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Mobile Biometrics for Financial Services: Market & Technology Analysis, Adoption Strategies & Forecasts 2015-2020

  • ID: 3621135
  • December 2015
  • Region: Global
  • 195 Pages
  • Goode Intelligence
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FEATURED COMPANIES

  • Agnitio
  • Cirrus Logic
  • FCA
  • Idair
  • NTT DoCoMo
  • SayPay
  • MORE

This comprehensive report includes a review of current global adoption, market analysis including key drivers and barriers for adoption, interviews with leading stakeholders, technology analysis with review of key biometric technologies and profiles of companies supplying biometric systems for this industry plus forecasts (regional and global) for users and revenue within the six-year period 2015 to 2020.

Today, millions of customers (120 million plus during 2015) are using mobile biometrics on a daily basis around the world to provide secure convenient user authentication and transaction authorisation with this theme set to continue and accelerate.

Adoption is being seen across almost all of the financial services industry; from traditional (ATMs) to alternative (Bitcoin Wallets) – the mobile is fast becoming the biometric authenticator of choice for the financial services industry.

Biometrics is a disruptive force for the financial services industry and is being used by new FinTech entrants, including mobile device manufacturers and mobile platform owners (Apple, Google and Samsung), as a method of dominating the banking and payment experience through ownership READ MORE >

Note: Product cover images may vary from those shown
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FEATURED COMPANIES

  • Agnitio
  • Cirrus Logic
  • FCA
  • Idair
  • NTT DoCoMo
  • SayPay
  • MORE

Executive Summary
ES1 Report Scope
ES2 Market and Technology Analysis
ES 2.1 An Introduction to Biometric Technologies
ES 2.2 How is Biometrics used for Financial Services on Mobile
ES 2.3 Market Drivers and Barriers
ES 2.3.1 Market Drivers
ES 2.3.2 Market Barriers
ES 2.4 Financial Services & Payments Biometric Regulation and Technology Standards
ES 2.5 Technology & Market Adoption
ES 2.5.1 Market Adoption and Analysis
ES 2.6 Biometric Technology – Analysis and Vendors
ES 2.6.1 Behavioral Biometrics
ES 2.6.2 Eye Biometrics
ES 2.6.2.1 Iris
ES 2.6.2.2 Eye-Vein
ES 2.6.3 Face Biometrics
ES 2.6.4 Fingerprint
ES 2.6.5 Voice
ES3 Forecasts
ES4 Conclusions

