How does ArtificiaI Intelligence affect the Payment Industry

The rise of artificial intelligence (AI) based technologies is without a doubt reaching our everyday lives. From chatbots to complex engineering design there is a vast amount of applications. But how can such technologies be used in the payment services sector? Are there already innovations in place? What’s the future all about? These questions will be covered with this article.

AI based software gains traction

For many years now AI is being used in the banking sector for fraud detection purposes in real-time. Nowadays it’s the only viable solution for payment transaction processing as there are an estimated 700 billion payment transactions in 2020 who can’t be handled by humans anymore. Apart from this mature use case the constant development of the technologies behind AI make it now possible for it to tackle other business areas like customer service or personalized products. The traction of this area is accelerated by growing VC investments into AI based startups. For example in the US from just shy of a billion dollars in 2012 to 17 billion in 2019.

Making use of data

The digital age led companies to amass data about their clients for nearly every aspect of life. “Big Data” – a relatively new business sector is now a treasure trove for companies to unveil secrets formerly hidden in plain sight. AI technologies play a leading role in this area because the quality of results is largely based on high computing power and pattern recognition.

In the finance field the usage of AI based chatbots becomes apparent as one of the first areas that AI adds value to. Many finance companies help customers with site navigation, answering questions and education, all without the need of human intervention. There are even approaches where the GUI can be controlled by inquiring a chatbot so that the bot acts upon the orders of the user, e.g. transferring money or generating account statements. A good example is the partnership of the Ingenico Group with IBM Watson for the development of an AI based chatbot to be used in the retail and hotel sectors. The bot is programmed with natural language processing capability which helps the communication with the user. It is more similar to a personal talk than an unpleasant input-output-process. The bot can ask questions and tailor the retailers’ or hotels’ offering directly to the needs of the customer. The conversion rate compared to traditional apps is five times better, which shows the suitability of AI in that regard.

Another sector is the personalization of the credit score. Until today the biggest challenge for credit bureaus is the avoidance of false-negatives in calculating a persons’ creditworthiness. The traditional approach with mapping of zip codes and creating customer buckets is too brittle and the industry longs for new ways of tackling this problem. AI can look at the data and create a personal offer on the fly that fits the customer best. Especially for unbanked or newly banked persons the introduction into the finance system works with fewer barriers that way. But there’s another side to the medal as well: Risk of regulators seeing the AI as a black box and being unable to communicate the reason for credit denial.

In the payment sector there is huge potential left when it comes to personal AI based assistance. Constantly monitoring the data helps to guide and educate the consumer. A software could analyze the spending habits, recognize reoccurring payments and give educated and personal advice on which services to discontinue or introducing a personal savings plan.

Based on data is a new form of payment that uses biological features such as fingerprint, voice or face. These being unique to every human could replace plastic cards and other bulky means of payment entirely. Today many popular finance apps offer the login or approval of a payment with a fingerprint. But face scans and voice recognition are still in their infancy. The enrichment of the old standard 3D Secure with AI technologies is also in the making. That way the checkout process disruption can be mitigated.

The good and the bad

Although the possible personalization levels with AI are very impressive and make for an easier life when it comes to commercial activities. But there are downsides to it as well. With an AI becoming more and more capable it can be characterized as a human force in itself. This lets ethical questions arise. May an AI decide on how someone get a loan? Furthermore, the vast amount of data collection poses questions of privacy.

Companies have to provide the user with a detailed explanation of what the AI does and why – it should be positioned as a guide, not a god.

PayRetailers collaborates with many partners to offer innovative payment solutions. Contact us to learn more about our product suite and how you can leverage our technology network.