Five Steps to Identifying the Right Biometric Identification System for Your Business

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Biometrics offers unprecedented security that can be deployed to protect your data and physical premises, but choosing the best system to invest in can be a difficult task.

According to a CIO Insight article, the cost of biometric security when protecting your physical premises, for example, averages between $ 2,500 and $ 10,000 per door.

With that in mind, it’s important to know what level of investment you need to make when looking at biometric security systems, and the first step in that process is to understand what those systems really are.

There are several basic types of biometric systems available, so choosing the right one requires knowledge of the basics. You don’t need to implement expensive security measures at the airport to replace the key card system that allows you to go through your building’s turnstile, for example.

Let’s take a quick look at each system and what they do.

ABIS – Automated Biometric Identification System

First on the list is ABIS, which stands for Automatic Biometric Information System. Historically, this type of database has been used by the police, so if you need to keep track of thousands of fingerprints or faces, this might work for you.

For example, Mexico has a regulation that forces banks to use biometrics to verify the identity of their clients in the context of the fight against money laundering.

ABIS is expensive, but if it’s something you need (when the law requires you to verify customer identities securely), it can be good for risk management. In the United States, companies that must adhere to anti-money laundering laws can use an ABIS system to minimize their liability.

One cool feature that ABIS incorporates is the way it uses biometrics to compare a selfie with your ID, then check your ID against a government database to make sure it isn’t. not stolen.

In the Philippines, you can get fake ID for around $ 50, and fake IDs are endemic, making identity verification unreliable. One of our clients in the Philippines works by giving out small consumer loans after collecting the fingerprints. The bank analyzes fingerprints to see if it can grant a loan to a customer based on their credit history. If they appear in the system in a form other than the name on their ID, the bank is able to eliminate the fraud. In fact, biometrics helped this customer reduce fraud by 90%.

On the other hand, banks can qualify people for larger mortgages if they know their information is very secure and linked to a biometric database. This makes consumer loans cheaper.

Remote integration

The next type of biometric system is remote integration. This can be used by any business that sells a service that requires customers to fill out a lot of forms. With digital integration, you can use your smartphone to take a photo of your face and ID to open a bank account, log into certain government websites, and possibly do things like pay utility bills.

These systems use OCR – Optical Character Recognition – which means you take a picture of your ID and the system reads all of the ID text. It then takes this data and forms for you when registering for an online service.

The biggest Slovak bank even uses it in branches to help you open an account in two minutes rather than half an hour. It’s so fast that now you come to the bank branch and sign up using an app on a tablet. “You can’t simplify the process,” said a bank representative.

Access control by facial recognition

This is a good solution if you are looking for physical security. When you enter a building, facial recognition and access control software, implemented in your video surveillance system, assesses your face, your gait or your physical presence and compares them to a database. Based on your physically recognizable characteristics, such as the way you walk, associated with your appearance, the system will automatically open the turnstile for you or call an elevator to the floor you are working on. This can be used to only allow certain people to access floors they are allowed to access.

Facial recognition access control measures can also be linked to your office presence system, so you know when people have walked in to work, when they left work and when they had lunch.

In some countries this is particularly important. In Dubai, companies are having problems with many migrant workers who would share the same work permit. Facial recognition ensures that only the person authorized to enter can enter the building.

This type of system could be deployed at airports for biometric airport tickets. It will be connected to your biometric identifiers in order to allow you a personalized trip through the airport. All you would have to do is just look in the biometric kiosk and it will tell you your door number and where you need to go. The system will know if you are vaccinated and if you have received your passport and if you are who you say you are. In places where enhanced security systems are needed, this provides immense value by reducing wait times and bottlenecks.

Attendance analysis

This type of system is excellent for collecting large-scale data on visitors to sites. Attendance analytics can analyze CCTV data on an anonymized basis to estimate age and gender to determine the number of people in a large place (such as a shopping mall) and their demographics. Once this data is collected, the system automatically casts faces when the people it follows leave the place.

This allows event coordinators or large venue owners to track customer faces for the duration of their stay in the mall or at a festival. This can be used to bring together age / gender cohorts: for “Today there were 5,000 males and 7,000 females of age…” for example, and owners can tailor their offerings to that particular audience.

So, let’s say the owner of a shopping center needs to attract more than a certain group and he reviews applications for commercial real estate; they could lease a store that can attract that desired demographic.

Finally, every respectable biometric algorithm is ranked by the National Institute of Standards and Technology (NIST). Every major company in biometrics sends their algorithm to NIST, and every company that means anything in biometrics is there, ranked according to its accuracy. For example, the NIST facial recognition provider test (FRVT) can help you choose the best facial recognition provider.

When making your final decision, it is important to ask two questions:

1. How do you treat personal data? For example: is your data all stored on a single server? Or compartmentalized so that IDs and faces are kept separate? In addition, what are the compliance standards (ISO or others) to which you adhere?

2. Does the algorithm you are using correctly identify people? For example, does it contain racial prejudice? Can a potentially biased algorithm affect the reputation of my business?

The best biometrics companies offer secure storage of your data under your full control and can identify people of all racial backgrounds even when wearing a Covid-style face mask. Don’t let salespeople trick you into thinking it can’t be done. Again, NIST has made reliable measurements of both bias in facial algorithms and their ability to recognize masked people.

Whether you are looking for a risk management solution or an attendance system, biometrics can make them more reliable, more comfortable and more inclusive. Many companies are now realizing that biometrics, if used correctly and in accordance with personal data protection, can be a game-changer and should not be out of reach for everyone.


About the Author

Jan Lunter is CEO and CTO of Innovation. Graduated from Télécom ParisTech University in France. Co-founder and CEO of Innovatrics, which has been developing and delivering fingerprint recognition solutions since 2004. Jan is the author of the Fingerprint Analysis and Recognition Algorithm, which consistently ranks among the best in prestigious comparative tests (NIST PFT II, ​​NIST Minex). In recent years he has also been involved in image processing and the use of neural networks for facial recognition.


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