1 Market and Technology Analysis
1.1 Introduction
1.2 An introduction to Biometric Technologies
1.3 Biometrics Definition
1.4 How Biometrics Works
1.5 Biometric Authentication
1.6 How is Biometrics use in financial services on mobile
1.7 Market Drivers & Barriers
1.7.1 Market Drivers
1.7.2 Market Barriers
1.8 Financial Services & Payments Biometric Regulation and Technology Standards
1.8.1 Introduction
1.8.2 Regulation
1.8.3 State & Federal Regulation
1.8.3.1 European Union (EU) Data Protection Act (DPA)
1.8.3.2 European Union Payment Services Directive (PSD) II
1.8.4 Industry Regulation / Guidelines
1.8.4.1 PCI-DSS
1.8.4.2 USA FFIEC
1.8.4.3 EMV
1.8.4.4 3D Secure
1.8.4.5 Bank of Korea
1.8.4.6 Bank of China
1.8.4.7 Hong Kong – The Office of the Privacy Commissioner for Personal Data
1.8.5 Technoloy Standards
1.8.5.1 Introduction
1.8.5.2 ISO
1.8.5.3 ANSI
1.8.5.4 UK CESG
1.8.5.5 USA NIST
1.8.5.6 FIDO Alliance
1.8.5.7 Natural Security Alliance
1.8.5.8 IEEE Biometric Open Protocol Standard (BOPS)
1.9 Technology and Market Adoption
1.9.1 Market Adoption and Analysis
1.9.1.1 Mobile Biometrics for Financial Services
1.9.1.2 So, Why Biometrics Now?
1.9.1.3 The Move towards Multi-Modal Biometrics
1.9.1.4 Mobile Biometrics for Payments
1.9.1.4.1 Mobile Biometrics for eCommerce Payments
1.9.1.4.1.1 Introduction
1.9.1.4.1.2 Continuous Verification using BehavioSec’s BehavioWeb
1.9.1.4.1.3 BioCatch Behavioral Biometrics reduces Fraud by Securing New Account Set-up and Reduces Vishing Fraud Exposure
1.9.1.4.1.4 Using Biometrics to support Know Your Customer (KYC) and Anti-Money Laundering (AML) methods: Facebanx Biometric Identity Management Solutions
1.9.1.4.2 Mobile Biometrics for mCommerce Payments – Mobile Payments
1.9.1.4.2.1 Introduction
1.9.1.4.2.2 Smart Mobile Device OEMs and Platforms
1.9.1.4.2.2.1 Apple Pay
1.9.1.4.2.2.2 Android Pay
1.9.1.4.2.2.3 Samsung Pay
1.9.1.4.2.3 Card Schemes
1.9.1.4.2.3.1 MasterCard - Pay by Selfie
1.9.1.4.2.4 eCommerce Payment Providers
1.9.1.4.2.4.1 Alipay
1.9.1.4.2.4.2 PayPal
1.9.1.4.2.5 Mobile Network Operators - Direct Carrier Billing
1.9.1.4.2.5.1 NTT DOCOMO
1.9.1.4.3 Mobile Biometrics for Bitcoin Payments
1.9.1.4.3.1 Introduction
1.9.1.4.3.2 Using Biometrics to Secure Bitcoin & Other Digital Currency Platforms by answering the key question, “Am I Who I Say I Am” – HYPR Corp
1.9.1.4.3.3 Case – The Hardware Bitcoin Wallet Secured by Biometrics
1.9.1.4.4 Mobile Biometrics & Cash (ATMs)
1.9.1.4.4.1 Introduction
1.9.1.4.4.2 Mobile Biometrics – The Authenticator for Cash Issued at an ATM
1.9.1.4.4.3 Leveraging Mobile-based Biometrics for ATM Cash Withdrawals – Hoyos Labs 1U ATM
1.9.1.5 Mobile Biometrics for Banking
1.9.1.5.1 Introduction
1.9.1.5.2 Biometrics for Mobile Banking
1.9.1.5.2.1 Introduction
1.9.1.5.2.2 Apple Touch ID – Apple shines a light for mobile banking
1.9.1.5.2.3 USAA Mobile Multi-Modal Biometrics Banking App
1.9.1.5.2.4 Getting Biometrics Integrated into Banking Platforms – Digital Insight adopts EyeVerify’s eye-vein biometrics technology for mobile banking app authentication
1.9.1.5.2.5 EyeVerify Eyeprint ID used as part of multi-modal mobile biometric authentication solution for Mountain America Credit Union (MACU)
1.9.1.5.3 Mobile Voice Biometrics for Telephone Banking / Contact Centre
1.9.1.5.3.1 Introduction
1.9.1.5.3.2 How passive voice biometrics can reduce telephone banking fraud: Integrating Agnitio’s Kivox Passive Detection voice recognition engine into fraud detection systems
1.9.1.5.3.3 Barclays Bank streamlines telephone banking service by adopting voice biometrics
1.9.2 Biometric Technology – Analysis and Vendors
1.9.2.1 Introduction
1.9.2.2 Behavioral Biometrics
1.9.2.2.1 Introduction
1.9.2.2.2 Technology Vendors and Service Providers
1.9.2.2.2.1 BehavioSec
1.9.2.2.2.2 Encap Security
1.9.2.2.2.3 Biometric Signature ID
1.9.2.2.2.4 BioCatch
1.9.2.2.2.5 Advantages and Disadvantages of Behavioral Biometrics
1.9.2.2.3 Eye Biometrics
1.9.2.2.3.1 Introduction
1.9.2.2.3.2 Iris
1.9.2.2.3.2.1 Introduction
1.9.2.2.3.2.2 Technology Vendors and Service Providers
1.9.2.2.3.2.2.1 EyeLock
1.9.2.2.3.2.2.2 Hoyos Labs
1.9.2.2.3.2.2.3 Fotonation / Smart Sensors
1.9.2.2.3.2.2.4 Advantages and Disadvantages of Iris Biometrics
1.9.2.2.3.3 Eye-Vein
1.9.2.2.3.3.1 Introduction
1.9.2.2.3.3.2 Technology Vendors and Service Providers
1.9.2.2.3.3.2.1 EyeVerify
1.9.2.2.3.2.3.2 Advantages and Disadvantages of Eye-Vein Biometrics
1.9.2.2.4 Face Biometrics
1.9.2.2.4.1 Introduction
1.9.2.2.4.2 Technology Vendors and Service Providers
1.9.2.2.4.2.1 Facebankx
1.9.2.2.4.2.2 KeyLemon
1.9.2.2.4.2.3 Daon IdentityX
1.9.2.2.4.2.4 Advantages and Disadvantages of Face Biometrics
1.9.2.2.5 Fingerprint
1.9.2.2.5.1 Introduction
1.9.2.2.5.2 Technology Vendors and service Providers – Fingerprint Sensor Manufacturers and Authentication Integrators
1.9.2.2.5.2.1 Fingerprint Cards
1.9.2.2.5.2.2 IDEX
1.9.2.2.5.2.3 Dermalog
1.9.2.2.5.2.4 Lumidigm - HID Global
1.9.2.2.5.2.5 NEXT Biometrics
1.9.2.2.5.2.6 Sonavation
1.9.2.2.5.2.7 Qualcomm
1.9.2.2.5.2.8 Synaptics Biometric Products Division
1.9.2.2.5.2.9 Nok Nok Labs
1.9.2.2.5.2.10 BIO-key
1.9.2.2.5.2.11 Zwipe
1.9.2.2.5.3 Camera-based Fingerprint Biometrics – Touchless
1.9.2.2.5.3.1 Technology Vendors and Service Providers – Touchless Fingerprint Biometrics
1.9.2.2.5.3.1.1 Diamond Fortress
1.9.2.2.5.3.1.2 Idair
1.9.2.2.5.4 Advantages and Disadvantages of Fingerprint Biometrics
1.9.2.2.6 Voice
1.9.2.2.6.1 Introduction
1.9.2.2.6.2 Technology Vendors and Service Providers
1.9.2.2.6.2.1 Agnitio
1.9.2.2.6.2.2 Nuance
1.9.2.2.6.2.3 Validsoft
1.9.2.2.6.2.4 VoiceVault / SayPay
1.9.2.2.6.2.5 VoiceTrust
1.9.2.2.6.3 Advantages and Disadvantages of Voice Biometrics

