Overview and Scope
Face-swiping payment refers to a payment mechanism that utilizes biometric facial recognition technology. It is used by customers for a faster transaction process at retail stores, restaurants, and other businesses, offering a seamless and contactless payment experience.
Sizing and Forecast
The face swiping payment market size has grown rapidly in recent years. It will grow from $5.79 billion in 2023 to $6.93 billion in 2024 at a compound annual growth rate (CAGR) of 19.7%. The growth in the historic period can be attributed to volatility in fuel prices, government incentives and regulations, environmental awareness, expansion of biofuel infrastructure, strategic alliances in the automotive industry.
The face swiping payment market size is expected to see rapid growth in the next few years. It will grow to $14.12 billion in 2028 at a compound annual growth rate (CAGR) of 19.5%. The growth in the forecast period can be attributed to stringent emission standards, consumer awareness and environmental consciousness, global expansion of biofuel infrastructure, incentives for sustainable transportation, collaboration in renewable energy initiatives.. Major trends in the forecast period include integration of advanced engine technologies, focus on increasing fuel efficiency, development of hybrid flex fuel vehicles, education and awareness initiatives, incorporation of renewable fuel standards (rfs), focus on research and development for advanced biofuels..
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Segmentation & Regional Insights
The face swiping payment market covered in this report is segmented –
1) By Type: Payment Equipment, Payment System
2) By Technology: Facial Recognition, Image Recognition
3) By Application: Retail, Restaurant, Travel, Other Applications
Asia-Pacific was the largest region in the face swiping payment market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the face swiping payment market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Major Driver Impacting Market Growth
Rising demand for contactless payments is expected to propel the growth of the face-swiping payment market going forward. Contactless payments refer to a wireless financial transaction in which the customer makes a purchase by moving a security token in close proximity to the vendor’s terminal. Contactless payments use face-swiping payment technology to offer speed and convenience, as users can complete transactions without physical contact with cards or devices. For instance, in 2022, according to reports shared by UK Finance, a UK-based financial services company, in 2022, around 17 billion contactless payments were performed using debit and credit cards, up 30% from 13.1 billion in 2021. Therefore, rising demand for contactless payments is driving the face-swiping payment market.
Key Industry Players
Major companies operating in the face swiping payment market report are Amazon.com Inc., Apple Inc., Alphabet Inc., Samsung Electronics Co. Ltd., Tencent Holdings Ltd., Visa Inc., NEC Corporation, WeChat Pay, Xiaomi Corporation, Alipay, PAX Global Technology Limited, UnionPay International Co. Ltd., CloudWalk Technology Co. Ltd., Facephi Biometria SA, Mastercard Inc., Zoloz Co. Ltd., Innovatrics, VisionLabs B.V., Smile Identity, FacePay Inc., FaceTec Inc., Telepower Communication Co. Ltd., PopID Inc., PayByFace B.V., SnapPay Inc.
The face swiping payment market report table of contents includes:
1. Executive Summary
2. Face Swiping Payment Market Characteristics
3. Face Swiping Payment Market Trends And Strategies
4. Face Swiping Payment Market – Macro Economic Scenario
5. Global Face Swiping Payment Market Size and Growth
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31. Face Swiping Payment Market Other Major And Innovative Companies
32. Global Face Swiping Payment Market Competitive Benchmarking
33. Global Face Swiping Payment Market Competitive Dashboard
34. Key Mergers And Acquisitions In The Face Swiping Payment Market
35. Face Swiping Payment Market Future Outlook and Potential Analysis
36.Appendix
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