Cover Image
市場調查報告書

行動ID、生物辨識及權標化 2015-2020年

Mobile Identity, Biometric Authentication & Tokenisation 2015-2020

出版商 Juniper Research 商品編碼 344209
出版日期 內容資訊 英文
商品交期: 最快1-2個工作天內
價格
Back to Top
行動ID、生物辨識及權標化 2015-2020年 Mobile Identity, Biometric Authentication & Tokenisation 2015-2020
出版日期: 2015年10月27日 內容資訊: 英文
簡介

本報告提供交易認證及ID對照的相關領域中機會及課題的詳細調查。

主要的調查內容

  • 現有的線上2因素認證解決方案相關問題的評估
  • 銀行和卡片詳細的個人資料替代發送手段的權標化的利用
  • 核心相關利益者取向預定經營模式相關討論,預測發展的各種技術的貨幣化之機會檢討
  • 大範圍的主要標準的詳細預測

主要的特徵

  • 產業倡議的影響評估
  • 主要趨勢、最重要課題分析
  • 行動認證,ID及權標化平台供應商的熱圖評估、企業簡介,及矩陣的排行榜
  • 包含用戶數、消費額及交易額的生物學認證的市場預測,及行動ID服務引進、收益的預測

主要的問題

  • 生物學認證能取得的主要優點為何?
  • 促進行動付款的生物學認證引進的是哪個服務?
  • 權標化如何減少行動交易的非法等級?
  • 到目前為止市場上最成功的行動ID解決方案為何?
  • 行動ID服務的引進相關主要課題為何?

本調查提及企業

  • 採訪:Bell ID, FIDO Alliance, Gemalto, Giesecke & Devrient, Okta, Precise Biometrics, Swisscom
  • 簡介:Bell ID, Encap Security, Gemalto, Giesecke & Devrient, Good Technology, IBM, Oberthur Technologies, Okta, Payfone, Precise Biometrics, Safran, TeleSign
  • 案例研究:Anthem, Apple, Ashley Madison, KDDI, FIDO Alliance, Premera Blue Cross, Swisscom
  • 提及的企業
目錄

Overview

Juniper Research's Mobile Identity, Biometric Authentication & Tokenisation research suite offers the most in-depth assessment and analysis to date of the opportunities and challenges across these interrelated fields.

With passwords increasingly perceived as inefficient and inadequate, and with data theft soaring, there is an urgent need for alternative mechanisms for transactional authentication and identity verification.

This research:

  • Assesses the problems associated with existing online two-factor authentication solutions.
  • Explores use of tokenisation as means of replacing transmission of personal data such as bank and card details.
  • Considers opportunities for monetising various technologies that might be deployed, including discussions around the potential business models for core stakeholders.
  • Provides the most in-depth forecasts across a range of key metrics.

Key Features

  • Industry initiative impact assessment.
  • Analysis of key trends and primary challenges.
  • Heat map assessment of mobile authentication, identity and tokenisation platform providers, player profiles and matrix ranking.
  • Market forecasts for mobile biometric authentication, including users, usage and transaction values, together with forecasts for mobile identity service adoption and revenues.

Key Questions

  • 1. What are the primary benefits that biometric authentication can deliver?
  • 2. Which services will drive the adoption of biometric authentication in mobile payments?
  • 3. How can tokenisation reduce fraud levels in mobile transactions?
  • 4. What are the most successful mobile identity solutions in the market to date?
  • 5. What are the key challenges around the deployment of a mobile ID service?

Companies Referenced

Companies Referenced

Interviewed: Bell ID, FIDO Alliance, Gemalto, Giesecke & Devrient, Okta, Precise Biometrics, Swisscom.

Profiled: Bell ID, Encap Security, Gemalto, Giesecke & Devrient, Good Technology, IBM, Oberthur Technologies, Okta, Payfone, Precise Biometrics, Safran, TeleSign.

Case Studied: Anthem, Apple, Ashley Madison, KDDI, FIDO Alliance, Premera Blue Cross, Swisscom.

