AI

Blog: AI’s Move From Hype To Hope

December 16, 2019 | CORTEZ ADAMS

When it comes to artificial intelligence (AI), for financial institutions the battle is one of hope vs. hype — and whether AI can really transform how financial services are delivered.

In an interview with PYMNTS, Cortez Adams, director of product management at Diebold Nixdorf, said financial services executives “really have hope” that AI will help improve their firms’ effectiveness in handling payments.

Thus far there has been a risk-scoring component in enabling AI, he said. And these same executives are interested in leveraging AI to help automate the decision making process, which he said is still marked by manual tasks.

Automating the risk-scoring has value, especially against the backdrop of high-value, high-risk transactions, and where payment activity spans several offerings across a financial institution (FI), from check payments to wire transfers and beyond, regardless of whether they involve individual consumers or B2B activity.

“It’s a pain point,” he told PYMNTS, and “institutions that Diebold Nixdorf speak to want to address this with AI. That’s the target.”  

Moving Beyond Decision Making
Beyond decision making, he said, executives want to use AI as they provide services to clients and conpsumers.

AI, he said, can help with onboarding of documentation related to Know Your Customer (KYC) mandates — but can also match consumers with relevant service and financial product offerings. That’s especially true as banking moves to what he termed a self-service channel, streamlined in nature.

It’s a channel where consumers choose what is right for them, complete applications and then, after all is said and done, there is still someone at the back end of the process (at the FI) to approve or deny the application. AI, he maintained, can bring the “best fit” to a financial institution’s customers based on data surrounding activities such as loan decision making done in an automated fashion, whether in a branch or digital setting.

“If we leverage AI at the beginning, to identify the user based, for example, on social behavior external data feeds or maybe existing behavior that they have interacted with that particular institution — you can leverage that in the decision right there at the beginning,” he said.

Diebold Nixdorf, he said, can offer “a hotbed of data that is probably extremely valuable in the right scenario. So now what you do with that data is obviously a huge discussion topic,” especially across the retail, fuel and convenience store verticals. Sharing information through multiple arenas across an institution can offer end-users services and products on an optimally tailored basis.

While there may not be a hard and fast roadmap for AI deployments just yet, Adams said, “You will find components of AI and analytics through multiple product areas across Diebold Nixdorf.”

But in fashioning the journey, he said, logical first steps involve looking at the collective data of the firm’s clients to get a baseline of behavior and determine how AI might be of use. Beyond that, he said, “We’re looking to provide actionable data around payment decision making for our clients.”

After that there comes a point “where AI becomes more prescriptive.” Some of those prescriptive actions may come in the need for specific approvals from Diebold’s clients, and where AI streamlines payments, money movement or “next best offers” for customer offers based on models in place at specific FIs.

To bring AI to scale, Adams said, requires a collaborative and collective effort. He said that executives are placing their bets slowly when it comes to investing in AI.

“We’re noticing a few chips coming to the table, and everyone has a small allocation toward this particular bet, but no one is going all in. There is not a collective movement of investment allocation just yet,” he said. Consider it a case of AI grabbing an increasing share of mind, if not wallet.

Against this backdrop, he said, Diebold Nixdorf seeks to partner with other like-minded institutions focused on the intersection between payments, digital technology, AI and legacy systems meeting at what he termed the “AI bridge, and discovering how we can cross it together.”

This content originally appeared on PYMNTS.com.

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Cortez Adams

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Cortez Adams

Director of Product Management- Banking Software

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