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市場調査レポート

オンラインペイメント詐欺:新たな脅威・セグメント分析・市場予測 (2020-2024年)

Online Payment Fraud: Emerging Threats, Segment Analysis & Market Forecasts 2020-2024

発行 Juniper Research Ltd 商品コード 926663
出版日 ページ情報 英文
納期: 即日から翌営業日
価格
本日の銀行送金レート: 1GBP=139.43円で換算しております。
オンラインペイメント詐欺:新たな脅威・セグメント分析・市場予測 (2020-2024年) Online Payment Fraud: Emerging Threats, Segment Analysis & Market Forecasts 2020-2024
出版日: 2020年02月25日 ページ情報: 英文
概要

当レポートでは、オンラインペイメント詐欺市場について調査し、今後5年間のマーチャントが詐欺から受ける影響の予測、不正検出・防止ソフトウェア市場の規模、ペイメントセキュリティを脅かす新しい脅威、同市場における主要なディスラプターおよびベンダーが採用する戦略、今後の市場予測などについてまとめています。

調査対象のデジタルペイメント市場

  • 航空券
  • デジタルバンキング
  • デジタル送金
  • リモートデジタル商品購入
  • リモート物理商品購入

主な特徴

  • 市場ダイナミクス:進化するペイメント詐欺市場・将来展望の詳細分析
    • PSD2インプリメンテーション & 将来の課題
    • 3-D セキュア 2.0 採用の増加
    • リアルタイムペイメントスキーム
    • オープンバンキングAPI
  • セグメント分析:部門特有の課題・戦略・将来展望の詳細評価
    • デジタルバンキング & 送金
    • リモートデジタル & 物理商品購入
    • 航空券
  • インタビュー:不正検出・防止市場の主要企業へのインタビュー
    • Accertify
    • ACI Worldwide
    • Experian
    • Fiserv
    • Gemalto
  • Juniper Research Leaderboard:主要ベンダー15社の評価
  • 産業予測のベンチマーク:eコマース市場セグメントの予測
    • デジタルバンキング
    • リモート物理商品購入
    • リモートデジタル商品購入
    • デジタル送金
    • 航空券
    • 不正検出 & 防止ソリューション
目次

Overview

Juniper Research's latest ‘Online Payment Fraud’ research report provides an extensive and highly insightful analysis of how the rapidly growing digital payments landscape is evolving. This includes how the continued intensification of fraudsters' efforts is creating challenges and opportunities for fraud prevention service providers.

The research report assesses how the landscape is fundamentally altering in payment security, with changes such as the implementation of PSD2 (the EU's revised Payment Services Directive), Secure Customer Authentication, the rise of Open Banking and growing 3-D Secure 2.0 implementation dramatically modifying the market. The research provides best practice recommendations based on these trends, as well as segment-specific analyses for the following digital payments markets:

  • Air Ticketing
  • Digital Banking
  • Digital Money Transfer
  • Remote Digital Goods Purchases
  • Remote Physical Goods Purchases

This research suite comprises:

  • Deep Dive Strategy & Competition (PDF)
  • 5-Year Deep Dive Data & Forecasting (PDF & Excel)
  • Executive Summary & Core Findings (PDF)
  • 12 months' Access to harvest Online Data Platform

Key Features

  • Market Dynamics: Detailed analysis of the evolving payment fraud market and future outlook, examining:
    • PSD2 Implementation & Future Challenges
    • Rising 3-D Secure 2.0 Adoption
    • Real-Time Payments Schemes
    • Open Banking APIs
  • Segment Analysis: In-depth evaluation of sector-specific challenges, strategies and future outlook in the context of fraud for:
    • Digital Banking & Money Transfer
    • Remote Digital & Physical Goods Purchases
    • Airline Ticketing
  • Interviews: Leading players in the fraud detection and prevention market interviewed, including:
    • Accertify
    • ACI Worldwide
    • Experian
    • Fiserv
    • Gemalto
  • Juniper Research Leaderboard: Key player capability and capacity assessment for 15 major Fraud Detection & Prevention vendors.
  • Benchmark Industry Forecasts: Market segment forecasts key eCommerce segments, including:
    • Digital Banking
    • Remote Physical Goods Purchases
    • Remote Digital Goods Purchases
    • Digital Money Transfer
    • Air Ticketing
    • Fraud Detection & Prevention Solutions

Key Questions

  • 1. What is the anticipated impact of fraud for merchants over the next 5 years?
  • 2. How large is the market for fraud detection and prevention software?
  • 3. What are the evolving threats that threaten to disrupt payment security?
  • 4. Who are the key disruptors in this space, and what strategies are vendors employing?
  • 5. How is the industry expected to develop by 2024?