Mentioned:

1Password, 21st Century Fox, Accenture, Adams Street Partners, Adobe, Agnitio, Alibaba, Alipay, Allergan, Alliance Venture, Altimeter, Amazon, American Express, AMP Bank, Andreessen Horowitz, ANZ New Zealand, ARM, Authasas, Avanza Pension Forsakring AB, Avid Life Media, Axiata Group Berhad, Axis Bank, Bank of America, Bank Pekao, BBVA, Best Buy, Biometrics Associates, BlackBerry, BluePrint Ventures, BMO Bank of Montreal, BNZ, Bouygues Telecom, Breach Level Index, Cambridge Savings Bank, Chase Bank, China Mobile, China Telecom, Chiquita, Citi, Cognitec Systems, Commonwealth Bank of Australia, CUA, Cyber Streetwise, Dailymotion, Deezer, Descartes Biometric, Deutsche Telekom, DFJ, Dialog Axiata, DISH Network, DNB, Dropbox, Early Warning, Eesti Telefon, Eesti Uhispank, eftpos Australia, Egis, ELAN Microelectronics Corporation, EMT, EMVCo, Enstream, EnteCard, Entersekt, ePlanet Capital, Equant, Equifax, Ericsson, Etihad Airways, Etisalat, ETrade, Evernote, EyeVerify, FacialNetwork, Feedzai, Feitian, FIS, ForgeRock, Frost Bank, Fujitsu, Getin Bank, GKM Newport, GlobalPlatform, Glynn Capital, Google, GoTrust, Greylock Partners, GSMarena.com, Hansapank, Huawei, Hypersecu, HYPR Corp, Infineon, ING, Intelligent Environments, Intercede, JP Sensor Corporation, Kapruka, Khosia Ventures, LastPass, LaunchKey, Lenovo, LinkedIn, Lloyds Bank, Lowe's, March Capital Partners, MasterCard, MCX, Meritech Capital Partners, MGM, Microsoft, MicroStrategy, Mi-Token, Mobey Forum, Mobile World Capital, Mobitel, MyDeal, NatWest Bank, NCSA (National Cyber Security Alliance), Netsize, NEXT Biometrics, Nok Nok Labs, Nomura Research Institute, NTT DoCoMo, NXP, Oak Investment Partners, OCBC Bank, OnePlus, OnePoll, Ooredoo, Oppo, Opus Capital, Orange, OSPT Alliance, PayPal, PeopleSoft, Ping Identity, Placard, ProVenture Management, Qualcomm, Rave Wireless, RBC, RBS, RE/MAX, Relay Ventures, Room66, RRE Ventures, Rustic Canyon Partners, SafeNet, Sainsbury's, Samsung, Santander, Scalado AB, SD Association, SecureKey, Securitas AB, Semble, Sensory, Sequoia Capital, Sharp, Simple, SK Planet, Smart Card Alliance, Softcard, Sonavation, Sony, SpareBank 1, Sparebanken Vest, Standard Bank, StrongAuth, Summit Partners, Sunrise, Synaptics, Tangerine Bank, Tapit, Tata Teleservices, Telecom Italia, Telefonica, Telelogic, Telenor, TeleSign, Telmex, Telstra, Tendryon, Tinder, Trivnet, Trüb AG, TrustZone, Turkcell, TWMP (Taiwan Mobile Payment Co), UK Cards Association, VALID, Validity Sensors, Verizon, Vettro, VimpelCom, Visa, Visa Europe, Vodafone, VUB, Walmart, Webster Bank, Western Union, WoW, Xolo, Yubicon, Yulong, ZTE.

Data & Interactive Forecast

Juniper Research's highly granular IFxls (Interactive Forecast Excels) enable clients to manipulate Juniper's forecast data and charts to test their own assumptions, perform what-if analysis; and compare select markets side by side in customised charts and tables.

