Facial Recognition Technology in the Smart Retail, Transport, Financial Services, and Automotive Applications Market Comprehensive Study by Leading Key Players | Alibaba, Amazon, Apple, BMW, Bosch, Tencent, Google, Samsung

HTF Market Intelligence released a new research report of 70 pages on title 'Developments and Opportunities for Facial Recognition Technology in the Smart Retail, Transport, Financial Services, and Automotive Applications Industry' with detailed analysis, forecast and strategies.

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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.

Companies Mentioned in the Report:

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

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Table of Contents

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 O

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