Artificial Intelligence use in payment solutions

16 August 2017

One of most heavily discussed technological developments over the past few years has been a rapid advancement of artificial intelligence (AI). AI is defined as systems and processes that gather and perceive input or information from their environment, understand what it means and act accordingly. Advanced systems also have the ability to learn by themselves.

AI is already making an impact in payments industry and capturing the attention of companies everywhere. For instance, numerous leading technology corporations, including Apple, Tesla, Facebook and Google are already investing actively in AI systems. However, its use extends beyond these technological leaders. AI is starting to play a role in driving real value for a broader range of firms, including those in financial services.

financial services

AI covers far more than just one technology, it grasps a spectrum of technologies that work together in payment solutions. These include facial, speech, and gesture recognition systems, as well as language processing, robotics, and machine learning. In essence, these combined technologies comprise a system that has the ability to perceive and collect data, analyze it, and use that analysis to support independent, informed decisions. This makes companies smarter and leaner, and enables them to react and adapt faster in the face of constant and pervasive change.

Say it, if you want to pay it

Amazon’s new product “Alexa” is based on a built-in voice recognition feature, as a part of natural language processing. Not only can it help you deal with mundane tasks, like scheduling your timetable or reporting the weather forecast, but this genuinely smart device can also make Amazon online payments by executing your spoken commands. Voice recognition for payments is already applied by Venmo, and Apple is on the way to teach Siri special payment words to process peer-to-peer payments in the nearest future.

Light, camera…payment!

The function of vision recognition found its way through to the payment industry, too – to support facial identification to make a purchase. Last year MasterCard introduced “selfie” payments. First, a user needs to download the MasterCard app and make a photo to verify their identity. Then it is as easy as shelling peas: at the checkout, put your selfie camera on and blink – your payment is done. This feature functions by matching your identity photo, which is saved in the app with the face appearing on camera. Easy and, what is more, fun. Samsung is in the development stage to offer its users face recognition mobile payments as well – in a good 365 days though.

Share the pizza, share the bill via…messengers

Sharing a meal with friends is always a good thing. Still, figuring out who needs to pay, what and how much can cause a headache. Now, even this routine has been automated and simplified, even if you forget your credit card or do not have any cash on you. Now users can make peer-to-peer payments via Facebook Messenger or Slack. However, group payments via messenger are only available in the US and only support Visa and MasterCard yet. The system works due to AI bots and a collaboration of digital payment wallets with other online services like messengers.

Share the pizza

The best way to fight the enemy is to know its weaknesses

Machine learning is perfectly applicable for fraud detection – PayPal has the proof. They have developed programs, which analyze and compare thousands and thousands of transaction flows. They help to indicate, if the payment was “friendly” or fraudulent. This way, PayPal has reduced their fraud rate to 0.32 % from the whole revenue, compared to the average rate of 1.32%.

The possibilities of AI application in online payment are infinite. Some of them have already been discovered and used successfully, but the rest are yet to come. Beyond the specific examples mentioned, there is a growing segment of the industry focused on offer optimization. There is also early thinking being done on the use of machine learning to dynamically determine the optimal routing path for transaction authorization. Let us stay excited and see how the coming years of AI development may surprise us.

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