IFxls greatly increase clients' ability both to understand a particular market and to integrate their own views into the model.

Forecast suite includes:

  • Mobile biometric authentication payment users, usage and transaction values, split by contactless and remote payments.
  • Mobile identity and universal login service users, service pricing and operator service revenues.
  • Splits by 8 Key Regions and by 9 Key Markets (Canada, Denmark, Germany, Norway, Portugal, Spain, Sweden, US and UK)
  • Interactive Scenario tool allowing user the ability to manipulate Juniper's data for 10 different metrics.

Access to the full set of forecast data of 42 tables and nearly 4,600 data points.

Table of Contents

Market Trends & Competitive Landscape

1. Creating a Unique Digital Identity

  • 1.1. Introduction
    • 1.1.1. The Rise in Data Theft
      • Figure 1.1: Global Criminal Data Breaches Per Annum, Forecast, 2015-2020
      • i. Case Study: Anthem, Premera Blue Cross, Ashley Madison
      • ii. Identity Theft
  • 1.2. Securing the Transaction: Tokenisation
    • Figure 1.2: Tokenisation Procedure
    • 1.2.1. Benefits Of Tokenisation
    • 1.2.2. Criticisms of Tokenisation
    • 1.2.3. Tokenisation Deployments
  • 1.3 Data Protection: Two-Factor Authentication
    • 1.3.1. The Password Problem
    • 1.3.2. From 'Something I know' to 'Something I am': The Biometric Opportunity
      • Figure 1.3: Smartphone Models Launched Featuring Fingerprint Sensors, Q3 2013-03 2015
        • ii. Case Study: Touch ID
      • Figure 1.4: Banks Offering Touch ID, August 2015
      • Figure 1.5: Trends in Average Flagship Smartphone Screen Size (inches), 2009-2015
    • 1.3.3. Authentication & Identification in Enterprise
  • 1.4. Creating a Mobile Identity
    • 1.4.1. Business Case - MNOs
    • 1.4.2. Business Case - Third Parties
    • 1.4.3. GSMA Mobile Connect
      • i. Support
        • Figure 1.6: Mobile Connect Login Procedure
      • ii. Security
        • Figure 1.7: Mobile Connect, Levels of Authentication
      • iii. Deployment
      • iv. Adoption
        • Figure 1.8: FIDO Registration Process
  • 1.5 Mobile ID in Practice
    • 1.5.1. Universal Login - Swisscom

2. Challenges & Stakeholder Strategies

  • 2.1. Introduction
  • 2.2. Juniper Growth Phase Analysis for Mobile Authentication Identity
    • Figure 2.1: Juniper Phased Evolution Model for Tokenisation, Biometric Authentication and Mobile Identity
  • 2.3. Tokenisation Challenges
  • 2.4. Fingerprint Authentication: Challenges
    • Figure 2.2: TEE Interaction with OS & SE
  • 2.5. Facial/Iris Recognition: Challenges
  • 2.6. Mobile Identity Challenges
    • Figure 2.3: Mobile ID Consumer Journey
    • Figure 2.4: Consumer Spend Uplift with Mobile ID Pricing of $1/Month, Selected Markets
    • i. Case Study: au ID
  • 2.7. Challenge Assessment
    • Figure 2.5: Juniper Challenge Assessment Quadrant

