Business guide to facial recognition: benefits, applications, and issues to consider

The meaning of the term ‘facial recognition’ is quite intuitive. The technology uses computer vision algorithms to map, analyze, and confirm the identity of a face in a photo or a video. Although every facial recognition solution (which often relies on proprietary algorithms) operates differently, we can distill the facial recognition process down to the following three steps:

Let’s take a look at the key facial recognition applications across different industries.

When incorporated into a hospital’s video surveillance system, facial recognition can simplify patient check-in, freeing hospital workers and patients from paperwork and preventing human error. By “looking” at a patient, a facial recognition system can verify their identity and insurance data, thus speeding up the admission process, laying the basis for a personalized experience, and preventing fraud.

Applications of facial recognition for patient tracking have high patient acceptance rates. Research published on Plos One states that almost 66% of patients find it acceptable for hospital systems to scan their faces for identity verification.

One example of such technology comes from ALCHERA, an AI-powered visual recognition firm. The company offers a facial recognition solution that helps hospitals streamline admission and discharge, identify unusual activities in patients, and control entry into the facilities while flagging unauthorized access.

Biometric technologies, including facial recognition, can also be used to verify the identities of surgical patients, identify patients who are unaccompanied by a medical worker, and track people entering and leaving the premises to prevent security threats.

Facial recognition can help diagnose rare genetic disorders, especially those with mild symptoms.

Delaware’s Nemours Children’s Hospital deployed this technology. As clinicians struggled to diagnose a patient experiencing unusual symptoms, they turned to Face2Gene, a face recognition-powered mobile app that Dr. Karen Gripp, one of the hospital’s employees, helped develop.

The application scans a patient’s photo, mapping their face with 130 landmarks, and uses machine learning to match the detected facial characteristics to those of rare genetic conditions. As a result, the application generates a list of potential diagnoses, each with a probability score. With Face2Gene, the doctors diagnosed that patient with a rare case of Wiedemann-Steiner syndrome.

Facial recognition helps track patients’ mental health patterns and behaviors. For example, the software can interpret the emotional state and improve the safety of patients prone to risky behaviors, such as removing a breathing tube.

People with special needs, too, can benefit from facial recognition. For example, researchers at Stanford University developed a facial recognition system that runs on Google Glass. It analyzes people’s facial expressions and prompts the wearer with respective cues, like ‘anxious’ or ‘happy.’ The research team claims their solution can help children with autism recognize facial expressions and improve the quality of their social interactions. The trials showed that children who relied on facial recognition software along with standard care showed improvement in socialization as opposed to the control group, who only received traditional care.

And just recently, Apple reported that its Vision Pro augmented reality headset can be potentially used to detect and alleviate mental distress. The headset includes cameras and sensors that can detect various facial expressions and emotions. For instance, the device can identify post-traumatic stress disorder, depression, and some other stress variations. Afterwards, the headset can soothe the user by showing images and playing calming sounds.

Contactless payment technology relies on machine learning algorithms to let customers pay for the goods by simply scanning their faces. Since goods are RFID-tagged and a customer’s faceprint corresponds to a specific payment method in a database, it is no longer necessary to manually scan the purchased items or communicate with a cashier.

The first nation’s facial recognition payment system was rolled out in Pasadena in 2020. And since then, different financial organizations have rallied to build and test biometric-based payment systems. J.P. Morgan is piloting a system that will enable customers to pay using a face or a palm scan without the need to show their card. And Mastercard is also experimenting with fingerprint scans and facial recognition models as a payment system.

Integrated into a store’s CCTV cameras, facial recognition technology can help retailers reward loyal customers without interrupting their buying experience. The moment a loyalty club member enters a store, the facial recognition system identifies the customer and rewards them with a personalized discount or informs them about deals or products they might be interested in.

Cali Group was one of the first US companies to roll out a facial recognition loyalty program. They equipped their restaurants with AI-powered self-service kiosks that identify registered customers and activate their loyalty accounts as soon as they approach the kiosk. The software powering the kiosk may prompt customers to order their favorite meals, and they can pay via facial recognition as well.

A similar approach is taken in this facial recognition application. For example, knowing how much time a particular customer spends in a store helps tailor future experiences to their preferences. And by analyzing their purchase history, retailers may nudge buyers with push notifications advertising products similar to those they have recently purchased.

Retailers can also set up digital signage with face recognition technology to alter product promotions on the fly based on the gender and age of the prospective customer.

Research shows that theft-induced financial losses in the US surpassed $112 billion in 2022, which is 19% up from the previous year.

Systems that prevent shoplifting are usually targeted at identifying repeat offenders whose photos are already stored in a database. A facial recognition system, thus, doesn’t attribute any personally identifiable information to the face of a shop visitor but searches for its equivalent in the database of known offenders.

