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Report

Fraud Detection And Prevention (FDP) - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026 - 2031)

Market Report I 2026-01-16 I 100 Pages I Mordor Intelligence

Fraud Detection And Prevention (FDP) Market Analysis

Fraud detection and prevention market size in 2026 is estimated at USD 70.19 billion, growing from 2025 value of USD 58.69 billion with 2031 projections showing USD 171.84 billion, growing at 19.6% CAGR over 2026-2031. This steep trajectory mirrors the surge in deepfake scams, synthetic identities, and other AI-enabled threats that overwhelm legacy rule engines and elevate demand for adaptive machine-learning defenses. Regulatory momentum, notably the European PSD3 and PSR package that tightens Strong Customer Authentication (SCA) from 2026, accelerates technology refresh cycles as banks look to align security, compliance, and customer experience in real time. Fraud detection and prevention market in various countries is fueled by mobile-first payment habits and laws such as the Philippines' Anti-Financial Account Scamming Act that mandates automated, real-time monitoring. Intensifying supply-chain fraud, evidenced by triple-digit spikes in counterfeit component scams, further underscores because organizations now treat security as a revenue-protection lever, not merely a compliance cost.

Global Fraud Detection And Prevention (FDP) Market Trends and Insights



Rising Digital Payments and E-commerce Volumes

Mobile wallets, QR codes, and contactless cards now dominate checkout flows, expanding attack surfaces that legacy systems cannot parse effectively. Real-time analysis of device fingerprinting and behavioral biometrics has therefore become mandatory to distinguish legitimate customers from bots or scripted card-testing attacks.E-commerce fraud losses reached USD 48 billion in 2023, with card-not-present (CNP) transactions as the chief culprit, pushing merchants toward cloud-based risk engines that score transactions in milliseconds. Retail platforms increasingly embed these engines directly in payment gateways to preserve checkout speed while reducing chargeback exposure. As digital-first consumers continue to displace in-store traffic, demand for scalable detection that adapts to novel payment formats-such as buy-now-pay-later and instant-credit lines-intensifies across every major geography.

Stringent Regulatory Compliance Pressures

Europe's PSD3 and PSR overhaul expands SCA beyond two-factor credentials to include mandatory payee name verification and real-time fraud data sharing among financial institutions. Vendors that deliver single platforms covering authentication, analytics, and reporting gain an edge as banks consolidate point products to rein in compliance overhead. The global nature of cross-border commerce compels US banks and PSPs to meet European SCA benchmarks when serving EU clients, effectively exporting stricter standards worldwide. Similar momentum appears in Asia-Pacific, where regulators in Singapore and Australia link operating licences to monitored fraud thresholds. Compliance thus compresses deployment timelines, pushing even risk-averse institutions toward cloud infrastructures that offer rapid rule and model updates without lengthy change-control cycles.

High False-Positive Rates Hurting Customer Experience

Overly sensitive rule sets can tag legitimate spend as suspicious, triggering manual reviews that stall instant-payment expectations. Customer surveys show that two consecutively declined genuine transactions triple the likelihood of switching banks within a year. Modern AI engines reduce noise by profiling individual spending rhythms, seasonal travel patterns, and device preferences, cutting false-positive counts by up to half without sacrificing catch rates. Yet the shift to real-time settlement compresses decision windows to mere seconds, leaving no room for human intervention. Institutions therefore calibrate risk thresholds more carefully, accepting marginally higher fraud loss on low-ticket items to protect overall conversion and satisfaction metrics.

Other drivers and restraints analyzed in the detailed report include:

AI/ML-Enabled Analytics Improving Detection AccuracyGenerative-AI Deepfake Fraud EscalationIntegration Complexity with Legacy Systems

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Solutions hold 63.25% of the fraud detection and prevention market size, underscoring the foundational role of analytics engines, authentication modules, and investigator dashboards. Vendors refine rule libraries with adaptive machine learning, letting financial institutions ingest terabytes of behavioral data per day and respond to fresh attack signatures in near real time. Solutions revenue also reflects regulatory reporting modules that convert detection data into audit-ready formats, allowing risk officers to satisfy PSD3, GDPR, or OCC exams without separate tooling.

