How AI is Changing Payment Technology in 2020
Alongside the healthcare and transport industries, the world of finance is at the forefront of pioneering use cases for AI. And if there’s one thing these three major industries have in common, it’s an abundance of data.
In recent years, digitised payment technologies have paved the way for an enormous amount of payments and transaction data to be produced – data which machine learning analysis models can use to produce accurate financial predictions. This is how payment platform FlexPay predicts and prevents credit cards from being declined. It’s also how Algoriz allows their customers with limited technical knowledge to create viable trading algorithms.
For shipping, retail, and ecommerce giant Amazon, AI-enabled payment data analysis has resulted in better inventory management, personalised product recommendations, and an overall enhancement of both existing products and internal logistics.
In fact, according to the Retail Insider’s Digital Retail Innovations Report 2019, Amazon is the biggest player in the AI-dominated retail landscape. Meanwhile, an estimated 37% of retailers have implemented AI technology alongside Amazon. By using AI to predict changes in product demand and other sales trends, these retailers have cemented their place at the forefront of harvesting the new gold: business data.
In short, the impact of AI on payment technology rests on the very data that these new technologies produce. According to FIS Global, digitised payments are becoming more and more common for companies in SaaS, education, video games, digital marketplaces, money transfer services, and even crypto exchanges. For every company that adopts digitised payment platforms, a unique set of data is created. And the more unique payment data sets emerge, the more AI analytics-enabled companies like FlexPay, Argoriz, FIS Global, and Amazon can improve user experiences with payment technologies across a variety of industries and services.
In other words, the growth of AI and payment technology reinforces one another. Apart from significantly improving payment ecosystems, AI can also help businesses that rely on new payment platforms to fight an age-old enemy in finance in the form of fraud. In fact, finance giant Visa reports an estimated 80% decline in card-based fraud ever since the rollout of smart payment cards under the EMV standard. Originally standing for “Europay, Mastercard, and Visa,” the EMV chip card is one of the finance industry’s latest successful attempts at standardising higher technical requirements for secure electronic payments. The consolidated data from EMV transactions is then fed into machine learning algorithms designed to identify fraudulent activities. In essence, the more customers transact with businesses through EMV cards, the more businesses and government regulators can protect them from illegitimate transactions.
Much like every major technology or industry on the planet, payment technology has embraced the AI revolution. This has been particularly true in 2020. As new physical distancing requirements have made contactless payment methods more essential to people’s lives, payment technology is rapidly advancing. Every day, more and more unique and relevant business data is being churned out by the increasingly digitised global payment ecosystem.
In turn, this presents more opportunities for machine learning algorithms to further improve the efficiency and security of new payment platforms. And if these patterns of development continue, AI and payment technology will continue to further contribute to each other’s rapid growth – well beyond 2020.