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Developments and Opportunities for Facial Recognition Technology in the Smart Retail, Transport, Financial Services, and Automotive Applications Industry

  • ID: 4662836
  • Report
  • October 2018
  • Region: Global
  • 70 pages
  • Market Intelligence & Consulting Institute (MIC)


  • Advicy Drive
  • British Airway
  • Ford
  • Huishang Bank
  • Mizuho Bank
  • Seeing Machines

Facial recognition technology has been commercialized since the late 1990s. However, it did not quite get the attention it deserved until the September 11 attacks. Since then, market demand for advanced human-machine interaction interfaces soared in national security and personal property security in light of the rising awareness on anti-terrorism, the change in economic activities from traditional offline transactions to e-commerce and the lifestyle evolution which now craves for smart living.

This report provides an overview of the facial recognition development in the smart retail, transport, financial services, and automotive application industry; examines advantages and disadvantages of the technology in the abovementioned industries; highlights the use cases and applications that have the highest growth potential in driving the implementation of facial recognition in these four industries.

List of Topics

  • Development of facial recognition technology in the smart retail, transport, financial services, and automotive application industry, touching on the advantages and disadvantages brought by the technology
  • Use cases and application of leading players in the smart retail, transport, financial services, and automotive application industry
  • Development of facial recognition patent applications and the results of the patent miningthat highlightmajordevelopment trends and applications of facial recognition technology
Note: Product cover images may vary from those shown


  • Advicy Drive
  • British Airway
  • Ford
  • Huishang Bank
  • Mizuho Bank
  • Seeing Machines

1. Introduction to Facial Recognition Technology

2. The Retail Industry Has Strong Demand for Data While Transforming
2.1 Transformation Underway
2.2 Customer-centric Retail Model Needs Data Support

3. Demand for Data Brings New Opportunities for Facial Recognition
3.1 Winning Back Lost Consumers as the Start Point of a Consumer-centric Retail Model
3.1.1 Execution is the Key
3.2 Online Retailers Seize Potential Consumers with Retargeting (Data Analytics)
3.2.1 Big Data Analytics as a Major Means for Retailers to Retarget Consumers
3.3 Physical Retailers to Better Compete with E-commerce Retailers with More Precise Data via Facial Recognition
3.3.1 Facial Recognition Makes Consumer Identity and Attribute Information Available

4. Facial Recognition Reinforces Physical Retailers' Advantages and Reduce Disadvantages
4.1 Facial Recognition Enhances In-store Shopping Experience
4.1.1 Turn Shopping into an Experience
4.1.2 Facial Recognition Helps Collect Consumer Behavior Data and Optimize Shopping Experience
4.2 Facial Recognition Helps Physical Retailers Reduce Operation Costs
4.2.1 Data and Automation as Key to Effective Allocation and Reduction of Human Resources
4.2.2 Data and Logistics as Key to Warehouse Inventory Management

5. Mature Software and Hardware Systems Reduce Introduction Cost
5.1 Enhancement in PC Performance and Maturity of Recognition Technology Drives Facial Recognition towards Commercialization

6. Privacy a Stumbling Block to Facial Recognition
6.1 Winning the Hearts of Consumers with Practical Benefits to Reduce Objection to Facial Image Collection
6.2 Retailers' Brand Image Influences Consumers' Acceptance of Facial Recognition

7. Application Cases of Facial Recognition Technology in Transport Industry
7.1 Transport Management System
7.1.1 Immigration Inspection: Automated Gate System at Japanese Narita Airport
7.1.2 Crime Tracking: Security System at China’s Hohhot Railway Bureau
7.2 Air Transport Industry
7.2.1 Passage Management: KLM's Boarding System
7.3 Land Transport Industry
7.3.1 Crime Prevention: Uber’s Driver Verification System in the US
7.3.2 Permission Management: Chinese Didi Chuxing’s Car Rental System
7.4 Car and Automotive Electronics Industries
7.4.1 Driver Alerts: Japanese Omron’s Driver Concentration Sensing Technology
7.4.2 Behavior Analysis: German Bosch’s Concept Car