Services, although smaller, are expanding at 20.95% CAGR as boards delegate 24/7 monitoring to managed-security specialists that provide calibrated models, curated global threat feeds, and post-incident forensics. Talent shortages in data science and cyber-ops elevate the appeal of outcome-based contracts that guarantee detection-rate SLAs. In parallel, consulting wraps around solution deployments to re-engineer KYC flows, optimize alert triage, and streamline dispute resolution. This convergence of technology and expertise is expected to lift services to almost one-third of 2031 revenue, reinforcing their strategic position within the broader fraud detection and prevention market.

On-premises installations retained 55.35% of 2025 revenue as tier-one banks leveraged sunk infrastructure and met data-residency statutes by processing PII in their own data centers. These firms favor hybrid patterns that shift model training to the cloud yet keep production scoring nodes in private clusters to minimize latency. Under such architectures, anti-fraud latency remains below 10 milliseconds even at holiday peak volumes.

Cloud-native platforms, however, outpace all others at a 22.05% CAGR and will narrow the share gap rapidly. Subscription pricing aligns license fees with transaction growth, letting mid-tier lenders and fintechs avoid capital outlays. Leading vendors now pre-package continuous deployment toolchains that refresh detection models multiple times per week, shortening exposure windows to novel frauds. Advanced encryption and confidential-compute zones address lingering sovereignty worries, while certifications like ISO 27001 and SOC 2 reassure auditors. These advantages collectively establish cloud as the future default for the fraud detection and prevention market.

Fraud Detection and Prevention Market is Segmented by Component (Solutions, Services), Deployment Mode (Cloud, On-Premises), Organization Size (SMEs, Large Enterprises), End-User Industry (BFSI, Retail and E-Commerce, Healthcare, and More), and by Geography. The Market Forecasts are Provided in Terms of Value (USD).

Geography Analysis

North America generated the largest regional slice at 27.10% of 2025 revenue, supported by early cloud adoption, sophisticated threat intelligence sharing, and sizeable technology budgets. Federal agencies such as the US Treasury recovered USD 1 billion in check fraud during fiscal 2024 after deploying AI-driven anomaly detection, signaling public-sector validation that further stimulates private-sector uptake. US card networks likewise advocate AI-based pre-authorization scoring to curb CNP chargebacks, embedding fraud logic directly in payment rails. Canadian banks collaborate in a joint consortium to combat emerging real-time rail fraud, demonstrating regional co-operation on signals exchange.

Europe follows with rapid regulatory expansion as PSD3 and PSR introduce mandatory payee-name matching and real-time risk feeds. GDPR constraints drive innovation in privacy-preserving federated learning, allowing banks to train cross-bank models without raw-data transfers. Telecom operators must filter spoofed calls and malware SMS under new eIDAS updates, broadening the fraud detection and prevention market into telco infrastructure. Nations such as Spain impose EUR 2 million (USD 2.35 million) fines on carriers that fail to implement these measures, embedding security requirements deep in operational licences.

Asia-Pacific records the fastest 19.95% CAGR, led by high mobile payment penetration and fragmented compliance terrain that forces vendors to offer configurable policy engines. The Philippines' Anti-Financial Account Scamming Act compels fraud systems scaled to institution size, while India's RBI mandates AI-powered transaction monitoring for UPI instant payments. Mainland China pilots AI corruption analytics on welfare distributions, proving applicability beyond fintech into public-fund oversight. Together, these dynamics amplify regional demand for flexible, real-time solutions, elevating APAC's weighting in the global fraud detection and prevention market.

List of Companies Covered in this Report:

SAP SE IBM Corporation SAS Institute Inc. ACI Worldwide Inc. Fiserv Inc. Experian PLC DXC Technology Company BAE Systems PLC RSA Security LLC (Dell Technologies) Oracle Corporation NICE Ltd Equifax Inc. LexisNexis Risk Solutions Fair Isaac Corporation (FICO) Cybersource Corporation (Visa) Global Payments Inc. Feedzai SA Signifyd Inc. Riskified Ltd. Kount Inc.

