From border management to banking and mobile commerce
As Isabelle explains, sectors including banking and mobile commerce are demonstrating a real appetite for the benefits of biometrics.
To further illustrate Isabelle's comments, we selected some of the most evolutionary changes experienced in the field of biometrics in 2017.
A report from the NAFTA (The North American Free Trade Agreement) member notes banks have also been mandated to make use of facial and voice recognition technologies for online identity verification.
A similar scheme is underway in Mexico where the National Banking and Security Commission has issued a rule demanding every bank in the country introduce fingerprint scanners for clients within the next twelve months.
In 2017 the Indian government announced that, in future, Indian citizens would need to link Aadhaar to PAN (Permanent Account Numbers – issued by the Central Board of Direct Taxes), bank accounts. The same obligation applies to a diverse range of savings and investment schemes. One of the major Aadhar changes is also the launch of facial authentication in July 2018.
Given that the Aadhaar number is inextricably linked to the holder's unique biometric data, marrying it to key financial accounts provides a powerful means of meeting KYC (Know Your Customer) obligations, as well as tackling modern menaces such as money laundering and tax evasion.
Around 558 million bank accounts have already been linked with Aadhaar. The total number of bank accounts in the country as per estimates is around 1.1 billion.
In Russia the central bank has started to roll out a major biometrics program named as "Unified Biometrics System" (UBS) in summer 2017. A state-owned firm, Rostelecom, will run the database that will collect face, voice, iris and fingerprint data across the country. In February 2018, Rostelecom, together with Tinkoff Bank, VTB Bank and Pochta Bank, has presented a beta version of its "UBS", a digital platform developed at the request of the Ministry of Communications and Mass Media and the Bank of Russia.
She also highlights that, in different parts of the world, different issues are coming into play.
Biometric Trends, an interview with Isabelle Moeller, CEO Biometrics Institute
Local factors shape a global future for biometrics
In South America, for example, fighting fraud is a clear priority: not just in the financial services domain, but also other potentially vulnerable businesses such as car rental.
Brazil in particular decided to move forward. Previously, the Brazilian Superior Electoral Tribunal (TSE) was granted the right to collect biometric data for voter identification as a means to prevent fraud. Early 2017 the government has announced it wants the TSE to collect biometric data from 140 million citizens by 2020 with a final goal of creating a single citizen database and unified ID card.
In the developing world, the need to provide citizens with irrefutable proof of identity is critical in terms of widening access to bank accounts, government services and much more besides.
In Western Europe and the US, meanwhile, the threat of terrorism continues to loom large.
Biometrics is no magic bullet
Not surprisingly, Isabelle recognizes the potential for further innovation. At the same time, she cautions against the idea that biometrics represents any kind of magic bullet.
An approach of multi-factor authentication is certainly, in most cases, the better way to go.
In other words, however compelling the technology, retaining trust and confidence in the years ahead will demand that stakeholders treat biometrics as one element of a much broader, multi-layered, identification and verification toolkit.
The Biometrics Institute
Founded in 2001, the Biometrics Institute is the leading representative body for this rapidly evolving international industry. As such, it is ideally placed to identify the key trends that are influencing the roll-out of biometric techniques such as fingerprint, face and voice recognition - and the likely shape of things to come.
Its mission is to promote the responsible use of biometrics in an independent and impartial international forum for biometric users and other interested parties.
Multi biometrics – fascinating and intriguing
Few biometric technologies are sparking the imagination quite like Multi biometric recognition.
Equally, its arrival has prompted profound concerns and reactions. But more about that later.
With artificial intelligence and the blockchain, Multi biometric recognition certainly represents a significant digital challenge for all companies and organizations - and especially governments.
In this dossier, you'll discover the 7 Multi biometric recognition facts and trends that are set to shape the landscape in 2018.
Deep learning impact
Market dynamics and dominant use-cases
Mapping of new users
Face recognition and the legal system
1. Top facial recognition technologies
In the race for biometric innovation, several projects are vying for the top spot.
Google, Apple, Facebook, Amazon and Microsoft (GAFAM) are also very much in the mix. All the software web giants now regularly publish their theoretical discoveries in the fields of artificial intelligence, image recognition and face analysis in an attempt to further our understanding as rapidly as possible.
The very latest results of tests conducted in March 2018 and published in May by the US Homeland Security Science and Technology Directorate, known as the Biometric Technology Rally, also provide an excellent indication of the best face recognition software available on the market.
But let’s take a closer look :
The GaussianFace algorithm developed in 2014 by researchers at Hong Kong University achieved facial identification scores of 98.52% compared with the 97.53% achieved by humans. An excellent score, despite weaknesses regarding memory capacity required and calculation times.
Facebook and Google
Again in 2014, Facebook announced the launch of its DeepFace program which can determine whether two photographed faces belong to the same person, with an accuracy rate of 97.25%. When taking the same test, humans answer correctly in 97.53% of cases, or just 0.28% better than the Facebook program.
In June 2015, Google went one better with FaceNet, a new recognition system with unrivaled scores: 100% accuracy in the reference test Labeled Faces in The Wild, and 95% on the YouTube Faces DB. Using an artificial neural network and a new algorithm, the company from Mountain View has managed to link a face to its owner with almost perfect results.
This technology is incorporated into Google Photos and used to sort pictures and automatically tag them based on the people recognized. Proving its importance in the biometrics landscape, it was quickly followed by the online release of an unofficial open-source version known as OpenFace.
Microsoft, IBM and Megvii
A study done by MIT researchers in February 2018 found that Microsoft, IBM and China-based Megvii (FACE++) tools had high error rates when identifying darker-skin women compared to lighter-skin men.
