From education to business to healthcare, the opportunities that artificial intelligence presents are limitless — at least according to proponents of the technology.
But what about the specifics of AI’s actual applications?
“I think the impact on payments is pretty 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 in addition to helping ramp up 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 in part why 2024 is increasingly being seen as a crucial period for implementing generative AI strategies and reaping the benefits they offer.
However, there are challenges to overcome, including gaining customer trust and ensuring compliance with regulations.
GenAI is also set to revolutionize payment processes by making them more automated and efficient, Sarkissian noted.
“Whether it’s giving suggested routing for payment messaging and things like that, you’ll start to see a lot of those positive things come to the surface,” he said. “We’re already seeing a merging of the network of networks concept. … What can these networks that facilitate transactions do proactively to add AI to their layers?”
Tasks such as filling out 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 chances of errors, Sarkissian said. Additionally, the integration of AI into payments orchestration and routing can optimize processes, leading to cost savings and personalized recommendations for customers.
While discussing the potential of generative AI, Sarkissian highlighted the importance of learning from previous AI implementations. He noted that personal financial management tools and robo-advisers, which were part of the earlier AI wave, had mixed results and 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 simply adding a veneer of technology to existing solutions. Sarkissian emphasized the need for interactive AI tools that gather more data and provide personalized results to customers.
AI can be used to streamline processes like loan origination and underwriting, but regulations and fiduciary rules must be considered, 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.
Still, while certain tasks with 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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