8. Application of Facial Recognition in the Transport Industry
8.1 Mainly Used in Public Transport and Infrastructure for ID Authentication Purposes
8.2 Online Car-Hailing Service Providers Use Facial Recognition to Prevent Crimes
8.3 Car Industry Widely Use Facial Recognition for Car Design

9. Opportunities for Facial Recognition in the Transport Industry
9.1 National Policies Accelerate the Adoption of Facial Recognition in Public Transport Worldwide
9.1.1 Facial Recognition Leapfrogs Ahead as Iris and Fingerprint Recognition Fail to Meet Expectations
9.1.2 ICAO’s Implementation Ensures Facial Recognition Development
9.1.3 Adoption of Facial Recognition from Passports to e-Gate Systems is Progressively Done
9.2 Smart Cars Create New Opportunity for Facial Recognition

10. Use Cases of Facial Recognition Technology Application in the Financial Services Industry
10.1 MasterCard Focuses on Increasing Consumption and Preventing Unauthorized Use
10.2 China's Bank of Jiangsu Take Aims at Offering Convenient Withdrawal Service and Preventing Unauthorized Use
10.3 Japan's Daiwa Securities Group Aims to Enhance Work Efficiency and Personal Information Protection
10.4 China's Ping An Focuses on Shortening the Time for Credit Investigation and Lowering Loan Risks
10.5 US HSBC Works on Accelerating Financial Services Process
10.6 Japan's Mizuho Bank Take Aims at Marketing and Offering Customer Services

11. Analysis on the Application Model of Facial Recognition Technology
11.1 Identity Authentication is the Major Purpose of Facial Recognition Technology
11.2 A Higher Proportion of Financial Services Industry in China Uses Facial Authentication
11.3 Facial Authentication is Commonly Used for Staff Management in the Japanese Financial Services Industry

12. Future Prospects of Facial Recognition Technology in the Financial Services Industry
12.1 Fintech is Major Growth Enabler but It Does Not Particularly Favor Facial Authentication
12.2 Consolidating Facial Recognition Technology into Mobile Devices is Key
12.2.1 Vein Authentication is Mainly Used in ATM Machines. Iris and Facial Authentication are Joining the Game in Recent Years.
12.2.2 Smartphones have Become Major Means in Financial Services Development; Vein Authentication and Facial Authentication Have Great Potential

13. Development of Facial Recognition Technology for Automobiles
13.1 Widespread Use of Biometric Technologies in Automotive Applications
13.2 Smart Cars Bringing New Opportunities for Facial Recognition

14. Development of Facial Recognition Patent Applications
14.1 Patent Search
14.2 Trends in Patent Applications
14.2.1 US and Japan Jointly Hold Over 80% of USPTO Patent Grants
14.2.2 Majority of Assignees are Automobile Vendors

15. Development Trends of Facial Recognition Technology and Application Areas
15.1 Applications Focus Mainly on Facial Detection
15.2 Majority of Patent Grants are for Security Purposes
15.2.1 60% of Patent Grants Are on Driving Safety Enhancement
15.2.2 Driver's Attention Level is Enhanced
15.2.3 Potential Causes of Distracted Driving is Reduced
15.2.4 System Operation Enhancement as Another Key Development Focus
15.3 Other Applications
15.3.1 Entertainment
15.3.2 Employee Performance or Insurance Fee Assessment for Private Companies

Author Perspectives
Glossary of Terms
List of Companies

List of Tables
Table 1 Facial Recognition Applications in the Transport Industry Worldwide
Table 2 National Policies and Programs for Biometric Identification Systems
Table 3 Automotive Product Manufactures and Their Biometric Technology
Table 4 Case of Facial Recognition Technology in Financial Services Industry
Table 5 Biological Feature Recognition in Financial Services Industry
Table 6 Iris and Facial Recognition Technology for ATM Machines
Table 7 Biometric Recognition Technologies Adopted in Automotive Industry
Table 8 Patent Search Settings and Results