Companies Referenced

  • Interviewed: Accertify, ACI Worldwide, CyberSource, Experian, Fiserv, Gemalto.
  • Profiled: Accertify, ACI Worldwide, CyberSource, Experian, FICO, Fiserv, Gemalto, iovation, Kount, LexisNexis Risk Solutions, NICE Actemize, NuData, Riskified, RSA, SAS.
  • Mentioned: 14W, 4Stop, ACCC (Australian Competition and Consumer Commission), Accenture, Accuity, Acuant, Aegean, Aite Group, Akamai, Aldo, AliPay, Allegacy Federal Credit Union, Allianz, Amadeus, Amazon, American Medical Collection Agency, Apple, Arvato Financial Solutions, Association of Banks, Auchan, Bain, Bank Liberty, Barclaycard, Biocatch, BluePay, BlueSnap, Boku, Boston Consulting Group, Braintree, British Airways, Canada Goose, Canva, Capital One, CardConnect, Cardinal Commerce, Carrefour, Cashplus, Central Bank, Chargebacks911, Chase, CIFAS, Cisco, Citi, Citrus Pay, Cognizant, CONAIR, Confused.com, ConvergeOne, Cosmos Bank, CredoLab, Cyota, Daon, Data61, Datacard, Dell Computers, Deloitte, Desjardins, Discover, Early Warning, EBA (European Banking Authority), Ekata, Emailage, EMVCo, Equifax, Ernst & Young, Esure, European Payments Council, Everis, Evo Payments, FAPI (Financial Grade API) Working Group, FCA (Financial Conduct Authority), Federal Reserve, FIDO Alliance, Finextra, First American Financial Corp, First Data, Fischer, FTC (Federal Trade Commission), Fuze, Ghd, Global Data Consortium, GNC, Google, Greyhound, HealthCare First Credit Union, HelloSoda, Horizon Investments, HP, HSBC, IATA, IBM, InAuth, Infosys, Instagram, ipagoo, IPC, Jack Henry & Associates, JCB, JetBlue, JETCO (Joint Electronic Teller Services Limited), JustPark, Kaidee, Klarna, KPMG, Landsbankinn, Last Minute, LaunchKey, Laurentian Bank, LeoVegas, Linode, Loves, Magento, Manlindo Air, Marks & Spencer, MAS (Monetary Authority of Singapore), Mastercard, Mattel, maxiPago, McAfee, Microsoft, Mitek, Moneris, MongoDB, Monzo, Motorola, mPath, M-Pesa, NAORCA (National Anti-Organized Retail Crime Association), NBT Bank, NCUA (National Credit Union Administration), New York Community Bank, NextCaller, Nextpayway, Nimbl, OBIE (Open Banking Implementation Entity), OIDF (OpenID Foundation), Onfido, OpenCart, Openpay, Oracle, Osper, OTP Bank, PassFort, PayCertify, Paym, PayPal, PBOC (Popular Bank of China), PingIdentity, Pingit, Pinpoint Intelligence, Pipl, Pizza Express, Playtech, Portland Local 8 Federal Credit Union, Prada, Praxis, Proofpoint, PSD2 Tracker, Pulse Commerce, PWC, Ravelin, Recurly, Red Hat, Regily, RELX Group, Ring, RingCentral, Rue du Commerce, Ryanair, Sage, Salesforce, Samsung, Santander, SAP, Scudetto, Servion, Shopify, ShopWare, ShopWired, Silicium Security, Silver Tail Systems, Sitecore, Sixgill, Southwest Airlines, Speedpay, Sphonic, Staley Credit Union, Stripe, Suprema, SWIFT, Symantec, Synectics Solutions, Tata Consulting Services, Telegram, Telstra, Temenos, Thales, Threat Fabric, Tink, T-Mobile, Traeger, TransUnion, Trunarrative, TrustID, TSYS, UBS, UK Finance, Unicredit Bank, UnionPay, United Colours of Benneton, Urban Outfitters, US DOJ (Department of Justice), Verifications.io, VeriFone, Verizon, Visa, Vocalink, W3C, Wallarm, Web Payment Security Interest Group, WeChat, Wells Fargo, Wendy's, WhatsApp, Wish, Worldpay, Zelle, Zuora.

