Industry: Service & Software
Published Date: 2025-07-07
Pages: 168 Pages
Report ld: 4786177
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AI Fraud Detection for Enterprises Market Size(US$)

CAGR 2025-2031
12.0%
Market Size,2031
USD 6,174
Million
Market Snapshot
Source: Secondary research, interviews with experts, and QYResearch analysis
The global AI Fraud Detection for Enterprises market is projected to grow from US$ 3128 million in 2025 to US$ 6174 million by 2031, at a Compound Annual Growth Rate (CAGR) of 12.0% during the forecast period.
AI Fraud Detection for Enterprises refers to the use of Artificial Intelligence (AI), Machine Learning (ML), and Big Data Analytics to automatically identify, prevent, and mitigate fraudulent activities in business operations. These systems analyze transactional, behavioral, and network data in real time to detect anomalies, predict risks, and reduce financial losses.
The US & Canada market for AI Fraud Detection for Enterprises is estimated to increase from $ million in 2025 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The China market for AI Fraud Detection for Enterprises is estimated to increase from $ million in 2025 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The Europe market for AI Fraud Detection for Enterprises is estimated to increase from $ million in 2025 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The global key manufacturers of AI Fraud Detection for Enterprises include Eastnets, Feedzai, Resistant AI, NetGuardians, ADVANCE, Sift, Fraud.net, SEON, Sardine, Mastercard Consumer Fraud Risk, etc. In 2024, the global top five players had a share approximately % in terms of revenue.
In terms of production side, this report researches the AI Fraud Detection for Enterprises production, growth rate, market share by manufacturers and by region (region level and country level), from 2020 to 2025, and forecast to 2031.
In terms of consumption side, this report focuses on the sales of AI Fraud Detection for Enterprises by region (region level and country level), by company, by Type and by Application. from 2020 to 2025 and forecast to 2031.
This report presents an overview of global market for AI Fraud Detection for Enterprises, capacity, output, revenue and price. Analyses of the global market trends, with historic market revenue/sales data for 2020 - 2025, estimates for 2025, and projections of CAGR through 2031.
This report researches the key producers of AI Fraud Detection for Enterprises, also provides the consumption of main regions and countries. Highlights of the upcoming market potential for AI Fraud Detection for Enterprises, and key regions/countries of focus to forecast this market into various segments and sub-segments. Country specific data and market value analysis for the U.S., Canada, Mexico, Brazil, China, Japan, South Korea, Southeast Asia, India, Germany, the U.K., Italy, Middle East, Africa, and Other Countries.
This report focuses on the AI Fraud Detection for Enterprises sales, revenue, market share and industry ranking of main manufacturers, data from 2020 to 2025. Identification of the major stakeholders in the global AI Fraud Detection for Enterprises market, and analysis of their competitive landscape and market positioning based on recent developments and segmental revenues. This report will help stakeholders to understand the competitive landscape and gain more insights and position their businesses and market strategies in a better way.
This report analyzes the segments data by Type and by Application, sales, revenue, and price, from 2020 to 2031. Evaluation and forecast the market size for AI Fraud Detection for Enterprises sales, projected growth trends, production technology, application and end-user industry.
Descriptive company profiles of the major global players, including Eastnets, Feedzai, Resistant AI, NetGuardians, ADVANCE, Sift, Fraud.net, SEON, Sardine, Mastercard Consumer Fraud Risk, etc.
MARKET SEGMENTATION
CHAPTER OUTLINE
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type and 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: AI Fraud Detection for Enterprises production/output of global and key producers (regions/countries). It provides a quantitative analysis of the production, and development potential of each producer in the next six years.
Chapter 3: Sales (consumption), revenue of AI Fraud Detection for Enterprises in global, regional level and country level. 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 of each country in the world.
Chapter 4: Detailed analysis of AI Fraud Detection for Enterprises manufacturers competitive landscape, price, sales, revenue, market share and industry ranking, latest development plan, merger, and acquisition information, etc.
Chapter 5: Provides the analysis of various market segments by Type, covering the sales, revenue, average price, and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 6: Provides the analysis of various market segments by Application, covering the sales, revenue, average price, and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 7: North America (US & Canada) by Type, by Application and by country, sales, and revenue for each segment.
Chapter 8: Europe by Type, by Application and by country, sales, and revenue for each segment.
