Global Biometric In-store Payments Market 2024-2028: Full Research Suite

Our Biometric In-store Payments research suite provides in-depth analysis and evaluation of how the in-store payments ecosystem is adapting to include biometric payment solutions. Focusing on palm vein, fingerprint recognition, facial recognition and iris recognition, which can provide greater ease for merchants and consumers.

The suite includes both a data deliverable, sizing the market and providing key forecast data across 60 countries and several different segments, and a Strategy & Forecasts document which gives a complete assessment of the key trends, challenges and recommendations for stakeholders. Collectively, they provide a critical tool for understanding this rapidly emerging market; allowing payment companies, biometric card manufacturers and biometric in-store terminal vendors to shape their future business model.

Key Features
Market Dynamics: Insights into key trends and market expansion challenges within the biometric in-store payments market; addressing challenges posed by the technical and costly nature of biometric in-store payments and ongoing consumer fears regarding level of security. It will also analyse the potential benefits it will be able to provide in the challenging in-store retail market.
Key Takeaways & Strategic Recommendations: In-depth analysis of key development opportunities and key findings within the biometric in-store payments market, accompanied by key strategic recommendations for stakeholders.
Benchmark Industry Forecasts: Overview into biometric in-store payments, including forecasts for total number of biometric-enabled POS terminals, transactions and spend via biometric in-store payments, split by mPOS and dedicated POS.
Juniper Research Competitor Leaderboard: Key player capability and capacity assessment for 16 biometric in-store payments vendors, featuring market size for major players in the biometric-in store payments industry. Delivered via the Juniper Research Competitor Leaderboard.
Alipay
Amazon
Fingerprints
G+D
IDEMIA
IDEX
Ingenico
JPMorgan
Mastercard
OVE Touch&Go
PayByFace
PayEye
Pop ID
Telpo
Tencent
Thales

Please note: the online download version of this report is for a global site license.


