5 technologies disrupting the payments landscape

For generations, high barriers of entry and a limited capacity for innovation safeguarded the cosy position of incumbent payments providers. Yet over the course of the past decade, an invasion of fintech start-ups have totally revolutionised the sector. New entrants have brought an unprecedented range of choice to consumer markets, and that choice inherently stems from the mass deployment of new technologies.

While that technology has varied dramatically in recent years, this year five tech trends are redefining payments.

Social payments

Chatbots have been around since the 1960s, and have since earned recognition as fairly useless distraction on social media networks. But in recent months, tech companies and payments providers have started to challenge that perception by redeploying chatbots as a real-time payment processing tool.

In June, social media leviathan Facebook filed for a patent detailing its development of a bespoke AI messenger bot capable of processing in-app transactions between a user and merchant via a series of short, conversational messages. Meanwhile, Mastercard announced earlier this year it would soon be piloting its new Masterpass QR chatbot to help African merchants move beyond cash to accept QR payments via Facebook Messenger.


Developers have gained a lot of ground in the field of biometrics, and companies across a variety of sectors are already deploying it as a means of authentication. Juniper Research is forecasting around 770m biometric authentication apps by 2019 – and the mass movement has already penetrated the payments sector via fingerprint-based processing tools like Apple Pay.

In California, POS provider NEC has even teamed up with local restaurant chain CaliBurger to take biometrics one step further by enabling face-based payments. Via the burger restaurant’s self-ordering kiosks, customers can now pay for their meals by smiling at a screen and typing in their card’s three-digit CVV number – although in the long-term CaliBurger is hoping to eliminate the CVV numbers to authenticate payments by smile alone.


Distributed ledger technology might have hit the mainstream almost a decade ago, but developers are only just now beginning to forge the most dynamic practical applications in terms of payments.

Over the course of 2018, payments providers have been engaged in a proverbial patent war over new blockchain developments, ranging from a new type of crypto account from Mastercard to the launch of rival Visa’s new enterprise blockchain infrastructure Visa B2B Connect, which began testing earlier this year. Yet with 406 blockchain patents recorded by the World Intellectual Property Organization in 2017, there are undeniably plenty of blockchain-powered products and services on the horizon for 2019 and beyond.


There’s nothing new about retail financing and purchasing goods through multiple instalments – but US-based start-up QuadPay has streamlined the concept and totally disrupted ecommerce through its easily integrated payment platform. Powered by Stripe, QuadPay offers customers the opportunity to split the purchase amount of their cart into four interest-free payments that are spread over six weeks. If the customer repays on time, they don’t pay a fee – and merchants are only liable for a nominal processing fee.

QuadPay isn’t alone. Competitors like Splitit have recently launched with similar pay-by-instalment web API solutions and virtual POS apps to clear pay-by-instalment transactions in-store as well as online.

Machine learning

The payment implications of AI extends far beyond social media chatbots. AI and machine learning have now given birth to a range of predictive analytics functions that are enabling payments providers to mine larger quantities of data than ever before with a view to better understand consumer spending, and optimise and customise personal interactions in real-time to create a smoother payment journey.

Demand for optimisation and smarter payment analytics has led to the creation of a range of new payment gateways like aiGateway, which utilises machine learning to slash fraudulent transactions through its real-time, omnichannel payment monitoring system. Meanwhile, incumbents like American Express are drastically and very publicly expanding their machine learning departments in order to drive product optimisation and rollout bespoke services.

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