0:07 Hello everybody, Adam Parks here with
0:10 another episode of Five Minute Pitch.
0:12 Today I'm here with my longtime friend
0:14 and a guy you've probably seen around
0:17 the conferences, Mr. Mike Walsh with EXL
0:20 here to talk to us about Paymentor and
0:22 how they're collecting accounts using
0:25 artificial intelligence and voice and
0:27 really just a cool frictionless process.
0:28 But how you doing today, Mike? I'm good,
0:31 sir. I appreciate you having me. Um,
0:33 excited to talk to you about
0:36 Paymentor. Uh, EXL is probably the
0:38 largest company no one's ever heard of.
0:40 Traded on NASDAQ,
0:45 55,000 global employees in counting. Um,
0:48 but instead of telling you, let's just
0:50 show you. I think that's better than me
0:51 talking. It's a good way to start. Let's
0:57 For effective collections, the contact
1:00 with a customer has to be driven by data
1:02 decisioning. It has to be through the
1:04 channel of choice and it has to be
1:06 personalized with the right contexts.
1:07 That is the only way to engage the
1:09 customers, call them to action and
1:12 optimize collections. Paymentor helps
1:14 achieve all of that. Let us look under
1:17 the hood and see how it's done.
1:19 Paymentor receives the overdue customer
1:21 data. The machine learning algorithm
1:23 determines the channel of choice, time
1:24 to send a message, and the modality of
1:26 the message to engage the customer and
1:29 persuade them to pay. The messaging goes
1:31 through a compliance check and is
1:33 executed in the form of an email, SMS,
1:37 WhatsApp message, or virtual agent IBR.
1:38 When the customer responds, the
1:40 real-time data about the customer's
1:42 engagement is tracked by the solution
1:44 instantly. For example, if the email was
1:46 open or if the customer responded to an
1:49 SMS, Payman handles that information
1:51 using a self-learning algorithm to
1:53 determine the most optimum channel of
1:55 communication in the tone of the next
1:58 message. Now, let's look at a real life
2:00 example. Daniel is a personal loan
2:02 account holder of your bank. He misses
2:05 an installment payment. Let us see how
2:07 Daniel's behavior drives EXL's payment
2:10 through email and SMS journey.
2:12 Daniel gets his first email and SMS
2:14 informing him of a mispayment on his
2:16 monthly installment. He does not open
2:19 the email. He reads the SMS but does not
2:22 respond. Daniel receives a second email
2:24 and SMS. He does not open the email
2:27 again, but he replies to the SMS assist
2:29 because he needs some assistance. Now,
2:31 he had multiple options to pay or opt
2:34 out or call a representative, but chose
2:36 assist. In a few seconds, Dana receives
2:39 another SMS requesting him to verify his
2:42 identity to continue with his assistance
2:45 request. After successful verification,
2:47 he described his hardship. He informs
2:50 payment of reduction of his [Music]
2:56 [Music]
2:59 income. Then the bank sends him an SMS
3:01 acknowledging his situation. The SMS
3:03 contains a link to the payment portal
3:05 where he can set up or select from
3:07 available payment
3:10 plans. Daniel clicks on the portal link
3:12 and is redirected to a portal login
3:15 screen. He logs in and can see his loan
3:17 details and overdue installment. He
3:18 clicked on the option to set up a payment
3:24 plan. Daniel selects a suitable payment
3:26 plan and proceeds to make the payment.
3:28 His account no longer remains delinquent
3:30 after the first payment is made. The new
3:32 payment schedule is displayed on the
3:33 homepage for his [Music]
3:35 [Music]
3:38 review. This personalized interaction
3:39 eliminates many of the differences
3:42 between digital and live collection
3:44 experiences, but it's more private and
3:47 Daniel chooses when it's convenient to
3:49 respond. This helps improve customer
3:52 satisfaction. Additionally, EXL Payment
3:54 generates a lot of data and insights on
3:56 our customers behavior that our clients
3:59 find very useful. Our clients benefits
4:01 from EXL payment are in the following
4:04 three ways. Increase collection rate,
4:06 usually around 100 to 300 basis points.
4:10 Reduce cost to collect 10 to 30% and
4:13 improve customer [Music]
4:17 [Music]
4:21 satisfaction. So what is that video mean
4:24 for you? Right? Like so depending on who
4:26 you are, a creditor, collection agency,
4:30 a debt buyer, payment can help you first
4:33 party. That's buckets one through six.