3. Competitive Landscape

  • 3.1. Introduction
  • 3.2. Vendor Analysis
    • 3.2.1. Vendor Assessment Criteria
      • Table 3.1: Mobile Identity & Authentication Vendor Assessment Criteria
    • 3.2.2. Limitations & Interpretation
    • 3.2.3. Vendor Analysis: Capability Assessment & Market Positioning
      • Figure 3.2: Identity & Authentication Vendor Analysis Scoring Matrix: Capability & Capacity vs Product & Position
      • Figure 3.3: Mobile Identity & Authentication Vendor Positioning Matrix 2015.
    • 3.2.4. Vendor Groupings
      • i. Summary
      • ii. On Track Vendors
      • iii. Vendors Exceeding Expectations
      • iv. Vendors with Further Potential
    • 3.2.5. Juniper Competitive Web Analysis
      • Figure 3.4: Juniper Competitive Web: Selected Authentication Vendors
  • 3.3. Mobile Authentication & Identity Movers & Shakers
  • 3.4. Vendor Profiles
    • 3.4.1. Bell ID
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Bell ID Key Strengths and Strategic Development Opportunities
    • 3.4.2. Encap Security
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
        • Figure 3.9: Identity Certainty Platform
      • v. Juniper's View: Payfone's Key Strengths and Strategic Development Opportunities
    • 3.4.3. Gemalto
      • i. Corporate
        • Figure 3.5: Gemalto Financial Snapshot, 2013-2014
      • ii. Geographic Spread
      • ii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Gemalto Key Strengths and Strategic Development Opportunities
    • 3.4.4. Giesecke & Devrient
      • i. Corporate
        • Figure 3.6: Giesecke & Devrient Financial Snapshot, 2013-2014
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Giesecke & Devrient Key Strengths and Strategic Opportunities
    • 3.4.5. Good Technology
      • i. Corporate
        • Table 3.7: Good Technology Financial Performance Snapshot, 2013-
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Good Technology Key Strengths and Strategic Development Opportunities
    • 3.4.6. IBM
      • i. Corporate
        • Table 3.8: IBM Financial Performance Snapshot, 2013-2014
      • ii. Geographical Coverage
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: IBM Key Strengths and Strategic Development Opportunities
    • 3.4.7. 0kta
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Okta Key Strengths and Strategic Development Opportunities
    • 3.4.8. Oberthur Technologies
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of 0rferings
      • v. Juniper's View: Oberthur's Key Strengths and Strategic Development Opportunities
    • 3.4.9. Payfone
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of 0rferings
        • Figure 3.9: Identity Certainty Platform
      • v. Juniper's View: Payfone's Key Strengths and Strategic Development Opportunities
    • 3.4.10. Precise Biometrics
      • i. Corporate
        • Table 3.10: Precise Biometrics Financial Performance Snap
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Precise Biometrics' Strengths and Strategic Opportunities
    • 3.4.11. Safran (Morpho)
      • i. Corporate
        • Table 3.11: Safran Financial Performance Snapshot, 2014-2015
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Safran Key Strengths and Strategic Development Opportunities
    • 3.4.12. Tele Sign
      • i. Corporate
      • ii. Geographic Spread
      • ii. Key Clients & Strategic Partnerships
      • iv. High Level View of 0fferings
      • v. Juniper's View: TeleSign Key Strengths and Strategic Development Opportunities

Market Sizing & Forecasts

1. Biometric Authentication & Mobile ID: An Overview

  • 1.1. Biometric Authentication
    • 1.1.1. From ‘Something I know' to ‘S omet hing I am': The Biometric Opportunity
      • i. Fingerprint Sensors
        • Figure 1.1: Smartphone Models Launched Featuring Fingerprint Sensors, Q3 2013-03 2015
      • ii. Facial/Eye Recognition
      • iii. Alternative Biometric Identifiers
        • Figure 1.2: Trends in Average Flagship Smartphone Screen Size (inches), 2009-2015
      • iv. Consumer Perception of Biometric Identifiers
  • 1.2. Creating a Mobile Identity
    • 1.2.1. Business Case - MNOs
    • 1.2.2. Business Case - Third Parties

2. Methodology

  • 2.1. Introduction
  • 2.2. Biometric Authentication Forecast Model
  • 2.3. Mobile Identity Forecast Model
    • Figure 2.1: Methodology: Biometric Authentication Market Sizing & Forecasts
    • Figure 2.2: Methodology: Mobile Identity Market Sizing & Forecasts

