Industry: Service & Software
Published Date: 2025-06-28
Pages: 102 Pages
Report ld: 4776560
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AI Fraud Detection in Banking Market Size(US$)

CAGR 2025-2031
12.0%
Market Size,2031
USD 3,373
Million
Market Snapshot
Source: Secondary research, interviews with experts, and QYResearch analysis
The global market for AI Fraud Detection in Banking was valued at US$ 1628 million in the year 2024 and is projected to reach a revised size of US$ 3373 million by 2031, growing at a CAGR of 12.0% during the forecast period.
AI Fraud Detection in Banking refers to the application of artificial intelligence techniques—such as machine learning, deep learning, and natural language processing—to identify and prevent fraudulent activities within banking and financial services. These systems analyze vast volumes of transaction data, user behavior, and contextual patterns to detect anomalies, predict potential fraud, and automate alerts in real time.
North American market for AI Fraud Detection in Banking is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
Asia-Pacific market for AI Fraud Detection in Banking is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The global market for AI Fraud Detection in Banking in Real-Time Transaction Monitoring is estimated to increase from $ million in 2024 to $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The major global companies of AI Fraud Detection in Banking include Eastnets, Feedzai, Resistant AI, NetGuardians, ADVANCE, Sift, Fraud.net, SEON, Sardine, Mastercard Consumer Fraud Risk, etc. In 2024, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for AI Fraud Detection in Banking, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding AI Fraud Detection in Banking.
The AI Fraud Detection in Banking market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. This report segments the global AI Fraud Detection in Banking market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the AI Fraud Detection in Banking companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
MARKET SEGMENTATION
CHAPTER OUTLINE
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by 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 2: 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 3: Detailed analysis of AI Fraud Detection in Banking company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by 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 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin 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 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
QYRESEARCH'S STRENGTHS
Unlike generic global market reports, this study combines macro-level industry trends with hyper-local operational intelligence, empowering data-driven decisions across the Compound Chocolate value chain, addressing:
We identify regional market threats and growth prospects to guide your overseas layout.
We adjust product portfolios in line with local consumption habits.
We unpack rivals’ operation strategies for scattered and highly concentrated industries.
We cover competition landscape, full supply chain and quantified market size data, and deliver tailor-made customized surveys to meet your unique business demands.
We own self-owned massive exclusive databases, backed by 19 years of global market research experience across thousands of sectors.
Our team operates 24 hours a day, 365 days a year, enabling ultra-fast report turnaround to respond to your research needs efficiently.
We integrate regional risk assessment, localized product optimization and competitor analysis to deliver actionable market strategies.
All data is cross-verified from multiple industry sources to deliver thorough, precise analysis that supports reliable corporate strategic decisions.
We provide responsive, dedicated after-sales support to resolve all follow-up inquiries about reports, data and industry interpretation.
TABLE OF CONTENTS
1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global AI Fraud Detection in Banking Market Size Growth Rate by Type: 2020 VS 2024 VS 2031
1.2.2 Supervised Learning-based Fraud Detection
1.2.3 Unsupervised Learning-based Fraud Detection
1.3 Market by Application
1.3.1 Global AI Fraud Detection in Banking Market Growth by Application: 2020 VS 2024 VS 2031
1.3.2 Real-Time Transaction Monitoring
1.3.3 Credit Card & Payment Fraud Prevention
1.3.4 Identity Verification & Biometric Authentication
1.3.5 Others
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Global Growth Trends
2.1 Global AI Fraud Detection in Banking Market Perspective (2020-2031)
2.2 Global AI Fraud Detection in Banking Growth Trends by Region
2.2.1 Global AI Fraud Detection in Banking Market Size by Region: 2020 VS 2024 VS 2031
2.2.2 AI Fraud Detection in Banking Historic Market Size by Region (2020-2025)
2.2.3 AI Fraud Detection in Banking Forecasted Market Size by Region (2026-2031)
2.3 AI Fraud Detection in Banking Market Dynamics
2.3.1 AI Fraud Detection in Banking Industry Trends
2.3.2 AI Fraud Detection in Banking Market Drivers
