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市場調查報告書
商品編碼
1907342

詐欺偵測與預防（FDP）：市佔率分析、產業趨勢與統計、成長預測（2026-2031）

Fraud Detection And Prevention (FDP) - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026 - 2031)
出版日期: | 出版商: Mordor Intelligence | 英文 100 Pages | 商品交期: 2-3個工作天內

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簡介目錄

預計到 2026 年，詐欺偵測和預防 (FDP) 市值將達到 701.9 億美元，從 2025 年的 586.9 億美元成長到 2031 年的 1,718.4 億美元。

預計2026年至2031年年複合成長率（CAGR）將達到19.6%。

詐欺檢測與預防 (FDP)-市場-IMG1

這種快速成長反映了深度造假詐騙、合成身分和其他人工智慧驅動的威脅的激增，而傳統的基於規則的引擎無法應對這些威脅，從而推動了對自適應機器學習防禦技術的需求。監管舉措，特別是歐盟PSD3和PSR一攬子計畫中要求從2026年起實施強客戶認證（SCA）的舉措，正在加速技術更新周期，因為銀行正尋求即時協調安全性、合規性和客戶體驗。各國詐欺偵測和預防（FDP）市場的成長受到行動優先支付習慣和監管要求的推動，例如菲律賓的《金融帳戶詐騙預防法》，該法案強制要求進行自動化即時監控。供應鏈詐騙的增加，包括假冒零件詐騙的三位數激增，進一步印證了這樣一種觀點：企業正在將安全視為一種收入保護工具，而不僅僅是合規成本。

全球詐欺檢測與預防 (FDP) 市場趨勢與洞察

數位支付和電子商務交易量正在上升

隨著行動錢包、QR碼和非接觸感應卡在支付流程中佔據主導地位，攻擊面也隨之擴大，超越了傳統系統的處理能力。因此，對設備指紋和行為生物特徵進行即時分析至關重要，以便區分合法客戶與機器人和腳本化的刷卡攻擊。預計到2023年，電子商務詐騙損失將達到480億美元，主要促進因素是非接觸式交易（CNP）。這迫使公司轉向基於雲端的風險引擎，以在毫秒內完成交易評分。零售平台正擴大將這些引擎直接嵌入到付款閘道中，以在保持支付速度的同時降低扣回爭議帳款風險。隨著數位優先的消費者取代實體店客流量，全部區域對支援新型支付方式（例如後付款服務和即時信用額度）的可擴展檢測技術的需求正在成長。

嚴格的監管合規壓力

歐盟修訂後的第三版支付服務指令 (PSD3) 和支付安全條例 (PSR) 將強客戶認證 (SCA) 的範圍從雙因素認證擴展到強制收款人姓名驗證和金融機構間即時詐欺資料共用。隨著銀行整合分散的產品以降低合規成本，提供單一平台認證、分析和報告服務的供應商正獲得競爭優勢。跨境貿易的全球化要求美國銀行和支付服務供應商(PSP) 在服務歐盟客戶時必須符合歐洲 SCA 標準，導致更嚴格的標準在全球推廣。亞太地區也出現了類似的趨勢，新加坡和澳洲的監管機構正在將營業執照與受監控的詐欺閾值掛鉤。這縮短了合規實施的時間，並迫使即使是最規避風險的金融機構也轉向雲端基礎設施，以便快速更新規則和模型，而無需冗長的變更管理週期。

高誤報率會損害客戶體驗

過於敏感的規則集會將合法消費標記為可疑交易，觸發人工審核，從而削弱即時支付的承諾。客戶調查顯示，連續兩筆合法交易被拒絕會使客戶在一年內更換銀行的可能性增加兩倍。現代人工智慧引擎透過分析個人的消費節奏、季節性出行模式和設備偏好來降低噪音，在不犧牲偵測率的前提下，將誤報率降低一半。然而，即時支付的普及已將決策時間縮短至幾秒，無需人工干預。因此，金融機構在調整風險閾值時更加謹慎，並願意接受小額交易中的少量詐騙損失，以保障整體轉換率和客戶滿意度。

