Jason Simon explains how artificial intelligence is improving digital payments

According to several reports, by the end of 2018, the artificial intelligence market had already surpassed $1.2 billion. A not-insignificant amount, which shows the wide projection that this type of tool has among different industries. The use of AI mechanisms or some of its branches in particular, such as machine learning or deep learning, is becoming popular in very diverse areas of activity, and with varied applications. Jason Simon, an expert in online payment solutions and eCommerce, explains how artificial intelligence (AI) can have a major impact on digital payments today.

According to Business Insider Intelligence’s report, AI in Banking and Payments, AI has four major areas of use in payments: in reducing fraudulent payments and false positives, anti-money laundering, and in its use in conversational platforms. The study indicates that of these, the uses that have the greatest potential to achieve good returns within five years are in fraud prevention and detection, avoiding fraudulent payments, and unauthorized transactions. The use of conversational platforms to make payments is at a lesser stage of maturity. “One of the sectors in which artificial intelligence has a big presence is in finance, where it impacts both the back-office and customer service side of the business. Among the uses for it is its application for payments,” Simon explains.

Visa, for example, is one of the large companies already employing AI technology in its financial practices. Some time ago, it announced the launch of the first implementation in Latin America and the Caribbean of Visa Smarter Stand-in Processing (Smarter STIP), a new real-time AI service to help issuers manage transaction authorizations while their services are down. The first issuer to deploy this innovative solution is Banrisul in Brazil, with several more to follow in other parts of the region.

Smarter STIP uses deep learning to analyze past transactions and make informed decisions regarding the approval or rejection of transactions on behalf of issuers when their systems are down. Simon says, “Visa is one of the first companies in the world to use Artificial Intelligence and neural networks to prevent fraud. Smarter STIP is the first in a series of innovations based on these technologies that will be made available through VisaNet, Visa’s global processing network.”

By incorporating this intelligence, Visa can intervene on behalf of issuers while their systems are down or offline and make transaction decisions that more closely reflect the issuers’ decision process, significantly reducing the number of declined transactions. The solution was quickly implemented in Brazil, as Smarter STIP does not require issuers participating in the service to make any technical modifications. Banrisul is already relying on Smarter STIP to support customers and ensure an excellent payment experience should their system experience any problems.

Mastercard is no slouch, either. The company is currently using machine learning to secure payments and detect possible misuse. Specifically, the tool uses algorithms to give a predictive score to the issuer, according to intelligent analysis, data that it then incorporates into its anti-fraud solutions. In this way, it generates a broad base from which to establish purchasing habits and then adapts to each case to be able to decide in real-time whether a transaction is suspicious or not. According to Ajay Bhalla, president of Corporate Risk and Security at Mastercard, the implementation of AI in its network helps financial institutions and merchants to “increase acceptance rates and improve the consumer experience.”

One example of the use of AI in conversational platforms is Amazon, which uses AI in payments through its Alexa voice assistant. According to Simon, the eCommerce giant seeks to “create a more ‘naturalistic’ payments path based on conversation.” That is, streamlining and simplifying payments for the customer: another example of artificial intelligence aimed not so much at security, but at user convenience. In any case, an example of how this tool is gaining ground in the payments sector. “These technologies are already here and in widespread commercial use. The AI revolution seems to be well underway. Its progress is now simply a matter of iterative improvement on existing models,” adds Simon.

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