2.3.3 AI Fraud Detection in Banking Market Challenges
2.3.4 AI Fraud Detection in Banking Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top AI Fraud Detection in Banking Players by Revenue
3.1.1 Global Top AI Fraud Detection in Banking Players by Revenue (2020-2025)
3.1.2 Global AI Fraud Detection in Banking Revenue Market Share by Players (2020-2025)
3.2 Global Top AI Fraud Detection in Banking Players by Company Type and Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players Ranking by AI Fraud Detection in Banking Revenue
3.4 Global AI Fraud Detection in Banking Market Concentration Ratio
3.4.1 Global AI Fraud Detection in Banking Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by AI Fraud Detection in Banking Revenue in 2024
3.5 Global Key Players of AI Fraud Detection in Banking Head office and Area Served
3.6 Global Key Players of AI Fraud Detection in Banking, Product and Application
3.7 Global Key Players of AI Fraud Detection in Banking, Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 AI Fraud Detection in Banking Breakdown Data by Type
4.1 Global AI Fraud Detection in Banking Historic Market Size by Type (2020-2025)
4.2 Global AI Fraud Detection in Banking Forecasted Market Size by Type (2026-2031)
5 AI Fraud Detection in Banking Breakdown Data by Application
5.1 Global AI Fraud Detection in Banking Historic Market Size by Application (2020-2025)
5.2 Global AI Fraud Detection in Banking Forecasted Market Size by Application (2026-2031)
6 North America
6.1 North America AI Fraud Detection in Banking Market Size (2020-2031)
6.2 North America AI Fraud Detection in Banking Market Growth Rate by Country: 2020 VS 2024 VS 2031
6.3 North America AI Fraud Detection in Banking Market Size by Country (2020-2025)
6.4 North America AI Fraud Detection in Banking Market Size by Country (2026-2031)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe AI Fraud Detection in Banking Market Size (2020-2031)
7.2 Europe AI Fraud Detection in Banking Market Growth Rate by Country: 2020 VS 2024 VS 2031
7.3 Europe AI Fraud Detection in Banking Market Size by Country (2020-2025)
7.4 Europe AI Fraud Detection in Banking Market Size by Country (2026-2031)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Ireland
8 Asia-Pacific
8.1 Asia-Pacific AI Fraud Detection in Banking Market Size (2020-2031)
8.2 Asia-Pacific AI Fraud Detection in Banking Market Growth Rate by Region: 2020 VS 2024 VS 2031
8.3 Asia-Pacific AI Fraud Detection in Banking Market Size by Region (2020-2025)
8.4 Asia-Pacific AI Fraud Detection in Banking Market Size by Region (2026-2031)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia & New Zealand
9 Latin America
9.1 Latin America AI Fraud Detection in Banking Market Size (2020-2031)
9.2 Latin America AI Fraud Detection in Banking Market Growth Rate by Country: 2020 VS 2024 VS 2031
9.3 Latin America AI Fraud Detection in Banking Market Size by Country (2020-2025)
9.4 Latin America AI Fraud Detection in Banking Market Size by Country (2026-2031)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa AI Fraud Detection in Banking Market Size (2020-2031)
10.2 Middle East & Africa AI Fraud Detection in Banking Market Growth Rate by Country: 2020 VS 2024 VS 2031
10.3 Middle East & Africa AI Fraud Detection in Banking Market Size by Country (2020-2025)
10.4 Middle East & Africa AI Fraud Detection in Banking Market Size by Country (2026-2031)
10.5 Israel
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Eastnets
11.1.1 Eastnets Company Details
11.1.2 Eastnets Business Overview
11.1.3 Eastnets AI Fraud Detection in Banking Introduction
11.1.4 Eastnets Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.1.5 Eastnets Recent Development
11.2 Feedzai
11.2.1 Feedzai Company Details
11.2.2 Feedzai Business Overview
11.2.3 Feedzai AI Fraud Detection in Banking Introduction
11.2.4 Feedzai Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.2.5 Feedzai Recent Development
11.3 Resistant AI
11.3.1 Resistant AI Company Details
11.3.2 Resistant AI Business Overview
11.3.3 Resistant AI AI Fraud Detection in Banking Introduction
11.3.4 Resistant AI Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.3.5 Resistant AI Recent Development
11.4 NetGuardians
11.4.1 NetGuardians Company Details
11.4.2 NetGuardians Business Overview
11.4.3 NetGuardians AI Fraud Detection in Banking Introduction
11.4.4 NetGuardians Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.4.5 NetGuardians Recent Development
11.5 ADVANCE
11.5.1 ADVANCE Company Details
11.5.2 ADVANCE Business Overview
11.5.3 ADVANCE AI Fraud Detection in Banking Introduction
11.5.4 ADVANCE Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.5.5 ADVANCE Recent Development
11.6 Sift
11.6.1 Sift Company Details
11.6.2 Sift Business Overview
11.6.3 Sift AI Fraud Detection in Banking Introduction
11.6.4 Sift Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.6.5 Sift Recent Development
11.7 Fraud.net
11.7.1 Fraud.net Company Details
11.7.2 Fraud.net Business Overview
11.7.3 Fraud.net AI Fraud Detection in Banking Introduction
11.7.4 Fraud.net Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.7.5 Fraud.net Recent Development