Additional Benefits:

    The market estimate (ME) sheet in Excel format
    3 months of analyst support

1 INTRODUCTION
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE
4.1 Market Overview
4.2 Market Drivers
4.2.1 Rising digital payments and e-commerce volumes
4.2.2 Stringent regulatory compliance pressures
4.2.3 AI/ML-enabled analytics improving detection accuracy
4.2.4 Tokenization and 3-D Secure 2.3 boosting adoption
4.2.5 Open Banking/instant-payment rails - new fraud vectors
4.2.6 Generative-AI deepfake fraud escalation
4.3 Market Restraints
4.3.1 High false-positive rates hurting CX
4.3.2 Integration complexity with legacy systems
4.3.3 Lack of labelled data sets for AI model training
4.3.4 Data-sharing limits under privacy regulations
4.4 Supply-Chain Analysis
4.5 Regulatory Landscape
4.6 Technological Outlook
4.7 Porter's Five Forces
4.7.1 Bargaining Power of Suppliers
4.7.2 Bargaining Power of Buyers
4.7.3 Threat of New Entrants
4.7.4 Threat of Substitutes
4.7.5 Intensity of Competitive Rivalry
4.8 Assesment of Macroeconomic Factors on the market

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)
5.1 By Component
5.1.1 Solutions
5.1.1.1 Fraud Analytics
5.1.1.2 Authentication
5.1.1.3 Reporting
5.1.1.4 Visualization
5.1.1.5 Others
5.1.2 Services
5.2 By Deployment Mode
5.2.1 Cloud
5.2.2 On-premises
5.3 By Organization Size
5.3.1 Small and Medium Enterprises
5.3.2 Large Enterprises
5.4 By End-user Industry
5.4.1 BFSI
5.4.2 Retail and E-commerce
5.4.3 IT and Telecom
5.4.4 Healthcare
5.4.5 Energy and Utilities
5.4.6 Manufacturing
5.4.7 Government and Public Sector
5.4.8 Others
5.5 By Geography
5.5.1 North America
5.5.1.1 United States
5.5.1.2 Canada
5.5.1.3 Mexico
5.5.2 South America
5.5.2.1 Brazil
5.5.2.2 Argentina
5.5.2.3 Rest of South America
5.5.3 Europe
5.5.3.1 United Kingdom
5.5.3.2 Germany
5.5.3.3 France
5.5.3.4 Italy
5.5.3.5 Spain
5.5.3.6 Rest of Europe
5.5.4 Asia-Pacific
5.5.4.1 China
5.5.4.2 Japan
5.5.4.3 South Korea
5.5.4.4 India
5.5.4.5 Australia
5.5.4.6 Rest of Asia-Pacific
5.5.5 Middle East and Africa
5.5.5.1 Middle East
5.5.5.1.1 Saudi Arabia
5.5.5.1.2 United Arab Emirates
5.5.5.1.3 Turkey
5.5.5.1.4 Rest of Middle East
5.5.5.2 Africa
5.5.5.2.1 South Africa
5.5.5.2.2 Nigeria
5.5.5.2.3 Egypt
5.5.5.2.4 Rest of Africa

6 COMPETITIVE LANDSCAPE
6.1 Market Concentration
6.2 Strategic Moves
6.3 Market Share Analysis
6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)
6.4.1 SAP SE
6.4.2 IBM Corporation
6.4.3 SAS Institute Inc.
6.4.4 ACI Worldwide Inc.
6.4.5 Fiserv Inc.
6.4.6 Experian PLC
6.4.7 DXC Technology Company
6.4.8 BAE Systems PLC
6.4.9 RSA Security LLC (Dell Technologies)
6.4.10 Oracle Corporation
6.4.11 NICE Ltd
6.4.12 Equifax Inc.
6.4.13 LexisNexis Risk Solutions
6.4.14 Fair Isaac Corporation (FICO)
6.4.15 Cybersource Corporation (Visa)
6.4.16 Global Payments Inc.
6.4.17 Feedzai SA
6.4.18 Signifyd Inc.
6.4.19 Riskified Ltd.
6.4.20 Kount Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK
7.1 White-space and Unmet-need Assessment

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