud Detection in Banking Product Portfolio
- 12.10.5 Mastercard Consumer Fraud Risk Recent Developments
- 12.11 Cifas
- 12.11.1 Cifas Company Information
- 12.11.2 Cifas Business Overview
- 12.11.3 Cifas Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.11.4 Cifas AI Fraud Detection in Banking Product Portfolio
- 12.11.5 Cifas Recent Developments
- 12.12 GFT
- 12.12.1 GFT Company Information
- 12.12.2 GFT Business Overview
- 12.12.3 GFT Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.12.4 GFT AI Fraud Detection in Banking Product Portfolio
- 12.12.5 GFT Recent Developments
- 12.13 Hawk
- 12.13.1 Hawk Company Information
- 12.13.2 Hawk Business Overview
- 12.13.3 Hawk Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.13.4 Hawk AI Fraud Detection in Banking Product Portfolio
- 12.13.5 Hawk Recent Developments
- 12.14 SymphonyAI
- 12.14.1 SymphonyAI Company Information
- 12.14.2 SymphonyAI Business Overview
- 12.14.3 SymphonyAI Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.14.4 SymphonyAI AI Fraud Detection in Banking Product Portfolio
- 12.14.5 SymphonyAI Recent Developments
- 12.15 SB Payment Service
- 12.15.1 SB Payment Service Company Information
- 12.15.2 SB Payment Service Business Overview
- 12.15.3 SB Payment Service Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.15.4 SB Payment Service AI Fraud Detection in Banking Product Portfolio
- 12.15.5 SB Payment Service Recent Developments
- 12.16 KPMG
- 12.16.1 KPMG Company Information
- 12.16.2 KPMG Business Overview
- 12.16.3 KPMG Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.16.4 KPMG AI Fraud Detection in Banking Product Portfolio
- 12.16.5 KPMG Recent Developments
- 12.17 NICE Actimize
- 12.17.1 NICE Actimize Company Information
- 12.17.2 NICE Actimize Business Overview
- 12.17.3 NICE Actimize Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.17.4 NICE Actimize AI Fraud Detection in Banking Product Portfolio
- 12.17.5 NICE Actimize Recent Developments
- 12.18 DataVisor
- 12.18.1 DataVisor Company Information
- 12.18.2 DataVisor Business Overview
- 12.18.3 DataVisor Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.18.4 DataVisor AI Fraud Detection in Banking Product Portfolio
- 12.18.5 DataVisor Recent Developments
- 12.19 4Paradigm
- 12.19.1 4Paradigm Company Information
- 12.19.2 4Paradigm Business Overview
- 12.19.3 4Paradigm Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.19.4 4Paradigm AI Fraud Detection in Banking Product Portfolio
- 12.19.5 4Paradigm Recent Developments
- 12.20 Shanghai Shengteng Data Technology
- 12.20.1 Shanghai Shengteng Data Technology Company Information
- 12.20.2 Shanghai Shengteng Data Technology Business Overview
- 12.20.3 Shanghai Shengteng Data Technology Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.20.4 Shanghai Shengteng Data Technology AI Fraud Detection in Banking Product Portfolio
- 12.20.5 Shanghai Shengteng Data Technology Recent Developments
- 12.21 Iflytek
- 12.21.1 Iflytek Company Information
- 12.21.2 Iflytek Business Overview
- 12.21.3 Iflytek Revenue in AI Fraud Detection in Banking Business (2021-2026)
- 12.21.4 Iflytek AI Fraud Detection in Banking Product Portfolio
- 12.21.5 Iflytek Recent Developments
13 Report Conclusion
14 Disclaimer
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