How AI Is Being Used By Verizon & Mastercard To Drive Innovation

Benzinga

Join Benzinga for a Live, Virtual Summit spotlighting the Titans of AI - featuring the hottest innovators, platforms and providers reshaping business and finance today.  BRIAN HIGGINS - Chief Customer Experience Officer | Verizon https://www.verizon.com/business/en-au/ (NYSE: VZ)  MOHAMED ABDELSADEK - Executive Vice President, Data, Insights & Analytics | Mastercard https://www.mastercard.us/en-us/business/fintech.html (NYSE: MA)

Transcript

00:00 How are your companies using AI to drive innovation?

00:04 And can you share an example

00:06 of a successful AI implementation at your organizations?

00:10 - Yep, Mahamud, you want me to start off there?

00:15 - Sure, go for it, Brian.

00:16 - Okay, yeah, we'll do.

00:17 So listen, I think, Mitch, first of all, great seeing you.

00:20 The first part I'd say is that AI is already heavily embedded

00:24 into the Verizon organization.

00:25 We're using it throughout all of our operations.

00:29 And if I had to pick just a few key areas for us,

00:32 it has to do with how do we interact with the customers,

00:35 and I'll touch on that in a moment,

00:37 and then also how do we become more efficient

00:39 within our operations.

00:42 For the customer side,

00:43 probably the best example I can provide

00:45 is gonna be around personalization.

00:47 If you think about Verizon,

00:49 we've got nationwide footprints, we're a global company,

00:52 we have well north of 100 million customers,

00:55 both home broadband and also mobile,

00:58 and then we have offers with content partners,

01:01 our own value props, et cetera, that sit in between.

01:03 And we've gotta make sure that we create

01:06 a one-to-one engagement with the customers.

01:08 So what that really means is that

01:10 pulling together value props or offers

01:12 based upon all the offerings that we have

01:15 directly with the consumer.

01:17 So the best way to think about this is that,

01:19 if Mitch was looking for a particular offer with Verizon,

01:22 I wanna make sure I take into account

01:24 everything that's in his account,

01:26 does he have home broadband with us or not?

01:28 Mobile, is he using a Disney+ as an example,

01:31 and then tailor something very specifically to his needs.

01:35 That way, it's a real one-to-one engagement,

01:37 and that's all driven by AI.

01:39 So we've got everything in the background

01:40 that pulls that together.

01:42 On the operational side,

01:43 I'll just touch on efficiency within our call centers

01:46 as an example.

01:47 So we've had going on for a number of years,

01:50 an engagement where we work together to match customers

01:53 with the right representative,

01:55 within our call center.

01:56 So what that means is,

01:58 if you're calling in because you've got

02:00 a question on a promotion or a question about a device,

02:03 we wanna make sure that we get you mapped

02:05 to the best representative

02:06 that's gonna have an efficient call

02:08 and one that's gonna lead to customer success.

02:10 So we do all that matching in the background,

02:12 again, all AI driven,

02:14 and then that makes for a better interaction

02:16 between our customers

02:17 and also the representative that we have on the floor.

02:20 Thank you for sharing that perspective.

02:22 We'll go to Mohamed here.

02:23 Yeah.

02:24 Yeah, look, like Brian said,

02:26 for us, we've been using AI for many, many years.

02:29 And obviously there's a lot of interest in AI right now.

02:31 And certainly with generative AI,

02:33 it creates a lot new opportunities.

02:35 But if I look at how we've been using AI at Mastercard,

02:39 so you know, three primary ways.

02:40 We've embedded in many of our products.

02:42 So, and we'll talk about a couple of examples of that.

02:45 We also help many of our customers to use AI

02:49 and take advantage of AI.

02:51 For example, we partner with some of the banks

02:52 to help them figure out how to create custom analytics

02:55 or AI models within their organizations.

02:58 And the third big area for us is internally,

03:00 is somewhat sort of that customer service example

03:01 that Brian discussed.

03:03 We use AI across different areas of our company

03:07 to help enhance productivity

03:09 and make our organization better and more effective.

03:12 A couple of examples on the product,

03:14 I would say for us as an organization,

03:16 we see a lot of transactions.

03:19 One of the issues in payments

03:21 that you're probably aware of, Mitch, is fraud.

03:23 Obviously, there's a lot of folks trying to mimic your,

03:26 or copy your card and commit fraud

03:29 and frankly, steal money.

03:30 So we see over 125 billion transactions a year.

03:34 We use AI models to help us prevent fraud.

03:37 And frankly, you know, for us as an organization,

03:41 that's been extremely effective.

03:43 And now we're looking at how to take advantage

03:44 of some of the next generation AI

03:46 to take advantage of that.

03:48 We also use AI quite a bit in personalization.

03:50 As a matter of fact, we own one of the leading companies

03:53 called Dynamic Heal in helping with personalization.

03:56 As you can imagine, a big part of figuring out

03:58 what message do you put in front of what customer

04:01 requires the ability to leverage AI

04:03 to identify what you do.

04:05 And Netflix is a great example of that.

04:06 When you log in, you see a different set of sort of videos.

04:10 It might be the same exact name of video,

04:11 but you see somebody, you know, holding hands

04:13 or somebody else might sort of see somebody

04:15 with a machine gun for the exact same movie, right?

04:19 So for us, personalization is a big area.

04:21 We have a lot of analytic tools.

04:23 One of them is a business experimentation product

04:25 that we use as well, where we take advantage

04:28 of the AI models to help remove bias

04:30 from some of the business experiments that we use.

04:32 The product is called our Test on Mark solution.

04:35 So, you know, broadly what I would say

04:36 is we have hundreds of data scientists.

04:38 We've been spending a lot of time on AI.

04:40 This is a big focus for us and will continue

04:42 to be a big focus going forward.

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