The eventual goal is to remove the hassle of dealing with passwords and physical IDs and also expand the use of this technology beyond surveillance and security.
Facial recognition technology works by capturing an individual’s unique facial data, extracting it to create a digital facial signature, comparing it via algorithms against a comprehensive private database, and finally determining if there is a match.
The technology will play a key role in Singapore’s national digital identity programmes, including facial biometrics-enabled log in for a variety of use cases (i.e. ID checks at airports and digital-signing capabilities in the legal sector).
SI Asia speaks to Fanglin Wang, Head of Artificial Intelligence at ADVANCE.AI, a leading big data and AI company in Asia on the challenges and potential of the technology.
SIA: What are the Pros and Cons of embracing AI and facial recognition?
Fanglin Wang: It’s important to recognise that facial recognition technology has already been part of daily life for almost a decade. It’s widely used in the algorithms in our smartphone cameras when taking selfies to identify faces in the shot, or automatically group and tag photos. Social networks are arguably considered the world’s largest facial recognition databases today when you consider the amount of selfies and photos uploaded to these platforms everyday.
Of course, mobile banking applications use facial identification to verify customer log-ins, and you also see this technology in use at airports and border checkpoints.
As with any technology, there are pros and cons. Based on where facial recognition technology is today, some of the pros include it being fast, convenient, and contactless. It removes the need to remember passwords or other digital tokens. It is very hard to falsify or defraud, and it is more accurate than human eyes. Good facial recognition technology and algorithms can be more than 99 per cent accurate, while human verification is less than 98%. Best of all, it can run 24/7 day and night, and in a place like Singapore where human resources and process optimisation are really critical, this technology can really be a game-changer.
Naturally, there are some cons. For example, collected data must always be kept safe and secure with a trusted guardian and safekeeper. Data must only be used for specific and stringent purposes, such as for law enforcement.
A balance must be maintained between convenience and data privacy and security.
It’s important for governments and the private sector to provide consumer education and comfort when it is initially introduced (i.e. at Changi Airport in Singapore). Finally, facial recognition technology must be able to prove a very high degree of accuracy before it’s deployed widely to prevent misidentification, and extensive testing must be conducted to understand its limitations before the technology is deployed.
How accurate is facial recognition today and what are some of the ethical considerations behind its use?
I’ve already touched on how facial recognition can be more than 99 per cent accurate. As to the conditions that impact accuracy, these include things like skin tone and facial structures between various races and nationalities, which can be very different.
For example, Indonesians look a bit different to Vietnamese, who in turn vary from Singaporeans. As such, your data has to be trained by relevant local sources. At ADVANCE.AI, we train our algorithms on private data sets. Public data is acquired via publicly-available sources such as universities and third-party studies.
Private data, meanwhile, is real customer data obtained via consent and compliance with local data laws in each market.
Turning to ethics, privacy, and security, this is a very important issue. Even as Singapore pushes ahead with its Smart Nation agenda, it is also one of the leaders in promoting right and ethical use of AI. The Singapore government proposed updates to its AI Governance Framework at Davos 2020 in January.
Broadly speaking, this requires that human involvement must be paired with AI technology to ensure accountable decision making. Moreover, AI decision-making must always be explainable, transparent, and fair. Finally, it’s up to governments to lead the way on encouraging discussion and ethical use cases of AI by private companies.
To illustrate how this works in practice, an AI system can flag high-risk or fraudulent bank transactions, but the bank’s human supervisors will need to review these decisions.
In healthcare, AI may be used to identify medical conditions, but human doctors will still make the final decision on diagnosis and treatment.
Changi Airport Terminal 4 in Singapore is a good example of what’s possible today with facial recognition. At the terminal, the technology has fully automated bag drops, immigration clearance, and boarding. Sixteen million passengers a year have their identities checked at the airport with facial recognition technology, and human officers can be retrained and redeployed for higher-value tasks. Overall, this has delivered a faster and better customer experience at the airport.
What are some of the industries and use cases for facial recognition technology?
Facial recognition technology, as a subset of AI, is being broadly adopted across sectors such as banking and financial services, fintech, retail and e-commerce. It’s being used for eKYC, anti fraud, and credit scoring. Generally speaking, AI, of which facial recognition is a key part, can really help in three major areas: automating process, gaining customer and competitive insight through data, and improving customer and employee engagement/experience.
Some real-life examples in the banking and financial services sectors include front- office capabilities such as quickening customer identification and authentication, while chatbots and voice assistance can help triage queries and provide personalised recommendations.
In the middle-office, facial recognition and AI technology can be used to quickly improve KYC, compliance, anti-fraud, and documentation checks.
In the back-office, AI can be used to analyse relevant customer and business data to help assess and underwrite credit and loan risk. The overall result is a vastly quicker, simpler, and more secure customer digital experience.
Another use case which is very relevant to the world today is when human interaction and contact is limited, such as during SARS when China saw a huge spike in demand for fresh fruit and vegetables on e-commerce platforms. The only way for merchants and suppliers to get onboard the e-commerce platform and rapidly scale to meet the demand without meeting face to face was through facial recognition digital onboarding and ID authentication.
So digital payment, customer and merchant authentication can all be streamlined with the use of anti-fraud AI technology, leveraging facial recognition, to simplify and expedite processes.
Broader use cases of facial recognition technology can also be applied to hospitality (i.e. hotel or theme park entry), F&B (personalised order history), supermarkets (payments and orders) and building or event entrance and crowd control, to name just a few examples.
How is ADVANCE.AI catering to this demand?
As a leading big data and AI company in Asia, our mission at ADVANCE.AI is to help enterprises solve digital transformation, fraud prevention, and process automation challenges through our flagship product Advance Guardian. Our product suite covers three areas, the first of which is AI solution.
This includes things like eKYC, intelligent process automation, and chatbots. The second area is our risk management solutions, which covers alternative credit scoring, and fraud detection and prevention. The third area is around digital lending solutions, which include digital onboarding, a smart decision engine, and smart collection systems.
What makes our enterprise solution, Guardian, unique is our technology and talent.
We have achieved 99% accuracy for our eKYC solutions, which leverage local data in each of the markets we operate (our current focuses are Singapore, Indonesia, and India). Our leading team of AI research scientists is key to this competitive advantage. We have ensured Guardian is a highly customer-centric offering, localised to the needs of each market including on-ground integration, customisation and support.
In Indonesia and Southeast Asia, we have over 400 corporate clients including Bank Mega and Danamart. In India, we have over 100 clients, including CASHe, one of the country’s leading digital lending companies. All this has resulted in Guardian being a fast-growing enterprise solution with 350 per cent year-on-year growth in API calls and 450 per cent growth of year-on-year revenue.