Data & Interactive Forecast

Juniper Research's ‘Online Payment Fraud’ forecast suite includes:

  • Forecasts for 8 Key Regions, as well as 11 countries including:
    • Canada
    • China
    • Denmark
    • Germany
    • Japan
    • Norway
    • Portugal
    • Spain
    • Sweden
    • UK
    • US
  • Fraud Transaction Value, Split by Device:
    • Mobile
    • Online
  • Fraud Transaction Value, Split by eCommerce Segment:
    • Air Ticketing
    • Digital Banking
    • Digital Money Transfer
    • Remote Digital Goods Purchases
    • Remote Physical Goods Purchases
  • Interactive Scenario Tool allowing user the ability to manipulate Juniper Research's data for 10 different metrics.
  • Access to the full set of forecast data of 182 tables and over 24,000 datapoints.

Juniper Research's highly granular IFxls (interactive Excels) enable clients to manipulate our forecast data and charts to test their own assumptions using the Interactive Scenario Tool; and compare select markets side by side in customised charts and tables. IFxls greatly increase clients' ability to both understand a particular market and to integrate their own views into the model.

Table of Contents

Deep Dive Strategy & Competition

1. Online Payment Fraud: Market Overview

  • 1.1. Introduction
  • 1.2. Types of Fraud
    • Figure 1.1: CyberSource Fraud Statistics
    • 1.2.1. Physical & Digital Goods
      • Figure 1.2: Remote Physical & Digital Goods Purchases per annum (m) 2019-2024
      • Figure 1.3: Transaction Value of eCommerce Fraud ($m) 2019-2024
    • 1.2.2. eCommerce Value
      • Figure 1.4: Total Digital Commerce Market Value ($m), Split by Segment 2019-2024
    • 1.2.3. Payments: Changing Dynamics & Expanding Ecosystems
      • Figure 1.5: Total Number of Remote Transactions for Physical Goods, Online Wallets (m), 2019-2024, Split by 8 Key Regions
      • Figure 1.6: iDEAL Transactions Per Annum (m), 2006-2018
  • 1.3. Development of Fraudulent Activity
    • Figure 1.7: eCommerce & Fraud Attempt Growth (%), 2018-2019
  • 1.4. Key Trends in Digital Fraud
    • 1.4.1. Fitting the Human into Payment Fraud
    • 1.4.2. Continued Darknet Activity & Messaging Apps
      • i. From Darknet to Clearnet
        • Table 1.8: Average Dark Market List Price ($), Various Tools & Products used by Fraudsters July 2018
        • Table 1.9: Average Dark Market List Price ($), Various Guides used by Fraudsters July 2018
    • 1.4.3. Identity Theft
      • Figure 1.10: FTC Consumer Sentinel Network Snapshot 2019
      • i. Data Breaches
        • Figure 1.11: Total Number of Data Records per annum Exposed through Cybercrime (m), Split by 8 Key Regions 2019-2024
        • Table 1.12: Selected Major Data Breaches Reported February-November 2019
        • Table 1.13: FTC Reported Identity Theft Cases 2018 vs 2017
      • ii. Cybercriminal Targeting Shifts
      • iii. Key Takeaways

2. Online Payment Fraud: Market Dynamics

  • 2.1. Introduction
  • 2.2. PSD2. Implementations & Future Challenges
    • 2.2.1. PSD2. Overview
    • 2.2.2. PSD2. State of the Nations
    • 2.2.3. RTS Implications for Payment Service Providers
      • i. Fraud Detection
      • ii. Exemptions from SCA
        • Table.2.1: CNP Fraud Rate Thresholds for SCA Exemption
  • 2.3. The API in the Machine
  • 2.4. The Fintech in the Equation
  • 2.5. Consumer Behaviour, the Fraudsters' Friend
    • i. API Authentication Security
    • ii. Avoiding Logic Abuse
  • 2.6. Real-time Payments
    • Table.2.2: Global Instant Payments Market Status
    • 2.6.1. Fraud & Payments
      • i. Problems Inherent in Infrastructure & Processes
      • ii. Further Protections Required
  • 2.7. 3DS 2.0 (3-D Secure 2.0) & Biometric Authorisation of Transactions
    • 2.7.1. Authentication Mechanisms
      • i. OTP (One-Time Passwords)
      • ii. KBA (Knowledge-Based Authentication)
      • iii. Authenticator Apps
      • iv. Biometric
    • 2.7.2. Further 3DS Implications
    • 2.7.3. Next Steps & Regional Outlook

