Transitioning GenAI in Payments from a Talking Point to a Featured Component

The opportunities presented by artificial intelligence are limitless, according to advocates of the technology, spanning from education to business to healthcare.

But what about the specific applications of AI?

“I think the impact on payments is quite significant,” AI-ID founder and CEO Shaunt Sarkissian told PYMNTS CEO Karen Webster during a discussion for the “What’s Next in Payments: Payments and Generative AI” series.

“There is the low-hanging fruit of fraud management and KYC [know your customer],” he explained. “You are already seeing people trying to address synthetic identity fraud … security is going to be a big theme.”

He added that as well as helping boost anti-fraud defenses and making payments more secure, generative AI will also have a positive impact by automating payment processes and enhancing customer service.

That’s why 2024 is increasingly being viewed as a critical period for implementing generative AI strategies and reaping the benefits they offer.

However, there are obstacles to address, including gaining customer trust and ensuring compliance with regulations.

Transforming Payments, Financial Services

GenAI is also poised to transform payment processes by making them more automated and efficient, noted Sarkissian.

“Whether it’s providing suggested routing for payment messaging and similar functions, you’ll start to see many of those positive aspects come to the forefront,” he said. “We’re already witnessing a convergence of the network of networks concept. … What proactive measures can these transaction-facilitating networks take to incorporate AI into their operations?”

Tasks such as completing wire transfer forms and suggesting routing for payment messaging can be expedited using AI. This automation will not only save time, but also reduce the likelihood of errors, Sarkissian said. Additionally, the integration of AI into payments orchestration and routing can optimize processes, resulting in cost savings and personalized recommendations for customers.

While discussing the potential of generative AI, Sarkissian emphasized the importance of learning from earlier AI implementations. He pointed out that personal financial management tools and robo-advisers, which were part of the earlier AI wave, had mixed results and only modest adoption in the marketplace.

“The value was not meeting the expectation of value,” Sarkissian said. “And cost is an issue in the absence of value.”

To ensure the success of generative AI, institutions must focus on delivering individualized value and avoid merely adding a superficial layer of technology to existing solutions. Sarkissian stressed the need for interactive AI tools that gather more data and provide personalized results to customers.

Implementing GenAI

AI can be employed to streamline processes such as loan origination and underwriting, but regulations and fiduciary rules must be taken into account, he said. When it comes to ensuring the accuracy and reliability of AI-generated financial advice, institutions may need to seek safe harbors and expand compliance measures.

The deployment of generative AI in payments and financial services faces various barriers. Institutions often approach new technologies cautiously, Sarkissian said, considering the potential risks involved. However, the integration of chatbots into banking and financial services has helped pave the way for more interactive AI tools.

However, while certain tasks related to payments and financial services can be automated, high-value interactions, such as onboarding large accounts, require a human touch.

“It’s important to consider the endpoint of the automated interaction, where the AI leaves off,” Sarkissian said.

Financial institutions must carefully consider how to integrate generative AI into their existing environments and ensure the quality of input data for effective decision making, Sarkissian said.

But the most important thing, when it comes to generative AI, is that firms use 2024 to get started.

“You can’t stand in front of the train of innovation,” Sarkissian said. “There’s a natural tendency, particularly amongst banks, to freeze, think, and then implement.”

“2024 is a year to move past the press release and start doing something with AI,” he added. “I would hope most banks and financial institutions spent a good deal of 2023 getting comfortable with the technology, doing vendor analysis, doing tool analysis to figure out what they’re going to implement.”

Sarkissian predicted that due to compliance requirements and the sensitive nature of the data financial institutions handle, many organizations will train models themselves to implement their own internal systems.

“You have to begin,” he said. “You have to start putting these tools out there.”

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