Customers of the Costcutter store at Brunel University in London don’t need cash or a credit card to pay for purchases. No PIN number or password to remember. They can now pay with a quick scan of the unique vein pattern in their fingertip. Their biometric data is linked to their bank card for payment.
In the store, a small scanner uses infrared light to read the shopper’s finger vein pattern. When you put a finger in the scanner, it checks for a pulse, and for the presence of hemoglobin (a protein molecule in red blood cells). This is a secure method of biometric authentication. To date there have been no reports of this type of biometric security being hacked.
The retailer does not keep the biometric data. The data is stored in an encrypted form, as binary numbers, by the financial institution – here Worldpay UK. This is similar to the way personal and credit card information can be saved by a financial institution for an online retailer to provide shoppers a convenient payment method.
Students appreciate the convenience of being able to shop on the go without carrying a wallet or handbag. The store expects to have 3,000 of 13,000 students signed up by November. Sthaler, the finger pay technology company, hopes to bring the technology to more retail stores, as well as nightclubs, gyms, football clubs and more. Vein pay technology is already being used in some countries – Poland, Turkey and Japan – for cash withdrawal at ATMs.
British supermarket offers 'finger vein' payment in worldwide first
By Katie Morley, The Telegraph UK, September 20,2017
Over 120 million consumers used biometric authentication for mobile banking in 2015, according to a report from Goode Intelligence. That number is expected to reach over a billion by the year 2020. The huge growth of biometric security is not surprising when considering the many benefits to consumers and banks.
For consumers, passwords are hard to remember and easy to steal. One way passwords are stolen is through phishing emails, purporting to be from your bank, asking you to change your password. If you enter your username and password, and some credentials, you’ve just given a fraudster a means of entering your account. Using biometric security as a second means of authentication to access your account would help protect you against this fraud.
It's good to know there are protections in place for your biometric data:
- Biometric data doesn’t have to be centrally stored. If you use a fingerprint or facial scan to log into a bank account, the image itself resides on your device. It is not stored on a server at your bank.
- Biometrics are generally used as a second layer of ID. Your authenticated smart phone or computer is the first layer. A thief would need to steal and establish control over your mobile device to access your account.
- Liveness detection helps prevent spoofing. Liveness detection assures that the fingerprint or face being scanned is from an actual person, not a photo, video or model.
Given the ease of using biometric authentication versus the difficulty of remembering and constantly changing passwords, biometric security is gaining acceptance among consumers. Biometric security also helps protect banks from billions of dollars of losses due to fraud. It’s becoming standard for mobile banking.
Banks may only allow their customers to use mobile banking for low value transactions such as purchases or online bill paying. Loans and other services, for example adding a new beneficiary, may require more security precautions.
Mobile Biometric Security in Digital Banking
By Aware, Inc., July 25, 2017
Over 1.1 Billion Users of Mobile Biometrics for Financial Services by 2020
Goode Intelligence research report, December 4, 2015
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| Image Credit: PNAS |
Researchers from Human Longevity, Inc., have used machine learning to link DNA genome data to facial and physical traits and are now able to use facial modeling and other physical trait predictions to identity people.
In a study with over 1,000 ethnically diverse participants ranging in age from 18 to 82, researchers were able to correctly identify about 80% of ethnically mixed participants and 50% of African American or European participants.
DNA genome information is used to create a facial image predicting face shape and features, including eye and skin color. It also is used predict sex, age, height and weight. Eye color, skin color and sex were predicted with the greatest accuracy.
Researchers would like to expand their study to hundreds of thousands of participants to refine their algorithms, but are also highlighting the need for better safeguards of participants’ privacy. While most would probably agree that using new facial imaging technology to create realistic mugshots of criminals is a good thing, privacy issues and possible future uses need consideration.
If your DNA can predict your personality traits, could this information potentially be tapped into by possible employers? If your possible health problems can be predicted, would health insurance companies have access to this information and be able to use it against you? The research team advocates, “more public deliberation is needed as more and more genomes are generated and placed in public databases.”
Researchers from Human Longevity, Inc. Use Whole Genome Sequence Data and Machine Learning to Identify Individuals Through Face and Other Physical Trait Prediction
Human Longevity, Inc. Press Release, Sept. 5, 2017
Identification of individuals by trait prediction using whole-genome sequencing data
Authors Info
Article published on pnas.org, June 28, 2017