細分市場分析

解決方案佔據了詐欺偵測與預防 (FDP) 市場 63.25% 的佔有率，這印證了分析引擎、身分驗證模組和調查儀表板的基礎性作用。供應商正利用自適應機器學習技術不斷完善規則庫，使金融機構能夠每天處理Terabyte的行為數據，並近乎即時地回應新的攻擊特徵。解決方案收入還包括監管報告模組，這些模組可將偵測資料轉換為符合審核要求的格式，使風險負責人無需借助其他工具即可滿足 PSD3、GDPR 和 OCC 的審查要求。

儘管服務領域規模較小，但隨著董事會擴大將全天候監控外包給託管安全專家，該領域正以 20.95% 的複合年成長率快速成長。這些服務提供者提供已調整的模型、精心策劃的全球威脅情報來源以及事後取證調查。資料科學和網路安全營運領域的人才短缺，使得基於績效的合約更具吸引力，因為此類合約能夠保證檢測率的服務等級協定 (SLA)。同時，諮詢解決方案也正在被應用，用於重新設計 KYC 流程、最佳化警報分級以及簡化爭議解決流程。預計到 2031 年，這種技術與專業知識的結合將佔服務收入的三分之一左右，從而鞏固其在更廣泛的詐欺偵測和預防 (FDP) 市場中的策略地位。

到2025年，本地部署方案將佔總收入的55.35%，大型銀行利用其現有基礎設施，透過在自有資料中心處理個人識別資訊（PII）來滿足資料居住法規的要求。這些公司傾向於採用混合模式，將模型訓練遷移到雲端，同時將生產評分節點保留在私有叢集，以最大限度地降低延遲。在這種架構下，即使在尖峰時段，詐欺防制處理的延遲也能維持在10毫秒以下。

然而，雲端原生平台將以 22.05% 的複合年成長率佔據主導地位，並迅速縮小差距。訂閱定價模式將授權費用與交易成長掛鉤，使中型金融機構和金融科技公司能夠避免資本支出。領先的供應商現在提供持續配置工具鏈，每週多次更新檢測模型，從而降低新詐欺的風險。先進的加密技術和保密計算區域解決了剩餘的主權問題。 ISO 27001 和 SOC 2 等認證確保了審核的信心。這些優勢的綜合作用使雲端成為未來詐欺偵測和預防 (FDP) 市場的標準基礎。

詐欺檢測與預防 (FDP) 市場按組件（解決方案、服務）、部署模式（雲端、本地部署）、組織規模（中小企業、大型企業）、最終用戶行業（銀行、金融服務和保險、零售/電子商務、醫​​療保健等）以及地區進行細分。市場預測以美元 (USD) 為單位。

區域分析

北美將佔最大佔有率，到2025年將佔總收入的27.10%。這得益於該地區早期採用雲端運算、先進的威脅情報共用以及充足的技術預算。美國財政部等聯邦機構在2024會計年度透過採用人工智慧驅動的異常檢測技術，追回了10億美元的支票詐騙損失，這既是公共部門的概念驗證，也鼓勵了私部門的進一步採用。同樣，美國信用卡網路正在推廣基於人工智慧的預核准評分，以減少非接觸式支付（CNP）扣回爭議帳款，並將詐欺檢測邏輯直接嵌入付款基礎中。加拿大各銀行已組成聯合聯盟，共同打擊新興的即時支付欺詐，展現了區域間在訊號交換方面的合作。

在歐洲，支付服務指示第三版 (PSD3) 和支付服務條例 (PSR) 正在迅速擴展監管範圍，包括強制收款人姓名驗證和引入即時風險資訊。一般資料保護規則(GDPR) 的限制推動了隱私保護型聯邦學習的創新，該技術允許在不傳輸原始資料的情況下訓練銀行間模型。新的 eIDAS 修正案要求通訊業者過濾欺騙性電話和惡意短信，將詐騙檢測和預防市場擴展到電信基礎設施領域。西班牙等國對未實施這些措施的業者處以 200 萬歐元（約 235 萬美元）的罰款，並將安全要求更深入地納入其營運許可證中。