4:34 We're actively working that with many
4:38 clients around the world. Um charge offs
4:40 fresh charge offer or as we were talking
4:42 earlier, Adam, the opposite of fresh
4:46 offs, very old, very beaten up paper. It
4:47 works right because it's an it's an
4:50 engagement tool and it's private and
4:52 customers can respond back to you on
4:55 their own time. They get a text at 2 PM.
4:56 They can respond at midnight and start
4:59 having a conversation with the AI. Um,
5:01 so that's part of it. And then the other
5:03 question I get to is, well, I'm
5:05 commercial or I'm medical. It's never
5:07 going to work. No, it works for medical,
5:09 works for commercial, credit card,
5:13 loans, utility. It is very flexible and
5:16 our our clients help us. I mean you
5:19 approve every template, everything that
5:21 is being said to your customer is
5:23 pre-approved. Um and it's very compliant
5:26 as well. Everything's built in. So every
5:28 language in the world too. So if you're
5:30 in Canada and you want to do French, but
5:32 out of the box in the US, we do Spanish
5:36 and English. So that's really some of
5:39 the, you know, what we can cover. And I
5:40 think there's an extra benefit. It was
5:43 covered a little bit in the video is
5:46 that behavioral data. And to me, many of
5:48 our customers, you know, take Mike Walsh
5:50 and Adam Parks. Let's say we were both
5:51 have the same propensity to pay,
5:54 struggling with a bill.
5:57 I I get some, you know, emails and texts
5:59 from payment. I do nothing, right? But
6:02 Adam Parks, he he responds. He tries to
6:04 negotiate a payment plan and maybe it's
6:05 not within the guidelines of, let's say,
6:08 it's a collection agency, but he's
6:09 trying. Then he goes to the payment
6:10 portal. he's trying to look for
6:12 something. Who are you going to call
6:15 first? If you have, you know, 30 agents,
6:17 are you going to call Mike Walsh who did
6:19 nothing or is that behavior data now
6:21 really valuable and you're going to call
6:22 Adam Parks? I call Adam Parks, right?
6:25 Like it's it's a so it changes how we
6:29 look at not just propensity to pay.
6:31 That's helpful. It's a starting point.
6:32 Now you have that behavior data and if
6:35 you're an API connected to us, you're
6:38 getting that almost in real time. or
6:39 even if you're, you know, you don't have
6:42 that kind of system or that connection,
6:43 you get that the next day, you you're
6:46 ready to go. So, it's a really powerful
6:48 tool. I'd love to demo it for anybody
6:51 out there. Sir, you've seen it. What do
6:52 you think? Those of you that are
6:54 watching, I highly suggest that you do
6:55 take a moment, reach out to Mr. Mike
6:57 Walsh here and go through the demo
6:59 because what we just watched, I know, is
7:03 a very small subset of the opportunity
7:04 that I've had to kind of go through the
7:06 whole model and really get a feel for
7:08 it. And as we look at the growth in the
7:10 volume of accounts over the next couple
7:11 of years and the decrease in
7:13 collectibility, finding more
7:14 cost-effective ways for us to
7:16 communicate with consumers and leverage
7:19 self-service technology, and this is
7:20 kind of all of those things together.
7:22 It's one thing to send out emails and
7:23 text messages, but where are you
7:26 actually sending those consumers and how
7:27 are you engaging or interacting with
7:30 them at that point in time? Feels like
7:32 Paymentor has got a lot of the elements
7:35 that are built into both those digital
7:38 communications type efforts as well as
7:39 those self-service efforts because once
7:41 you've got them to connect, you're
7:43 pushing them to a location and you're
7:46 enabling the most frictionless payment
7:48 opportunity or negotiation that you can.
7:50 seems like a really cool piece of
7:53 technology and something that is greatly
7:55 needed around the debt collection
7:58 industry as we continue to face these challenges.
7:59 challenges.
8:01 Appreciate that. It is. We're here.
8:04 Please reach out. For those of you that
8:05 are watching, if you have additional
8:07 questions you'd like to ask, you can
8:08 leave those in the comments below. I'll
8:10 also be leaving Mike's contact
8:12 information below as well so that you
8:14 can reach out to him directly, schedule
8:17 a demo, and start a discussion, start to
8:18 learn how we're going to leverage
8:20 artificial intelligence in 2025 and
8:23 beyond for the debt collection industry.
8:25 But until next time, everybody, Mike, I
8:26 really do appreciate your five minutes
8:28 today. Thanks so much for coming on and
8:30 enjoying some time with me. Thanks Adam.
8:31 Appreciate it. For those of you that are
8:33 watching, I hope you all enjoyed this.
8:34 We'll see you all again soon. Bye everybody.