3. Online Payment Fraud Segment Analysis

  • 3.1. Introduction
  • 3.2. Banking & Money Transfer
    • 3.2.1. Key Challenge: Advanced Persistent Threats
      • Table 3.1: Lazarus APT Attack
    • 3.2.2. Key Challenge: Open Banking & Multi-part Attacks
    • 3.2.3. Key Trends & Outlook in the Financial Sector
  • 3.3. Remote Goods Purchases
    • 3.3.1. Key Challenge: Synthetic Identity
      • i. Omnichannel Fraud
      • ii. Detection
    • 3.3.2. Key Challenge: Omnichannel Security
    • 3.3.3. Key Trends & Future Outlook in eRetail
    • 3.3.4. Machine Learning
  • 3.4. Airlines
    • Figure 3.2: Impact of Crude Oil Price ($) on Aviation Operating Costs (%) 2005-2019
    • 3.4.1. Key Challenge: Security
    • 3.4.2. Airline & Holiday Firm Collapses
    • 3.4.3. Key Challenge: Chargebacks
    • 3.4.4. Key Trends & Future Outlook in the Airline Sector

4. Online Payment Fraud Competitive Analysis

  • 4.1. Introduction
  • 4.2. Juniper Research Leaderboard
    • Table 4.1: FDP Vendor Capability Assessment Criteria
  • 4.3. Leaderboard Scoring Results
    • Table 4.2: Juniper Research Leaderboard: FDP Vendors
    • Figure 4.3: Juniper Research Leaderboard: FDP Vendors
    • 4.3.1. Stakeholder Groupings
      • i. Established Leaders
      • ii. Leading Challengers
      • iii. Disruptors & Emulators
    • 4.3.2. Limitations & Interpretations
  • 4.4. Online Payment Fraud Movers & Shakers
  • 4.5. Vendor Profiles
    • 4.5.1. Accertify
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-Level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.2. ACI Worldwide
      • i. Corporate
        • Table 4.4: ACI Worldwide Financial Snapshot ($m) 2015-2018
      • ii. Geographic Spread
      • iii. Key Clients & Partnerships
      • iv. High-level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.3. CyberSource, a Visa Solution
      • i. Corporate
        • Table 4.5: Visa Financial Snapshot ($m) 2017-2019
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.4. Experian
      • i. Corporate
        • Table 4.6: Experian Financial Snapshot ($m) FY 2017-2019
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.5. FICO
      • i. Corporate
        • Table 4.7: FICO Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.6. Fiserv
      • i. Corporate
        • Table 4.8: Fiserv Financial Snapshot ($bn) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.7. Gemalto
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
        • Figure 4.9: ID Cloud Fraud Prevention Diagram
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.8. iovation
      • i. Corporate
        • Table 4.10: TransUnion Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.9. Kount
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.10. LexisNexis Risk Solutions
      • i. Corporate Profile
        • Table 4.11: RELX Group Financial Snapshot (£m/$m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.11. NICE Actemize
      • i. Corporate
        • Table 4.12: NICE Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.12. NuData Security
      • i. Corporate
        • Table 4.13: Mastercard Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.13. Riskified
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.14. RSA Security
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities
    • 4.5.15. SAS
      • i. Corporate
        • Table 4.14: SAS Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Products
      • v. Juniper's View: Vendor's Key Strengths & Strategic Development Opportunities

Deep Dive Data & Forecasting

1. Online Payment Fraud: Market Overview

  • 1.1. Introduction
  • 1.2. Types of Fraud

2. Online Payment Fraud Market Summary

  • 2.1. Introduction
  • 2.2. Methodology & Assumptions
    • Figure 2.1: FDP Forecast Methodology
  • 2.3. Forecast Summary
    • 2.3.1. CNP Fraud
      • Figure & Table 2.2: Total CNP Fraud Value ($m): Remote Goods Purchases, Airline Tickets, Split by 8 Key Regions 2019-2024
    • 2.3.2. Total Value of Fraudulent Transactions
      • Figure & Table 2.3: Total Value of Fraudulent Transactions ($m), Split by eCommerce Segment 2019-2024

