Angelo Gajo | June 26, 2019 | 7 minutes
Today, countless consumers use their smartphones to conduct transactions, whether it be mobile shopping or mobile banking. To provide a secure and convenient m-commerce user experience, many organisations have implemented biometric technologies. They have done this by utilising the biometric capabilities of smartphones, such as face, iris, fingerprint and voice biometrics.
There is no doubt that e-commerce is an integral part of any businesses as the world becomes a more digital place. With the need for digital mobility as well, the trend for m-commerce is growing. M-commerce is e-commerce done on a handheld mobile device such as a smartphone. This means any commercial transactions that can be done over the smartphone is considered m-commerce. Some examples of m-commerce are mobile shopping, mobile banking and mobile payments.
“Mobile commerce is a natural progression of e-commerce.”
– Nabeena Mali, Head of Marketing, AppInstitute
With smartphone manufacturers like Apple and Samsung innovating powerful, high-quality devices year-on-year, the performances far surpass the common digital needs of an average user. Smartphone users can do things such as sending e-mails, browsing the web, watching videos, taking photos and using the millions of apps on the app store. Smartphones also feature biometric security technologies such as fingerprint and voice biometrics. Interestingly, all these things play a part in making m-commerce work.
To understand the scale of m-commerce, here are some quick statistics:
As m-commerce continues to be globally adopted, critical importance is placed on providing a secure and convenience m-commerce user experience.
Biometric security such as Auraya’s voice biometric engine, ArmorVox, can greatly improve the convenience and security of m-commerce. In fact, biometric technologies such as face, iris, fingerprint and voice biometrics are already widely used in mobile applications today to identify and verify users. Telstra Retail currently uses ArmorVox for in-store credit check authorisations, allowing quick and delightful verification and authorisation services. Meanwhile, the Bank of New Zealand uses ArmorVox to identify and verify banking customers by only stating their identification numbers, providing convenient and secure user experience. Furthermore, Apple Pay and Samsung Pay use fingerprint biometrics to verify and authorise transactions digitally using a smartphone without the physical need of a credit or debit card.
In PaySafe’s white paper titled ‘Lost in Transaction: The end of risk?’, research shows that:
These statistics show that although biometric technology has proven to be more secure and convenient when compared to traditional methods, there is still a stigma surrounding it. The best way to address these concerns is to ensure proper biometric security implementation via multi-factor authentications. By utilising at least two factors, biometric security can be properly implemented with minimal risks and concerns.
Further, these biometric technologies can be tweaked to provide superior security and accuracy, whilst being able to detect imposters. For example, ArmorVox can be tweaked to achieve a false reject rate of less than 0.01% when the selected false accept rate is 1 in 10,000*. ArmorVox can also reduce its error rate by over 90% with patented features such as active learning, tuned UBM, speaker-specific thresholds and speaker-specific background models. Bear in mind that the initial error rate would already be minuscule.
In conclusion, m-commerce and biometric technology truly go together. With improved convenience and security, consumers can engage in m-commerce seamlessly. With the rate of innovation in smartphones and other smart devices and the constant developments and improvements in biometric technology, only time will tell when it completely replaces knowledge-based passwords.
* (results based on independent tests using the NIST standard of a non-conformant attack against a voice print created using 3 enrolment utterance of a unique number with 3 active learning cycles and 2 verification attempts on the same channel).