List of Figures
Figure 1 Applications of Facial Recognition Technology
Figure 2 Renting Process of DiDi Car Rental
Figure 3 Omron’s Driver Concentration Sensing Technology
Figure 4 Facial Recognition Procedures of MasterCard Online Payment
Figure 5 Ten Plans Proposed by the Financial Supervisory Commission R.O.C (Taiwan) for Fintech Development
Figure 6 Distribution of Facial Recognition Patent Grants by Country of Origin
Figure 7 Distribution of Patent Grants by Assignee
Figure 8 Major Purposes of Facial Recognition for Automotive Applications
Figure 9 Steps in the Facial Recognition Process57
Figure 10 Facial Recognition Patents for Automotive Applications by Technology Type
Figure 11 Facial Recognition Patents for Automotive Applications by Application (Excluding Law Enforcement Applications in Public Sectors or Business Applications in Private Sectors)
Figure 12 Patent Title: Sensing and Managing Vehicle Behavior Based on Occupant Awareness
Figure 13 Patent Title: Adjusting Speakers Using Facial Recognition Technology

Note: Product cover images may vary from those shown


  • Advicy Drive
  • Affectiva
  • Alibaba
  • Alipay Cloud
  • Amazon
  • AndPay
  • Ant Financial Services Group
  • Apple
  • Bank of Jiangsu
  • Bank of Okinawa
  • BC Card
  • Beijing Xiaoju Technology
  • Blackberry
  • BMW
  • Bosch
  • British Airway
  • Careem
  • China CITI
  • China Merchants Bank
  • Conduent
  • Craft Silicon
  • Criteo
  • Daiwa Securities Group
  • Denso
  • Didi Chuxing
  • Disney
  • Empatica
  • Facebook
  • Fiat Chrysler Automobiles
  • Financial Supervisory Commission
  • Ford
  • Fujitsu
  • Gentex
  • Gestigon
  • GM
  • Google
  • Grab
  • Harman
  • Hewlett-Packard
  • Hiroshima Bank
  • Hitachi
  • Honda
  • HP
  • HSBC
  • Huishang Bank
  • Hyundai
  • IBM
  • Industrial Bank of Korea
  • Jaguar Land Rover
  • KLM Royal Dutch Airlines
  • Konica Minolta
  • Lakala Payment
  • Lexus
  • Lytx
  • MasterCard International
  • McKinsey
  • Media Lab
  • Mizuho Bank
  • MYbank
  • NEC
  • Nippon Electric Company
  • Omron
  • Outerspace Design
  • Panasonic
  • People’s Bank of China
  • Ping An Insurance (Group) Company of China
  • Ltd.
  • Ping An Puhui
  • Polyvore
  • Qian Hai Zheng Xin
  • Rong 360
  • Samoyed
  • Samsung
  • Seeing Machines
  • Shopzilla
  • Smile
  • Sober Steering
  • Softbank
  • Sumitomo Mitsui Banking Corporation
  • Synaptics
  • Taikang Life Insurance
  • Tencent
  • Thanko
  • Toyota
  • Uber
  • Vigo
  • VocalZoom
  • WeBank
  • Xeron
  • YuanBaoPu
  • ZTE
Note: Product cover images may vary from those shown

Primary research with a holistic, cross-domain approach

The exhaustive primary research methods are central to the value that the analyst delivers. A combination of questionnaires and on-site visits to the major manufacturers provides a first view of the latest data and trends. Information is subsequently validated by interviews with the manufacturers' suppliers and customers, covering a holistic industry value chain. This process is backed up by a cross-domain team-based approach, creating an interlaced network across numerous interrelated components and system-level devices to ensure statistical integrity and provide in-depth insight.

Complementing primary research is a running database and secondary research of industry and market information. Dedicated research into the macro-environmental trends shaping the ICT industry also allows the analyst to forecast future development trends and generate foresight perspectives. With more than 20 years of experience and endeavors in research, the methods and methodologies include:


  • Component supplier interviews
  • System supplier interviews
  • User interviews
  • Channel interviews
  • IPO interviews
  • Focus groups
  • Consumer surveys
  • Production databases
  • Financial data
  • Custom databases


  • Technology forecasting and assessment
  • Product assessment and selection
  • Product life cycles
  • Added value analysis
  • Market trends
  • Scenario analysis
  • Competitor analysis