3. Biometric Authentication Forecasts

  • 3.1. Biometric Availability
    • Figure & Table 3.1: Smartphones Featuring Fingerprint Authentication as a Percentage of Total Smartphone Installed Base (%), Split by 8 Key Regions 2015-2020
    • Figure & Table 3.2: Total Smartphones Featuring Fingerprint Biometric Scanners Installed Base (m), Split by 8 Key Regions 2015-2020
  • 3.2. Biometric Authentication Adoption: Contactless Payments
    • Figure & Table 3.3: Percentage of Smartphones with Biometric Scanners Using Scanners for Contactless Payment Authentication (%), Split by 8 Key Regions 2015-2020
    • Figure & Table 3.4: Total Number of Smartphones Using Biometric Authentication for Contactless Payments (m), Split by 8 Key Regions 2015-2020
  • 3.3. Biometric Authentication Usage Levels: Contactless Payments
    • Figure & Table 3.5: Smartphones, Average Number of Biometrically Authenticated Contactless Transactions Per Device Per Annum, Split by 8 Key Regions, 2015-2020
    • Figure & Table 3.6: Smartphones, Total Number of Biometrically Authenticated Contactless Transactions Per Annum (m), Split by 8 Key Regions 2015-2020
  • 3.4. Biometric Authentication Transaction Value: Contactless Payments
    • Figure & Table 3.7: Smartphones, Average Value of Biometrically Authenticated Contactless Transactions ($), Split by 8 Key Regions 2015-2020
    • Figure & Table 3.8: Smartphones, Total Transaction Value, Biometrically Authenticated Contactless Transactions ($m), Split by 8 Key Regions 2015-2020
  • 3.5. Biometric Authentication Adoption: Remote Payments
    • Figure & Table 3.9: Smartphone Users Making Remote Payments for Physical Goods (m), Split by 8 Key Regions 2015-2020
    • Figure & Table 3.10: Percentage of Smartphone Remote Payment Users Verifying Purchases via Biometrics (%)Split by8 Key Regions 2015-2020
    • Figure & Table 3.11: Number of Smartphone Remote Payment Users Verifying Purchases via Biometrics (m)Split by8 Key Regions 201-2020
  • 3.6. Biometric Authentication Usage Levels: Remote Payments
    • Figure & Table 3.12: Average Number of Remote Smartphone Remote Payments Per User Per Annum that are Biometrically Verified, Split by 8 Key Regions 2015-2020
    • Figure & Table 3.13: Total Number of Remote Smartphone Payments Per Annum that are Biometrically Verified (m), Split by 8 Key Regions 2015-2020
  • 3.7. Biometric Authentication Transaction Value: Remote Payments
    • Figure & Table 3.14: Average Remote Payment Transaction Value($) Split by 8 Key Regions 2015-2020
    • Figure & Table 3.15: Total Transaction Value, Biometrically Verified Remote Payments ($m,) Split by 8 Key Regions 2015-2020
  • 3.8. Total Biometric Transaction Volume
    • Figure & Table 3.16: Smartphones, Total Biometrically Authenticated Mobile Transaction Volumes (m), Split by 8 Key Regions 2015-2020
  • 3.9. Total Biometric Transaction Value
    • Figure & Table 3.17: Smartphones, Total Biometrically Authenticated Mobile Transaction Values, By Country & Region ($m), 2015-2020

4. Mobile Identity Forecasts

  • 4.1. Mobile Identity Adoption
    • Figure & Table 4.1: Percentage of Mobile Subscribers Using MSISDN for Single Sign In (%) Split by 8 Key Regions 2015-2020
    • Figure & Table 4.2: Number of Mobile Subscribers Using MSISDN for Single Sign In (m)Split by 8 Key Regions 2015-2020
  • 4.2. Mobile Identity Monetisation
    • Figure & Table 4.3: Average Cost Per Month Per mlD/Universal Customer ($) Split by 8 Key Regions 2015-2020
    • Figure & Table 4.4: Total MNO Direct Revenues from mlD/Universal Login ($m) Split by 8 Key Regions 2015-2020
Back to Top