1. Key Takeaways & Strategic Recommendations
1.1 Key Takeaways
1.2 Strategic Recommendations
2. Market Landscape
2.1 Introduction
2.2 Definitions and Scope
2.2.1 Definitions
i. Biometric Verification
Figure 2.1: Main Biometric Verification Methods
ii. Biometric Authentication
iii. Biometric In-store
2.2.2 Using Biometric for In-store Payments
i. The Biometric In-store Payment Process
ii. Reason to Authenticate Payments Using Biometrics
2.3 The Retail Market
2.3.1 Evolution of Biometrics in the Retail Market
2.3.2 How Biometric In-store Payments are Transforming the Retail Industry
i. Heightened Transaction Security
ii. Seamless Customer Experience
iii. Personalised Shopping Experiences
iv. Enhanced Loyalty Programmes with Seamless Enrolment
v. Rapid Customer Onboarding
vi. Diverse Authentication Options
vii. Competitive Edge
viii. Customer Service Improvement with Efficient Returns/Exchanges
2.4 Biometric Landscape
2.4.1 Biometric Technology Is Already a Big Part of People’s Lives
2.4.2 Main Applications of Biometrics
i. Online Transactions
ii. In-store Payments
iii. ATM Transactions
iv. Remittances
v. Cryptocurrency
vi. Access Control
vii. Financial Inclusion
viii. Marketing Systems
2.4.3 Limitations of Biometric Systems
i. Failure to Enrol
ii. False Acceptance and Rejection Rates
iii. Spoofing
iv. Compromised Biometrics
2.4.4 Regulatory Landscape for Biometric Payments
2.5 Key Trends & Drivers
2.6 Privacy
2.6.1 Privacy Challenges
i. Function Creep
ii. Covert Collection
iii. Secondary Information
iv. Other Challenges
2.6.2 Biometric and Privacy Laws
2.7 Other Challenges Related to Biometrics
2.7.1 Technical Challenges
2.7.2 Legal Concerns
2.7.3 High Cost
2.7.4 Ethical Issues
3. Payment Form Factors & Segment Analysis
3.1 Biometric Terminals
3.1.1 Palm Vein
i. Definitions
ii. Deployments
Figure 3.1: Palm scanning payment model
iii. Challenges
iv. Future Outlook
3.1.2 Fingerprint
i. Definitions
Figure 3.2: Biometric Terminals’ Accuracy and Cost Comparison
ii. Deployments
iii. Challenges
iv. Future Outlook
3.1.3 Face
i. Definitions
ii. Deployments
iii. Challenges
iv. Future Outlook
3.1.4 Iris and Retina
i. Definition
ii. Deployments
iii. Challenges
iv. Future Outlook
3.1.5 Other Biometric Terminals
i. Voice Waveform Recognition
ii. Earlobe and Hand Geometry Identification
3.2 Biometric Payment Cards
3.2.1 Definition
3.2.2 The Functioning of Biometric Cards
3.2.3 Current Status
Figure 3.3: SCA Authentication
3.2.4 Key Deployments
3.2.5 Challenges
3.2.6 Future Outlook
3.3 Mobile Payment Biometric
3.3.1 Current Status
3.3.2 Key Developments
3.3.3 Future Outlook
3.4 Supermarkets & Hypermarkets
i. Current Status
ii. Key Deployments
3.5 Convenience Stores
i. Current Status
ii. Key Deployment
3.6 QSRs (Quick Service Restaurants)
i. Current Status
ii. Key Development
3.7 Boutiques
4. Competitor Leaderboard & Vendor Profiles
4.1 Why Read This Report
Table 4.1: Juniper Research Competitor Leaderboard Vendors: Biometric In-store Payments
Figure 4.2: Juniper Research Competitor Leaderboard – Biometric In-store Payments
Table 4.3: Juniper Research Competitor Leaderboard: Biometric In-Store Payments Vendor Ranking
Table 4.4: Juniper Research Competitor Leaderboard Biometric In-Store Payments – Heatmap
4.2 Biometric In-store Payments Vendor Profiles
4.2.1 Alipay/Ant Group
i. Corporate
ii. Geographical Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.2 Amazon
i. Corporate
ii. Geographical Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
Figure 4.5: Amazon One, Pay by Palm Technology
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.3 Fingerprints
i. Corporate
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
Figure 4.6: Fingerprints’ Biometric Card
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.4 G+D
i. Corporate
ii. Geographical Spread
iii. Key Clients & Strategic Partnerships
iv. High-level Views of Offerings
Figure 4.7: G+D Convego YOU Card
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.5 IDEMIA
i. Corporate
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
Figure 4.8: IDEMIA’s FCODE Intuitive Enrolment
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.6 IDEX
i. Corporate
Table 4.9: IDEX’s Funding Rounds
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-Level View of Offerings
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.7 Ingenico
i. Corporate
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.8 J.P Morgan
i. Corporate
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offering
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.9 Mastercard
i. Corporate
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
Figure 4.10: Facial Recognition-based ‘Pay by Selfie’ by Mastercard
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.10 OVE Touch & Go
i. Corporate
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.11 PayByFace
i. Corporate
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.12 PayEye
i. Corporate
Table 4.11: PayEye’s Funding Rounds (€m), 2020-
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.13 PopID
i. Corporate
Table 4.12: PopID’s Funding Rounds ($m), 2019-
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.14 Telpo
i. Corporate
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
Figure 4.13: Telpo’s Face Payment Solution
Figure 4.14: Telpo’s Retail Solution Overview
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.15 Tencent
i. Corporate
Table 4.15: Tencent’s Funding Rounds ($bn), 1999-
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.2.16 Thales
i. Corporate
ii. Geographic Spread
iii. Key Clients & Strategic Partnerships
iv. High-level View of Offerings
Figure 4.16: Thales IDPrime FIDO Bio Smart Card
Figure 4.17: Thales Biometric Card Enrolment
v. Juniper Research’s View: Key Strengths & Strategic Development Opportunities
4.1 Juniper Research Leaderboard Assessment Methodology
4.1.1 Limitations & Interpretations
Table 4.18: Juniper Research Leaderboard Assessment Criteria
5. Market Forecasts
5.1 Introduction
5.1.1 Biometric In-store mPOS Forecast Methodology
5.1.2 Biometric In-store Dedicated POS Forecast Methodology
Figure 5.1: Biometric In-store Payments Methodology
5.2 Market Forecast Summary
5.2.1 Total Value of Biometric POS Transactions
Figure & Table 5.2: Total Value of Biometric POS Transactions ($m), Split by 8 Key Regions, 2023-
5.2.2 Total Number of Transactions via Biometric-enabled POS Terminals
Figure & Table 5.3: Total Number of Transactions via Biometric-enabled POS Terminals (m), Split by 8 Key Regions, 2023-
5.2.3 Global Number of Biometric-enabled POS Terminals
Figure & Table 5.4: Total Number of Biometric-enabled POS Terminals (m), Split by 8 Key Regions, 2023-
5.3 mPOS Forecast Summary
5.3.1 Number of mPOS Terminals in Use Featuring Biometric Technology
Figure & Table 5.5: Total Number of mPOS Terminals in Use Featuring Biometric Technology (m), Split by 8 Key Regions, 2023-
5.3.2 Total Value of Biometric mPOS Transactions
Figure & Table 5.6: Total Value of Biometric mPOS Transactions ($m), Split by 8 Key Regions 2023-
5.4 Dedicated POS Forecast Summary
5.4.1 Number of Dedicated POS Terminals in Use Featuring Biometric Technology
Figure & Table 5.7: Total Number of Dedicated Terminals in Use Featuring Biometric Technology (m), Split by 8 Key Regions, 2023-
5.4.2 Total Value of Biometric Dedicated POS Transactions
Figure & Table 5.8: Total Value of Biometric Dedicated POS Transactions ($m), Split by 8 Key Regions, 2023
5.5 Endnotes

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