The mobile payments industry is rapidly changing. More consumers than ever are using smartphones to shop and pay, and artificial intelligence will continue to streamline this payments channel for both merchants and customers.
Mobile app popularity has been on the rise for the past several years. Roughly 72.9% of online purchases across the globe are made from mobile devices. This means up to 3 out of every 4 purchases are being made via mobile.
With the introduction of artificial intelligence (AI) into the payments sphere — and in the mobile payments industry in particular — the payments process is becoming more streamlined and intelligent. In the coming years, this technology will likely change today’s mobile payment apps as we know them.
Terms like “machine learning”, “predictive analytics”, and “natural language processing (NLP)” have been connected to the AI phenomenon and have infiltrated almost every industry. The payments space is no different. We’ll explore some of the ways AI technology has transformed the mobile payments industry and look ahead to what’s in store.
Consumers have grown accustomed to the convenience of shopping and paying when and where they want to. Smart merchants have catered to this preference by offering streamlined omnichannel payments. Thanks to machine learning and AI, this has brought payments into channels not necessarily built for commerce. For example, merchants like Starbucks allow customers to send gifts using iMessage by layering remote payment processing and gift card activation technologies. The mega coffee retailer has also implemented a voice-activated chatbot — My Starbucks Barista, that allows customers to place and pay for voice-activated orders.
The key is to balance customer experience with security, removing friction for the consumer while keeping sensitive card data protected. Artificial intelligence enables bots to converse naturally with consumers, helping them place and pay for orders, while machine learning technology can keep a tight hold on transaction data, alerting merchants to suspicious activity. In the future, we’ll likely continue to see the mobile payments industry converge with channels where consumers prefer to spend time.
Financial institutions have also taken a page from the conversational commerce book and have used AI-backed bot technology to facilitate money transfer requests through messaging apps. Back in 2017, Western Union rolled out a money transfer bot in the Philippines, which enabled users to request money from people working or living abroad in the U.S. The technology utilizes Facebook’s Messenger application, where requests can be sent via chatbot and fulfilled by the sender by clicking the message through the mobile app.
Using PayPal as a funding source for these peer-to-peer (P2P) payments, Western Union has taken accessibility and convenience to the next level for its patrons. The mobile payments industry will continue to utilize layered technologies to facilitate P2P payments and money transfers as a means of offering more personalized options to consumers.
Machine learning has been integral to keeping fraud at bay in a highly effective and efficient manner, a necessity for the mobile payments industry. While rules-based systems have long been the norm for merchants looking to squash fraud, machine learning steps in and carries the torch in a more sophisticated way. Machine learning significantly reduces the scope of error in fraud detection, processing large amounts of transactional data and applying nuanced and iteratively improving transaction filtering rules to spot true fraud. By identifying only high-risk transactions and applying an additional security layer, machine learning can improve the end-user experience with mobile payments without sacrificing security.
It’s a far cry from the manual process that has been in effect for ages, removing the resource burden from merchants and almost error-proofing the process. Since machine learning is able to adapt as fraud attacks become more sophisticated, it enables merchants to stay one step ahead of bad actors while keeping time and resource costs at bay. It also enables the processing of large amounts of transactional data, which can be monumental for larger merchants.
Machine learning also gives way to reduced false declines. This problem has been a thorn in merchants’ sides for years – and a costly thorn at that. In 2019, false declines cost merchants $20.3 billion in losses. Falsely declined non-fraudulent transactions are often more expensive than fraud losses for merchants.
While AI and machine learning technology have come a long way, their applications to the mobile payments industry are still nascent. We will continue to see improvements in both user experience and in deterring fraud for mobile payments in the near and long term. It’s a cyclical evolution: the more intelligent mobile transactions become, the more consumers will utilize this channel for payments.
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