11.8 SEON
11.8.1 SEON Company Details
11.8.2 SEON Business Overview
11.8.3 SEON AI Fraud Detection in Banking Introduction
11.8.4 SEON Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.8.5 SEON Recent Development
11.9 Sardine
11.9.1 Sardine Company Details
11.9.2 Sardine Business Overview
11.9.3 Sardine AI Fraud Detection in Banking Introduction
11.9.4 Sardine Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.9.5 Sardine Recent Development
11.10 Mastercard Consumer Fraud Risk
11.10.1 Mastercard Consumer Fraud Risk Company Details
11.10.2 Mastercard Consumer Fraud Risk Business Overview
11.10.3 Mastercard Consumer Fraud Risk AI Fraud Detection in Banking Introduction
11.10.4 Mastercard Consumer Fraud Risk Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.10.5 Mastercard Consumer Fraud Risk Recent Development
11.11 Cifas
11.11.1 Cifas Company Details
11.11.2 Cifas Business Overview
11.11.3 Cifas AI Fraud Detection in Banking Introduction
11.11.4 Cifas Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.11.5 Cifas Recent Development
11.12 GFT
11.12.1 GFT Company Details
11.12.2 GFT Business Overview
11.12.3 GFT AI Fraud Detection in Banking Introduction
11.12.4 GFT Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.12.5 GFT Recent Development
11.13 Hawk
11.13.1 Hawk Company Details
11.13.2 Hawk Business Overview
11.13.3 Hawk AI Fraud Detection in Banking Introduction
11.13.4 Hawk Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.13.5 Hawk Recent Development
11.14 SymphonyAI
11.14.1 SymphonyAI Company Details
11.14.2 SymphonyAI Business Overview
11.14.3 SymphonyAI AI Fraud Detection in Banking Introduction
11.14.4 SymphonyAI Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.14.5 SymphonyAI Recent Development
11.15 SB Payment Service
11.15.1 SB Payment Service Company Details
11.15.2 SB Payment Service Business Overview
11.15.3 SB Payment Service AI Fraud Detection in Banking Introduction
11.15.4 SB Payment Service Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.15.5 SB Payment Service Recent Development
11.16 KPMG
11.16.1 KPMG Company Details
11.16.2 KPMG Business Overview
11.16.3 KPMG AI Fraud Detection in Banking Introduction
11.16.4 KPMG Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.16.5 KPMG Recent Development
11.17 NICE Actimize
11.17.1 NICE Actimize Company Details
11.17.2 NICE Actimize Business Overview
11.17.3 NICE Actimize AI Fraud Detection in Banking Introduction
11.17.4 NICE Actimize Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.17.5 NICE Actimize Recent Development
11.18 DataVisor
11.18.1 DataVisor Company Details
11.18.2 DataVisor Business Overview
11.18.3 DataVisor AI Fraud Detection in Banking Introduction
11.18.4 DataVisor Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.18.5 DataVisor Recent Development
11.19 4Paradigm
11.19.1 4Paradigm Company Details
11.19.2 4Paradigm Business Overview
11.19.3 4Paradigm AI Fraud Detection in Banking Introduction
11.19.4 4Paradigm Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.19.5 4Paradigm Recent Development
11.20 Shanghai Shengteng Data Technology
11.20.1 Shanghai Shengteng Data Technology Company Details
11.20.2 Shanghai Shengteng Data Technology Business Overview
11.20.3 Shanghai Shengteng Data Technology AI Fraud Detection in Banking Introduction
11.20.4 Shanghai Shengteng Data Technology Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.20.5 Shanghai Shengteng Data Technology Recent Development
11.21 Iflytek
11.21.1 Iflytek Company Details
11.21.2 Iflytek Business Overview
11.21.3 Iflytek AI Fraud Detection in Banking Introduction
11.21.4 Iflytek Revenue in AI Fraud Detection in Banking Business (2020-2025)
11.21.5 Iflytek Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.1.1 Research Programs/Design
13.1.1.2 Market Size Estimation
13.1.1.3 Market Breakdown and Data Triangulation
13.1.2 Data Source
13.1.2.1 Secondary Sources
13.1.2.2 Primary Sources
13.2 Author Details
13.3 Disclaimer
TABLE OF FIGURES
List of Tables
List of Figures
KEY QUESTIONS ADDRESSED BY THE REPORT
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Published: 2026-03-12
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The global AI Fraud Detection in Banking market was valued at US$ 1709 million in 2025 and is anticipated to reach US$ 3738 million by 2032, at a CAGR of 12.0% from 2026 to 2032.
Published: 2026-03-12
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The global market for AI Fraud Detection in Banking was estimated to be worth US$ 1709 million in 2025 and is projected to reach US$ 3738 million, growing at a CAGR of 12.0% from 2026 to 2032.
Published: 2026-03-09
Pages: 159
The global AI Fraud Detection in Banking market size was US$ 1628 million in 2024 and is forecast to a readjusted size of US$ 3373 million by 2031 with a CAGR of 12.0% during the forecast period 2025-2031.
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REPORT COVERAGE
DESCRIPTION
OVERVIEW
MARKET SEGMENTATION
CHAPTER OUTLINE
QYRESEARCH'S STRENGTHS
TABLE OF CONTENTS
TABLE OF FIGURES
RLEATED REPORTS
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