3. Airline eTicketing Fraud: Market Forecasts

  • 3.1. Introduction
    • Figure 3.1: Impact of Crude Oil Price ($) on Aviation Operating Costs (%) 2005-2019
  • 3.2. Airline eTicketing Fraud Transaction Value
    • Figure & Table 3.2: Total Airline eTicket Fraudulent Value ($m), Split by 8 Key Regions 2019-2024
  • 3.3. Airline eTicketing Fraud: Online vs Mobile
    • Figure & Table 3.3: Total Airline eTicket Fraudulent Value ($m), Split by Sales Channel 2019-2024
  • 3.4. Airline eTicketing Fraud Rates

4. Remote Digital Goods Purchases Fraud: Market Forecasts

  • Figure & Table 3.4: Total Airline Ticket Fraud Rate by Value (%), Split by 8 Key Regions 2019-2024
  • 4.1. Introduction
  • 4.2. Remote Digital Goods Fraud Transaction Value
    • Figure & Table 4.1: Total Remote Digital Goods Fraudulent Value ($m), Split by 8 Key Regions 2019-2024
  • 4.3. Remote Digital Goods Fraud: Online vs Mobile
    • Figure & Table 4.2: Total Remote Digital Goods Fraudulent Value ($m), Split by Sales Channel 2019-2024
  • 4.4. Remote Digital Goods Fraud Rates
    • Figure & Table 4.3: Total Remote Digital Goods Fraud Rate by Value (%), Split by 8 Key Regions 2019-2024

5. Remote Physical Goods Purchases Fraud: Market Forecasts

  • 5.1. Introduction
  • 5.2. Remote Physical Goods Fraud Transaction Value
    • Figure & Table 5.1: Total Remote Physical Goods Fraudulent Value ($m), Split by 8 Key Regions 2019-2024
  • 5.3. Remote Physical Goods Fraud: Online vs Mobile
    • Figure & Table 5.2: Total Remote Physical Goods Fraudulent Value ($m), Split by Sales Channel 2019-2024
  • 5.4. Remote Physical Goods Fraud Rates
    • Figure & Table 5.3: Total Remote Physical Goods Fraud Rate by Value (%), Split by 8 Key Regions 2019-2024

6. Money Transfer Fraud: Market Forecasts

  • 6.1. Introduction
    • Figure 6.1: $10 billion+ International Remittance Corridors in 2018
  • 6.2. Money Transfer Fraud Transaction Value
    • Figure & Table 6.2: Total Money Transfer Fraudulent Value ($m), Split by 8 Key Regions 2019-2024
  • 6.3. Money Transfer Fraud: Online vs Mobile
    • Figure & Table 6.3: Total Money Transfer Fraudulent Value ($m), Split by Sales Channel 2019-2024
  • 6.4. Money Transfer Fraud Rates
    • Figure & Table 6.4: Total Money Transfer Fraud Rate by Value (%), Split by 8 Key Regions 2019-2024

7. Digital Banking Fraud: Market Forecasts

  • 7.1. Introduction
  • 7.2. Digital Banking Fraud Transaction Value
    • Figure & Table 7.1: Total Digital Banking Fraudulent Value ($m), Split by 8 Key Regions 2019-2024
  • 7.3. Digital Banking Fraud: Online vs Mobile
    • Figure & Table 7.2: Total Digital Banking Fraudulent Value ($m), Split by Sales Channel 2019-2024
  • 7.4. Digital Banking Fraud Rates
    • Figure & Table 7.3: Total Digital Banking Fraud Rate by Value (%), Split by 8 Key Regions 2019-2024

8. Fraud Detection & Prevention Solutions: Market Forecasts

  • 8.1. Introduction
  • 8.2. Business Models
    • 8.2.1. SaaS (Software as a Service)-based Hosting
    • 8.2.2. Licensed On-Premises Software Solution
    • 8.2.3. Hybrid Model
  • 8.3. FDP Solutions Market Size
    • Figure & Table 8.1: Total Annual FDP Spend ($m), Split by 8 Key Regions 2019-2024