AI for Fintech: Making Customer Service Feel…Human?

Probably three or four areas that I, I think AI really, really applies to, just in a general sense across FinTech.
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Um, probably one is, is the response time to a customer. Uh, the chat bots are, you know, almost instantaneous as far
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as responses they can bring up, uh, specific data points, generally a lot faster than, um, most individuals can, uh,
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and, and, you know, can do it in a multilingual format. The second is just availability. So, you know, as it relates, it’s around the clock.
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It’s, uh, you know, people, uh, who are awake in the middle of the night can get responses to something that’s pressing
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and, and top of mind, rather than having to wait, wait for business hours, uh, to speak to an individual scalability.
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So a lot of customers, uh, particularly in, in FinTech, uh, itself, this lends really well too, because you see a lot of highs
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and lows around volume of requests, um, whether there’s simultaneous, uh, or there’s, you know, seasonal spikes or sudden surges in those customer inquiries.
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The scalability aspect is, is kind of what, you know, particularly AI helps solve. And then finally, personalization, I think would be the biggest, you know, final use case
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that AI really helps, um, address. Uh, because you can train the ai, you can, uh, formalize a response, you can provide it
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with the right inputs, um, to deliver more of a tailored experience and to, uh, make, you know, suggested relevant products
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and services to that individual or based on, you know, their kind of implied behavior. Um, as well. Lemme see, The best cases
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for a ai, or the best use of it is kind of, uh, setting it up for success at the forefront
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of interaction with a customer. Um, positioning AI so that it’s addressing, you know, the initial, uh, customer challenges, routine inquiries,
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um, you know, those classical kind of interactions of, you know, tell me, um, I have a dispute on a transaction
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or, uh, you know, have a question about, uh, eligibility for a product or service. You know, that, that is, you can leverage both AI
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and humans for, for, you know, both interactions. But generally speaking, AI can scale faster and then start to refine, um, you know, the answers
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that it’s providing and the assistance it’s providing to then hone that and personalize that experience to an end, you know, uh, uh,
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person who can then provide the final kind of leg of support. My perspective would be, you know, focus on, uh, kind
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of future proofing your customer service strategy and how do you do that as a FinTech company, right? So I think it’s, it’s, uh, the focus there as a FinTech is
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to say, uh, if I’m going to adopt ai, how am I gonna do it in a very intelligent way, uh,
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in a very progressive way, meaning I’m not jumping fully in perhaps because I don’t really know, you know, how my customers are gonna interact with it.
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I don’t know how, uh, it’ll interact with the, the legacy and, and current applications that we have and the data sets that we have, right?
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So I would strongly suggest or recommend, uh, kind of fostering more of a hybrid model where you are adopting AI in a, you know,
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increasing format or looking at how you’re going to adopt ai. Um, and then back filling that with what is the human kind
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of, um, expertise that I need, interaction and expertise that I need that maintains a high touch of service for my products or company.
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Uh, and, and then, you know, how do I continue to build upon that hybrid model? So I think the, the idea is that you’re blending kind
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of the benefit of both.
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