Chapter 9: China by Type, and by Application, sales, and revenue for each segment.
Chapter 10: Asia (excluding China) by Type, by Application and by region, sales, and revenue for each segment.
Chapter 11: Middle East, Africa, Latin America by Type, by Application and by country, sales, and revenue for each segment.
Chapter 12: Provides profiles of key manufacturers, introducing the basic situation of the main companies in the market in detail, including product descriptions and specifications, AI Fraud Detection for Enterprises sales, revenue, price, gross margin, and recent development, etc.
Chapter 13: Analysis of industrial chain, sales channel, key raw materials, distributors and customers.
Chapter 14: Introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 15: 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 for Enterprises 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 for Enterprises Market Share by Application: 2020 VS 2024 VS 2031
1.3.2 E-commerce
1.3.3 Insurance
1.3.4 Telecommunications
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 for Enterprises Market Perspective (2020-2031)
2.2 Global AI Fraud Detection for Enterprises Growth Trends by Region
2.2.1 Global AI Fraud Detection for Enterprises Market Size by Region: 2020 VS 2024 VS 2031
2.2.2 AI Fraud Detection for Enterprises Market Size by Region (2020-2031)
2.3 AI Fraud Detection for Enterprises Market Dynamics
2.3.1 AI Fraud Detection for Enterprises Industry Trends
2.3.2 AI Fraud Detection for Enterprises Market Drivers
2.3.3 AI Fraud Detection for Enterprises Market Challenges
2.3.4 AI Fraud Detection for Enterprises Market Restraints
3 Competition Landscape by Key Players
3.1 Global Revenue AI Fraud Detection for Enterprises by Players
3.1.1 Global AI Fraud Detection for Enterprises Revenue by Players (2020-2025)
3.1.2 Global AI Fraud Detection for Enterprises Revenue Market Share by Players (2020-2025)
3.2 Global AI Fraud Detection for Enterprises Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players of AI Fraud Detection for Enterprises, Ranking by Revenue, 2023 VS 2024 VS 2025
3.4 Global Market Concentration Ratio
3.4.1 Global AI Fraud Detection for Enterprises Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by AI Fraud Detection for Enterprises Revenue in 2024
3.5 Global Key Players of AI Fraud Detection for Enterprises Head office and Area Served
3.6 Global Key Players of AI Fraud Detection for Enterprises, Product and Application
3.7 Global Key Players of AI Fraud Detection for Enterprises, Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 Breakdown Data by Type
