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Context-awareness: The salvation against the BlackBerry syndrome


Context-awareness: The salvation against the BlackBerry syndrome

Yacine KESSACI

Senior AI Researcher

Not so long ago, those who are now considered to be the undisputed smartphone behemoths (Apple and Samsung respectively with 17% and 22% of the market 2021) were either not on the market or were insignificant competitors in the field of mobile phone manufacturing (0% for Apple and 2.8% for Samsung in 1998) .

I would like to begin by with a cautionary tale which illustrates through a story about a parallel industry (mobile phone manufacturing) how the next big disruption in payments will require that companies adapt or die.

With the arrival of the internet, more and more (mostly professional) users were no longer satisfied with simple calls, SMS or MMS. They found it necessary to stay connected to their work environment through email and other internet based channels from their phone.

The difficulty that quickly arose was the poor experience provided by mobile hardware for accessing services usually designed for desktop computers.

 

One player stood out at that time: BlackBerry.

Indeed, their emergence was partly due to their ability to overcome this hardware weakness while offering a new way of accessing information that was more suitable for the mobile, namely “server push” (being pro-actively offered information instead of having to look for it).

Thus, thanks to their breakthrough content compression technique, it was made possible for them to synchronize, in real time, emails and notifications over low speed mobile networks (GSM, GPRS, UMTS etc.) making the ease of sending an email similar to that of sending a text message.

However the low network speeds did not last forever, and new technological breakthroughs saw the emergence of faster mobile networks and new multi-touch screens, comparatively reducing the BlackBerry’s advantages.

While BlackBerry was ahead of the curve in anticipating the arrival of the internet in the mobile world by offering innovations that set them apart from the rest of the market, the benefits of their data compression and physical keyboard was gradually lost with this second technological transition.

By initiating this technological shift, Apple and Samsung have since been able to renew themselves in order to thrive. Each used a different strategy. For Apple, it was by total internal mastery of their phones, mixing software and hardware. For Samsung, it was by keeping its hardware know-how while allying itself with a software leader (Google) for the OS and application part (Android).

 

So what about payments?

In analogy with the mobile phone example, the payment industry is continuously evolving, and has already had its first digital disruptions many years ago.

The age of the manual terminals (“irons”), where the embossed numbers on the cards were effectively used to physically capture cards imprints, lays way behind us as payment providers have shifted to digital levers for more automated, scalable, efficient and digitally secure payment methods for both physical shopping and e-commerce.

Beyond that, while the world is shifting more and more to smartphone enabled payments, we are still using the traditional transaction paradigm, where a user triggers and confirms a payment consciously. While those smartphone applications aim to bring user centric trust and convenience, they mostly still use the foundations of user-driven transaction processing, dealing either with classical purchases (covering those that are human-triggered and not affected by real-time data, as well as automatic payments for subscription services) or tolls, triggered by a machine, but not affected by real-time data.

With the advent of a fully “as-a-service” society, a third way to perform transactions has gained interest as being both automatic and data-driven. Examples of such payments can be found in fridges that check and adjust the amount of food available, washing machines that monitor and manage detergent purchases, or even soon autonomous electric cars that can take the initiative to charge themselves.

Through virtual assistants, chatbots or autonomous services, we are heading to a new switch of paradigm taking us from an automated digitalisation to an autonomous digitalisation as detailed in the chapter about Context Aware Services in our recently published Navigating Digital Payments report.

As consequence, the payment will be performed by autonomous services. This will change the payment landscape, by creating new needs for additional functionality and re-enforcing the need for trust in this way of handling payments. As a consequence, the payment business model will change as some of the autonomous decisions behind the services won’t be accepted by the customer, leading to possible misunderstanding and disputes.

By leveraging AI and contextual information, Worldline is already working on this scenario to provide autonomous validation services that will guaranty the solvability,  the validity and the transparency of any payment made by an autonomous service in order to bring back trust to the different actors of this new ecosystem.

Today Fraud Risk Management (FRM) focusses on card and transaction parameters. Tomorrow, in addition to this information, the paying autonomous services will build their payment decisions based on the fusion of continuous multichannel information (including, amongst other things, the histories of conversations with their users, images, and sounds) all while respecting action rights. That will generate a higher complexity with a continuous drift of the FRM challenge. With context-aware AI, Worldline sees our role to help and accompany our customers in order to manage these new challenges by adjusting the transaction acceptance policy according to all these new parameters to reach the most accurate assessment of the underlying risks.

I think that building trust in this new autonomous payment ecosystem will be an exciting yet complex journey, which will include, in addition to explaining external payment decisions, full transparency about the AI-based autonomous decisions made by our validation services.

With the support of a research program and various working groups, Worldline, through the Labs and Scientific Community, is continuously working to remain at the cutting edge of transaction processing innovation, maximizing the use of contextual information to meet the above-mentioned challenges.

Interested to know more? Stay tuned and read the Context Aware Services chapter of our Navigating the Digital Payment report.