2. Forecasts
2.1 Methodology and Assumptions
2.2 Mobile Biometrics for Financial Services Forecasts
2.2.1 Introduction
2.2.2 Mobile Biometrics for Financial Services User Forecasts
2.2.2.1 Mobile Biometrics for Financial Services User Forecasts – By Technology
2.2.2.1.1 Mobile Biometrics for Financial Services User Forecasts – By Technology: Fingerprint
2.2.2.1.1.1 Fingerprint Biometric Users – Forecast Highlights
2.2.2.1.2 Mobile Biometrics for Financial Services User Forecasts – By Technology: Voice
2.2.2.1.2.1 Voice Biometric Users – Forecast Highlights
2.2.2.1.3 Mobile Biometrics for Financial Services User Forecasts – By Technology: Eye (Iris and Eye-Vein)
2.2.2.1.3.1 Eye Biometric Users – Forecast Highlights
2.2.2.1.4 Mobile Biometrics for Financial Services User Forecasts – By Technology: Behavioral
2.2.2.1.4.1 Behavioral Biometric Users – Forecast Highlights
2.2.2.1.5 Mobile Biometrics for Financial Services User Forecasts – By Technology: Face
2.2.2.1.5.1 Face Biometric Users – Forecast Highlights
2.2.2.1.6 Mobile Biometrics for Financial Services User Forecasts – By Technology: Combined
2.2.2.1.6.1 Combined Biometric Users – Forecast Highlights
2.2.2.2.1 Mobile Biometrics for Financial Services User Forecasts – Banking
2.2.2.2.2 Mobile Biometrics for Financial Services User Forecasts – Payments
2.2.2.2.3 Mobile Biometrics for Financial Services User Forecasts – Combined
2.2.3 Mobile Biometrics for Financial Services Revenue Forecasts
2.2.3.1 Assumption on Revenue Forecasts
2.2.3.2 Mobile Biometrics for Financial Services Revenue Forecasts – By Technology: Fingerprint
2.2.3.3 Mobile Biometrics for Financial Services Revenue Forecasts – By Technology: Voice
2.2.3.4 Mobile Biometrics for Financial Services Revenue Forecasts – By Technology: Eye (Iris & Eye-Vein)
2.2.3.5 Mobile Biometrics for Financial Services Revenue Forecasts – By Technology: Behavioral
2.2.3.6 Mobile Biometrics for Financial Services Revenue Forecasts – By Technology: Face
2.2.3.7 Mobile Biometrics for Financial Services Revenue Forecasts – By Technology: Combined
2.2.4 Mobile Biometrics for Payment Transaction & Transaction Value Forecasts
2.2.4.1 Assumptions on Transaction & Transaction Value Forecasts
2.2.4.2 Mobile Biometrics for Payments Transaction Forecasts – Total Transactions
2.2.4.3 Mobile Biometrics for Payments Transaction Forecasts – Total Value ($)

