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

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

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

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 PerspectivesAppendixGlossary of TermsList 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

Samples

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Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

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

Methodology

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:

Method

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

Methodology

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

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Table of Contents

Samples

Companies Mentioned (Partial List)

Methodology

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