4.1 Global AI Fraud Detection for Enterprises Historic Market Size by Type (2020-2025)
4.2 Global AI Fraud Detection for Enterprises Forecasted Market Size by Type (2026-2031)
5 Breakdown Data by Application
5.1 Global AI Fraud Detection for Enterprises Historic Market Size by Application (2020-2025)
5.2 Global AI Fraud Detection for Enterprises Forecasted Market Size by Application (2026-2031)
6 North America
6.1 North America AI Fraud Detection for Enterprises Market Size (2020-2031)
6.2 North America Market Size by Type
6.2.1 North America AI Fraud Detection for Enterprises Market Size by Type (2020-2031)
6.2.2 North America AI Fraud Detection for Enterprises Market Share by Type (2020-2031)
6.3 North America Market Size by Application
6.3.1 North America AI Fraud Detection for Enterprises Market Size by Application (2020-2031)
6.3.2 North America AI Fraud Detection for Enterprises Market Share by Application (2020-2031)
6.4 North America Market Size by Country
6.4.1 North America AI Fraud Detection for Enterprises Market Size by Country: 2020 VS 2024 VS 2031
6.4.2 North America AI Fraud Detection for Enterprises Market Size by Country (2020-2031)
6.4.3 United States
6.4.4 Canada
7 Europe
7.1 Europe AI Fraud Detection for Enterprises Market Size (2020-2031)
7.2 Europe Market Size by Type
7.2.1 Europe AI Fraud Detection for Enterprises Market Size by Type (2020-2031)
7.2.2 Europe AI Fraud Detection for Enterprises Market Share by Type (2020-2031)
7.3 Europe Market Size by Application
7.3.1 Europe AI Fraud Detection for Enterprises Market Size by Application (2020-2031)
7.3.2 Europe AI Fraud Detection for Enterprises Market Share by Application (2020-2031)
7.4 Europe Market Size by Country
7.4.1 Europe AI Fraud Detection for Enterprises Market Size by Country: 2020 VS 2024 VS 2031
7.4.2 Europe AI Fraud Detection for Enterprises Market Size by Country (2020-2025)
7.4.3 Germany
7.4.4 France
7.4.5 U.K.
7.4.6 Italy
7.4.7 Russia
7.4.8 Nordic Countries
8 China
8.1 China AI Fraud Detection for Enterprises Market Size (2020-2031)
8.2 China Market Size by Type
8.2.1 China AI Fraud Detection for Enterprises Market Size by Type (2020-2031)
8.2.2 China AI Fraud Detection for Enterprises Market Share by Type (2020-2031)
8.3 China Market Size by Application
8.3.1 China AI Fraud Detection for Enterprises Market Size by Application (2020-2031)
8.3.2 China AI Fraud Detection for Enterprises Market Share by Application (2020-2031)
9 Asia (excluding China)
9.1 Asia AI Fraud Detection for Enterprises Market Size (2020-2031)
9.2 Asia Market Size by Type
9.2.1 Asia AI Fraud Detection for Enterprises Market Size by Type (2020-2031)
9.2.2 Asia AI Fraud Detection for Enterprises Market Share by Type (2020-2031)
9.3 Asia Market Size by Application
9.3.1 Asia AI Fraud Detection for Enterprises Market Size by Application (2020-2031)
9.3.2 Asia AI Fraud Detection for Enterprises Market Share by Application (2020-2031)
9.4 Asia Market Size by Region
9.4.1 Asia AI Fraud Detection for Enterprises Market Size by Region: 2020 VS 2024 VS 2031
9.4.2 Asia AI Fraud Detection for Enterprises Market Size by Region (2020-2031)
9.4.3 Japan
9.4.4 South Korea
9.4.5 China Taiwan
9.4.6 Southeast Asia
9.4.7 India
9.4.8 Australia
10 Middle East, Africa, and Latin America
10.1 Middle East, Africa, and Latin America AI Fraud Detection for Enterprises Market Size (2020-2031)
10.2 Middle East, Africa, and Latin America Market Size by Type
10.2.1 Middle East, Africa, and Latin America AI Fraud Detection for Enterprises Market Size by Type (2020-2031)
10.2.2 Middle East, Africa, and Latin America AI Fraud Detection for Enterprises Market Share by Type (2020-2031)
10.3 Middle East, Africa, and Latin America Market Size by Application
10.3.1 Middle East, Africa, and Latin America AI Fraud Detection for Enterprises Market Size by Application (2020-2031)
10.3.2 Middle East, Africa, and Latin America Market Share by Application (2020-2031)
10.4 Middle East, Africa, and Latin America Market Size by Country
10.4.1 Middle East, Africa, and Latin America AI Fraud Detection for Enterprises Market Size by Country: 2020 VS 2024 VS 2031
10.4.2 Middle East, Africa, and Latin America AI Fraud Detection for Enterprises Market Size by Country (2020-2031)
10.4.3 Brazil
10.4.4 Mexico
10.4.5 Turkey
10.4.6 Saudi Arabia
10.4.7 Israel
10.4.8 GCC Countries
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 for Enterprises Introduction
11.1.4 Eastnets Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.2.4 Feedzai Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.3.4 Resistant AI Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.4.4 NetGuardians Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.5.4 ADVANCE Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.6.4 Sift Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.7.4 Fraud.net Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.8.4 SEON Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.9.4 Sardine Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.10.4 Mastercard Consumer Fraud Risk Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.11.4 Cifas Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.12.4 GFT Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.13.4 Hawk Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.14.4 SymphonyAI Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.15.4 SB Payment Service Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.16.4 KPMG Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.17.4 NICE Actimize Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.18.4 DataVisor Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.19.4 4Paradigm Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.20.4 Shanghai Shengteng Data Technology Revenue in AI Fraud Detection for Enterprises 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 for Enterprises Introduction
11.21.4 Iflytek Revenue in AI Fraud Detection for Enterprises 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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REPORT COVERAGE
DESCRIPTION
OVERVIEW
MARKET SEGMENTATION
CHAPTER OUTLINE
QYRESEARCH'S STRENGTHS
TABLE OF CONTENTS
TABLE OF FIGURES
RLEATED REPORTS
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