亞太地區以19.95%的複合年成長率成為成長最快的地區，這主要得益於行動支付的高普及率和複雜的合規環境，後者迫使供應商提供可配置的策略引擎。菲律賓的《金融帳戶詐騙預防法》強制要求金融機構實施規模化的詐騙偵測系統，而印度儲備銀行則強制要求對UPI即時支付進行基於人工智慧的交易監控。中國當地正在試行將人工智慧應用於福利金的腐敗分析，這顯示其在金融科技以外的公共資金監控領域也具有應用價值。這些趨勢共同推動了亞太地區對靈活、即時解決方案的需求，使亞太地區在全球詐欺偵測和預防（FDP）市場中佔據越來越重要的地位。

其他福利：

  • Excel格式的市場預測（ME）表
  • 3個月的分析師支持

目錄

第1章 引言

  • 研究假設和市場定義
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章 市場情勢

  • 市場概覽
  • 市場促進因素
    • 數位支付和電子商務交易量增加
    • 嚴格的監管合規壓力
    • 利用人工智慧/機器學習的分析技術提高了檢測精度
    • 令牌化和 3-D Secure 2.3 的採用
    • 開放銀行/即時支付基礎設施—新的詐欺風險因素
    • 人工智慧驅動的深度造假詐騙日益猖獗
  • 市場限制
    • 高誤報率會損害客戶體驗
    • 與舊有系統整合的複雜性
    • 缺乏用於訓練人工智慧模型的標記資料集
    • 隱私法規下的資料共用限制
  • 供應鏈分析
  • 監管環境
  • 技術展望
  • 波特五力模型
    • 供應商的議價能力
    • 買方的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭對手之間的競爭
  • 評估市場中的宏觀經濟因素

第5章 市場規模與成長預測

  • 按組件
    • 解決方案
      • 詐欺分析
      • 認證
      • 報告
      • 視覺化
      • 其他
    • 服務
  • 透過部署模式
    • 雲
    • 本地部署
  • 按組織規模
    • 小型企業
    • 主要企業
  • 按最終用戶行業分類
    • BFSI
    • 零售與電子商務
    • 資訊科技和電信
    • 衛生保健
    • 能源與公共產業
    • 製造業
    • 政府和公共部門
    • 其他
  • 按地區
    • 北美洲
      • 美國
      • 加拿大
      • 墨西哥
    • 南美洲
      • 巴西
      • 阿根廷
      • 南美洲其他地區
    • 歐洲
      • 英國
      • 德國
      • 法國
      • 義大利
      • 西班牙
      • 其他歐洲地區
    • 亞太地區
      • 中國
      • 日本
      • 韓國
      • 印度
      • 澳洲
      • 亞太其他地區
    • 中東和非洲
      • 中東
        • 沙烏地阿拉伯
        • 阿拉伯聯合大公國
        • 土耳其
        • 其他中東地區
      • 非洲
        • 南非
        • 奈及利亞
        • 埃及
        • 其他非洲地區

第6章 競爭情勢

  • 市場集中度
  • 策略趨勢
  • 市佔率分析
  • 公司簡介
    • 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.

第7章 市場機會與未來展望

簡介目錄
Product Code: 56904

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.

Fraud Detection And Prevention (FDP) - Market - IMG1

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:

  1. AI/ML-Enabled Analytics Improving Detection Accuracy
  2. Generative-AI Deepfake Fraud Escalation
  3. Integration 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.

  1. SAP SE
  2. IBM Corporation
  3. SAS Institute Inc.
  4. ACI Worldwide Inc.
  5. Fiserv Inc.
  6. Experian PLC
  7. DXC Technology Company
  8. BAE Systems PLC
  9. RSA Security LLC (Dell Technologies)
  10. Oracle Corporation
  11. NICE Ltd
  12. Equifax Inc.
  13. LexisNexis Risk Solutions
  14. Fair Isaac Corporation (FICO)
  15. Cybersource Corporation (Visa)
  16. Global Payments Inc.
  17. Feedzai SA
  18. Signifyd Inc.
  19. Riskified Ltd.
  20. Kount Inc.

Additional Benefits:

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

TABLE OF CONTENTS

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