The UK’s facial recognition retail security firm, Facewatch, provides a solution that operates on this basis. The company has access to the national facial recognition database. It scans every visitor and sends a notification if a suspicious person enters the facilities. The company claims their solution can reduce store theft by at least 35% during the first year of deployment.

Since the frequent shooting incidents, thousands of schools across the country have deployed facial recognition systems as preventive measures. Here’s how they can operate in a school setting.

A facial recognition system analyzes the faces of people entering or navigating the campus and compares them to a database of authorized individuals, including students, the school’s current staff, and parents, to establish their identity. If a person doesn’t exist in the database or matches the identity of an unwanted person, like an expelled student or a former employee, the system immediately alerts security and automatically denies the visitor entry into the campus area. Modern facial recognition solutions can have additional features, such as object detection, to identify gun-shaped objects.

While US universities are hesitant to deploy this technology, the Chinese educational system is willing to give it a try. Beijing Normal University mounted facial recognition equipment at the entrance to its student dorms. And several other universities and schools experimented with the technology in their classrooms.

Tracking attendance used to be a lengthy and tedious process that, despite a fair amount of time spent at the beginning of every class, leads to inevitable gaps and omissions when conducted manually. To fix that, educators are turning to AI-powered educational solutions. These facial recognition applications offer a faster and less disruptive way of tracking attendance.

One example of such a system comes from Australia. Victoria’s Department of Education resorted to facial recognition to monitor the whereabouts of students, letting teachers and staff access attendance data through a web dashboard or a mobile app. Another example comes from India, as Telangana’s government prepares a facial recognition-based attendance management system to be deployed in schools.

The core of the technology can be extended to enable more use cases, for instance, setting up automated book-lending library systems or managing other campus facilities.

Researchers report that analyzing students’ facial microexpressions, like raising eyebrows or tightening eyelids, may help highlight boredom, confusion, delight, frustration, surprise, and other emotions. This can be useful for professors and curriculum designers. For example, when conducting a lecture, a professor may evaluate the emotional state of the attendees and determine the parts of the lecture that spark or weaken interest.

As insights about student engagement come in, faculty may adjust the curriculum to better reflect student preferences and provide a more tailored learning experience.

Different universities are experimenting with this technology. For instance, a professor teaching Computer Technology Information Systems at Guilford College, North California, is working with his team to build a facial recognition system that can tell when students are confused or bored.

With financial services going almost entirely digital, it’s only natural for customer verification procedures to follow. Building on eKYC—a digital version of the “know your customer” standard that governs the verification and authentication of a customer’s data—financial institutions can now shift the customer onboarding process entirely online. Especially with research showing that three out of four bank clients accept biometric authentication. While eKYC uses fingerprints as an authentication method, facial recognition may become a viable alternative.

To give a few examples, the Bank of America uses a facial recognition solution from Samsung to allow customers to log into their banking mobile app. And the Orissa High Court in India is pushing for deploying facial recognition technology on ATMs to identify people involved in illegal withdrawals.

Today, criminals routinely use skimming devices to hack into ATMs. Facial recognition could potentially replace plastic cards and PINs as a more secure option for preventing fraud.

Several banks have already started testing out facial recognition solutions. For example, National Australia Bank partnered with Microsoft to develop a system that allows the bank’s customers to scan their faces in order to access ATM services. The OCBC bank in Singapore allows customers to use ATMs through facial recognition. But there is a condition that the first transaction performed with the technology has to be a balance inquiry. And, since recently, Japan’s Seven Bank has been preparing to enable customers to withdraw and deposit cash through an ATM using face-based verification. This service is set to commence in March 2024. And by September, the bank is planning to expand facial recognition-based services to include opening new accounts.

Facial recognition technology can offer incredible benefits, but there are also challenges that you need to consider to succeed with implementation. Let’s explore.

The proponents of rolling out facial recognition in enterprise environments say the technology brings about many benefits. Here are the essential ones:

Although capable of driving tangible benefits, facial recognition is not flawless. Among the issues halting a wider adoption of the technology are the following:

If you consider rolling out an AI-based facial recognition solution, we strongly recommend committing to doing so ethically. Here are some aspects that you need to investigate before you start building your solution:

No matter what your line of business is, you are likely to discover exciting facial recognition applications that you can use in your sector. But even though the technology is maturing and getting more affordable, incomprehensive legislation still hinders its promising potential.

Amid public debate about the safety of facial recognition technology, businesses and tech vendors should prioritize building transparent and explainable solutions. As of now, the technology is not 100% accurate, and it can be fooled; a simple false mustache can trick some facial recognition systems, not to mention face spoofing and other more elaborate techniques. Depending on the implications of your facial recognition solution, you might want to add an extra verification layer, such as gait recognition or fingerprint scans.

Here at ITRex, we can analyze your business requirements and recommend an appropriate facial recognition model with a backup verification system, if needed. We are also experienced in explainable AI solutions and can implement a human-in-the-loop approach to assist with accuracy and transparency.