Appendices

Appendix A: Organisation Referenced in this Report

Appendix B: How to Measure Biometric Technology? A Guide to Choosing the Right Biometric System

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- Alipay
- Agnitio
- Apple
- ARM
- Banco
- Santander
- Bank of Lanzhou
- Bank of China
- Bank of Korea
- Barclays
- BehavioSec
- BioCatch
- BIO-key
- Biometrics Signature ID
- British Bankers Association
- Cirrus Logic
- Daon, DARPA
- Diamond Fortress
- Diebold
- EarlyWarning
- Edgar, Dunn & Co.
- EMVCo
- Encap Security
- Ernst & Young
- ECB
- eyeLock
- EyeVerify
- Facebanx
- FFIEC
- FCA
- FFA
- Fingerprint Cards,
- Fotonation
- Fujitsu
- Garanti Bank
- Gemalto Bank
- Google
- Hitachi
- Hoyos Labs
- HYPR Corp.
- Huawei
- Idair
- IDEX
- IEEE
- ING Bank
- IrisGuard
- Isbank
- KeyLemon
- MasterCard
- Microsoft
- NIST
- NCR
- NEXT Biometrics
- Nok Nok Labs
- NTT DoCoMo
- Nuance
- OCBC
- OCC
- OKI
- PayPal
- Pindrop
- Qualcomm
- RBS
- Royal Bank of Canada
- RSA Security,
- Samsung
- SayPay
- St Georges Bank
- Sonavation
- Synaptics
- Tangerine Bank
- Tencent
- The FIDO Alliance
- The Natural Security Alliance
- Trustonic
- USAA
- US Federal Reserve
- ValidSoft
- Verint, VISA
- VoiceTrust
- VoiceVault
- VOXX International
- Westpac
- Wincor Nixdorf
- ZTE

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