At the end of June, Microsoft announced in a blog post that it had made solid improvements to its biased facial recognition technology.
In May 2018, Ars Technica reported that Amazon is already actively promoting its cloud-based face recognition service named Rekognition to law enforcement agencies. The solution could recognize as many as 100 people in a single image and can perform face match against databases containing tens of millions of faces.
2. Learning to learn through deep learning
The feature common to all these disruptive technologies is known as deep learning.
Why is it important?
It's a central component of the latest-generation algorithms and holds the secret to face detection, face tracking and face match as well as real-time translation of conversations.
Deep learning uses "a network of artificial neurons imitating the functioning of the human brain," explains Australian robotics expert Peter Corke. "The possibilities offered by this technology will increase as we discover the secrets of our own brains. By understanding the algorithm on which the human brain is based…reverse engineering will allow us to bring the potential of the human brain to artificial networks."
Artificial neural networks are algorithms supplied with several different input values. These are processed by a range of functions which eventually return one output value. These functions initially involve a learning phase in order to calibrate the results produced.
Firstly, the network is supplied with input values and known output results.
Checks are then made to ensure that the network is producing the expected result.
As long as this is not the case, adjustments are made until the system is correctly configured and capable of systematically producing the expected result.
Think about it this way :
The network behaves in a similar way to a black box. It is given input values whose results are not yet known, and will produce an output value.
This experience learning therefore makes it possible to use neural networks for image recognition, face analysis or stock market predictions, for example.
3. Facial recognition markets
Face recognition markets
A study in June 2016 estimated that by 2022, the global face recognition market would generate $9.6 billion of revenue, supported by a compound annual growth rate (CAGR) of 21.3% over the period 2016-2022.
This increases to 22.9% growth if we take government administrations alone, the biggest drivers of this growth.
The main facial recognition applications can be grouped into three key categories.
Top 3 application categories
1. Security - law enforcement
This market is led by increased activity to combat crime and terrorism, as well as economic competition.
The benefits of facial recognition for policing are evident: etection and prevention of crime.
Facial recognition is used when issuing identity documents, and most often combined with other biometric technologies such as fingerprints.
Face match is used at border checks to compare the portrait on a digitized biometric passport with the holder's face.
Face biometrics can also be employed in police checks although its use is rigorously controlled in Europe. In 2016, the "man in the hat" responsible for the Brussels terror attacks was identified thanks to FBI facial recognition software. The South Wales Police implemented it at the UEFA Champions League Final in 2017.
Significant advances have been made in this area.
Thanks to deep learning and face analysis, it is already possible to:
track a patient's use of medication more accurately
detect genetic diseases such as DiGeorge syndrome with a success rate of 96.6%
support pain management procedures.
3. Marketing and retail
This area is certainly the one where use of facial recognition was least expected. And yet quite possibly it promises the most. Know Your Customer (KYC) is sure to be a hot topic in 2018. This important trend is being combined with the latest marketing advances in customer experience.
By placing cameras in retail outlets, it is now possible to analyze the behavior of shoppers and improve the customer purchase process.
Like the system recently designed by Facebook, sales staff are provided with customer information taken from their social media profiles to produce expertly customized responses.
How long before the selfie payment?
Since 2017, KFC, the American king of fried chicken, and Chinese retail and tech giant Alibaba, have been testing a face recognition payment solution in Hangzhou, China.
So, Minority Report could soon become the present, not the future!
4. Mapping of new users
While the United States currently offers the largest market for face recognition opportunities, the Asia-Pacific region is seeing the fastest growth in the sector. China and India lead the field.
Facial recognition is the new hot tech topic in China from banks and airports to police. Now authorities are expanding the facial recognition sunglasses program as police are beginning to use them in the outskirts of Beijing.
China is also setting up and perfecting a video surveillance network countrywide. 176 million surveillance cameras were in use at the end of 2017 and 626 million are expected by 2020.
In India, the Aadhaar project is the largest biometric database in the world. It already provides a unique digital identity number to 1.2 billion residents. UIDAI, the authority in charge, announced that facial authentication will be launched by July 1, 2018. Face authentication will be available as an add-on service in fusion mode along with one more authentication factor like fingerprint, Iris or OTP.
In Brazil, the Superior Electoral Court (Tribunal Superior Eleitoral) is involved in a nationwide biometric data collection project. The aim is to create a biometric database and unique ID card by 2020, recording the information of 140 million citizens.
Russia's Central Bank has been deploying a country-wide program since 2017 designed to collect faces, voices, iris scans and fingerprints.
5. When Multi recognition strengthens the legal system
The ethical and societal challenge posed by data protection is radically affected by the use of facial recognition technologies.
Do these technological feats, worthy of science-fiction novels, genuinely threaten our freedom? And with it our anonymity?
In Europe, the General Data Protection Regulation (GDPR) provides a rigorous framework for these practices. Any investigations into a citizen's private life or business travel habits are out of the question and any such invasions of privacy carry severe penalties. Applicable from 25 May 2018, the GDPR supports the principle of a harmonized European framework, in particular protecting the right to be forgotten and the giving of consent through clear affirmative action. This directive is bound to have international repercussions.
In America, the State of Washington is the third US state to formally protect biometric data through a new law introduced in June 2017.
In India, thanks to the Puttaswamy judgment delivered on 27 August 2017, the Supreme Court has enshrined the right to privacy in the country's constitution. This progressive decision has rebalanced the relationship between citizen and state, and poses a new challenge to expansion of the Aadhaar project in 2018.
Rebound effect: the legal system and its professions get even stronger. As both ambassadors and guardians of data protection regulation, the post of data protection officer has become necessary for businesses and a much sought-after role.