Ever fear that someone is peering over your shoulder when you’re withdrawing money? Now you can face the fear.
Security is paramount in a world where fraud and identity theft have become ever prevalent. Easing the paranoia is the National Australia Bank and Microsoft’s proof of concept Automatic Teller Machine (ATM). In a short period of about two months, the concept was developed a small team from the Bank’s in-house innovation lab, NAB Labs and technology division. The ATM uses cloud and artificial intelligence technology to provide customers both security and assurance.
Customer First Banking
The key goal of the project is to test the customer experience of using such technology.
All a customer needs to do is to scan their face and enter their PIN number into the machine. Facial recognition technology maps the customer’s face. Features such as the eyes, nose and moles are detected by the machine. This information is then stored on the cloud. Using Azure Cognitive Services, the cloud-based application can recognise and authenticate only the user. If a doppelganger exists, the PIN provides the second layer of authentication. Furthermore, should the machine capture another face peering into the machine, the technology bars the user from proceeding onto the next step of entering the PIN. Thus, bank cards are rendered obsolete in the cash withdrawal process.
Steve Day, National Australia Bank’s EGM Infrastructure, Cloud and Workplace, said, “If you think about the experience for the customer, that removes the requirement to have a card, you can use your face to enable the service. Still key in a PIN to make sure that you have the second factor. You know, with your face recognition and the PIN, that’s about as secure as you can ever get.”
The cloud platform does not store the images, only the biometric data. Even so, the data is securely stored on the technology giant’s trusted cloud platform and will be erased following the experiment’s conclusion.
Patrick Wright, National Australia Bank’s Chief Technology and Operations Officer said, “Cloud technology allows us to take advantage of features and capabilities that are world-leading and enable us to deliver at pace for our customers.”
Since data and artificial intelligence are key drivers for business efficiency changes in the financial sector as well as improving customer experience.
He said, “It just reinforced to me the need for banks to be simpler and faster for our customers; we want to deliver great connected customer experiences.”
Cloud for Banking
The proof of concept was showcased at Sibos 2018 in Sydney, Australia. A key theme at the conference this year is how data, artificial intelligence and robotics are driving service innovation and business model renewal for financial service firms worldwide. Synergy in partnership and the technology boasted by the ATM is a good example of this.
Steven Worrall, Managing Director of Microsoft Australia, said, “Cloud computing and artificial intelligence present the opportunity for a new generation of secure, streamlined financial services to be developed and rapidly deployed at scale. NAB’s innovation focus is concentrated on meeting the changing needs of the customer; this concept ATM that NAB and Microsoft are working on together provides an important glimpse into the future.”
He added, “For a consumer facing application such as the AI-powered ATM we’ve developed with NAB, this sort of continuous AI innovation is important.”
National Australia Bank has embarked on two other cloud-based initiatives. It was the first major Australian bank to transfer over key workloads to its partner’s latest Azure Central region. This is specifically designed to handle national critical computing.
Moreover, in a bid to train its workforce, the National Australia Bank continues to partner the technology giant in its Cloud Guild development program. This ensures the Bank has the internal skills for cloud success. Employees are trained in cloud computing skills. Since its launch in April this year, more than 3000 of the Bank’s employees have been trained.