Artificial intelligence (AI) is already in use within the payment industry, primarily in the form of Machine Learning (ML), which is most commonly used to combat fraud. However, the usage of AI is increasing rapidly, especially creative uses of generative AI, which refers to the creative extrapolation and the creation of new ideas. Here are some specific use cases that will become much more common across payments in 2024.
Use of generative AI and ML in combating payment fraud
ML has been used for some time in combating payment fraud, particularly in evaluating transactions and flagging behaviors that are associated with fraud. Suspicious cases can be rejected or passed on for further scrutiny by humans and other systems.
The initial use of ML was to create static rule-based systems that were generated for fraud detection. Next, the use of machine learning was expanded to collaboratively enhance the static models of fraud detection by continuously leveraging live data, with the latest models adding generative AI.
Generative AI is being tested and used to create new patterns to train ML systems so that they can get stronger and more robust quickly without the risk of real fraud. Generative AI can mimic the kinds of behaviors fraudsters might commit, and in addition, the criticism of generative AI for making up information or “hallucinating” is actually an advantage because it can come up with new patterns for training that can only make systems stronger.
Another area where generative AI is employed is to combat fraudulent uses of generative AI itself—especially in fraudulent identity creation. In fact, this is one of the fastest-growing forms of fraud, comprising more than 85% of identity fraud cases. “Synthetic identity fraud” is powered by generative AI, making it challenging to detect using traditional methods. Interestingly, generative AI is very useful in detecting the fingerprints of generative AI in fraudulent identities. Many companies already specialize in detecting and combating fraudulent usage of generative AI.
Use of generative AI in streamlining payment approval processes
Onboarding is the process of setting up a merchant to accept online payments. One of the slowest points of onboarding for any payment provider is gathering business information and creating the many forms needed for completing underwriting, filing regulatory documents, assessing processing fees, and more. For new merchants, this is a time-consuming and difficult process where they lack expertise.
Companies are beginning to experiment with generative AI to speed up the process of completing these documents. One approach is to engage in custom, interactive interviews and allow AI to generate much of the needed documentation automatically. This limits human input rather than manually entering repetitive information.
In addition, much of the onboarding process consists of providing the customer with a great deal of legal information that must be acknowledged and accepted for regulatory and legal requirements to be met. This information must also be generated individually for each customer and must be explained carefully. Generative AI is useful both for completing these documents and for providing easy-to-read summaries that can speed up the acceptance process. More advanced usage can even include AI-created interactive chatbots that can explain the process as it happens.
Use of generative AI in streamlining customer checkout experience
ML and generative AI will be utilized more widely across the payment experience, including the customer experience. One prominent example is AI-driven chatbots in customer service. This use case extends to active shopping, where generative AI can intelligently offer additional products and services to complement items a customer is actively purchasing. Additionally, chatbots can help answer common customer questions.
As more businesses turn to a single SaaS solution to run day-to-day operations like appointment scheduling, accounting, and payments, the concept of embedded payments has emerged. Embedded payments are built into the software application, creating more natural payment flows that are consistent with the existing user interface—as opposed to third-party branded payment forms and redirects. In an article on how generative AI can help improve embedded payments, Tom Randklev, Global Head of Product at Cellpoint Digital, said that AI can improve upon embedded payments and continue to streamline checkout experiences: “Consumer convenience plays to the very front of this one, where embedded payments have already made the experience incredibly smooth—it’s a one- or two-click experience to get from product selection to a payment, and I think generative AI will continue to accelerate that,” Randklev said.
Use of generative AI to predict consumer behavior
Generative AI, in combination with ML, is also going to lead to increased personalization of services by analyzing consumer behavior to predict future purchase decisions and how much they are likely to spend. It will streamline the experience by continuing to offer purchasers exactly what they want at the right time, even down to payment method choice. This can help businesses tailor their offerings to meet the needs of individual customers, increase customer loyalty, and drive revenue growth. Examples of this could include personalized loyalty programs, interactive chatbots to help in the purchase of high-end and complex products and services, and offering more complete and descriptive product information to help in decision-making at the point of sale.
A survey by Edgar, Dunn and Company of over 100 payments professionals found that fraud detection and improving customer service were the leading expected use cases for AI in the payments industry.
Looking to the future
At its core, AI provides speed, increased efficiency, data insights, and cost savings that will benefit businesses and consumers alike. In 2024, the payments industry will use generative AI to help streamline payment processes, improve fraud detection, and enhance customer experiences. Since generative AI is inherently a creative field with many unknown use cases, undoubtedly, other opportunities will arise. Indeed, it is an exciting time to be in payments, witnessing the transformative potential AI holds for the industry.
About the Author
Zachary Jarvinen is the VP of Marketing at Exact Payments, a member of the Forbes Technology Council, and a published AI writer. During his 15+ years career, he has grown a data analytics startup to #87 on the Inc. 5000 list, helped expand global markets for Fortune 500 Epson, and led AI & Analytics product marketing at OpenText.
