Latest / Leaders In Payments / Special Series: Modern Finance with Pat Moye, Executive Director of Product Innovation, Receivables at Deluxe | Episode 426

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Special Series: Modern Finance with Pat Moye, Executive Director of Product Innovation, Receivables at Deluxe | Episode 426 · Leaders In Payments

• 0:01
  Speaker 1: Welcome to this special four-part series titled Modern Finance, sponsored by Deluxe, where we explore the future of financial automation.
• 0:09
  Speaker 1: From treasury to accounts payable and receivable, we're diving into how AI and intelligent automation are transforming every corner of finance.
• 0:19
  Speaker 1: In each episode, you'll hear from leaders at Deluxe who are driving innovation and delivering real-world results.
• 0:26
  Speaker 1: Whether you're navigating compliance, fighting fraud or connecting the financial dots, this series is packed with insights you won't want to miss.
• 0:37
  Speaker 2: Hello everyone and welcome to the Leaders in Payments podcast.
• 0:39
  Speaker 2: I'm your host, greg Myers, and this episode is part of our four-part series we're doing on modern finance being brought to you by Deluxe.
• 0:47
  Speaker 2: So today we have a very special guest, pat Moy, who is the Executive Director of Product Innovation at Deluxe.
• 0:54
  Speaker 2: So, pat, thank you so much for being on the show today and welcome to the show.
• 0:58
  Speaker 3: Happy to be here, Greg.
• 0:59
  Speaker 2: All right.
• 0:59
  Speaker 2: Well, let's get started by having you tell our audience a little bit about yourself, maybe where you're born, where you grew up, where you went to school, just a few things like that.
• 1:07
  Speaker 3: Yeah, sure.
• 1:07
  Speaker 3: So I grew up in Fairfield, connecticut, so about an hour outside New York City, went to school at Loyola University of Chicago and studied business administration there and then bounced around a little bit in a few different industries administration there and then bounced around a little bit in a few different industries.
• 1:27
  Speaker 3: Spent a lot of time in HR software, then in payments, then down in Atlanta at First Data, then in Columbus, ohio, at Nationwide Insurance and for the past four years been at Deluxe In all those places helping companies build new products.
• 1:45
  Speaker 2: Okay, okay.
• 1:46
  Speaker 2: Well, for those in the audience who may not know who Deluxe is, if you don't mind, tell us a little bit about Deluxe and maybe where they fit into the payments ecosystem.
• 2:06
  Speaker 3: Yeah, absolutely.
• 2:07
  Speaker 3: If you haven't heard of Deluxe, I'm sure you know a lot about the payment channel that we invented 110 years ago the paper check and ever since then we've been really trying to enable businesses to pay and get paid and grow, and part of that journey has been how do we take this core business of checks, how do we take this core business of checks, printing checks, processing checks and expand into adjacent areas that help businesses with the other problems that come in, like the order-to-cash space, where we're going to be spending a lot of time talking today.
• 2:40
  Speaker 3: So we've been steadily investing in new technology and new platforms that help solve some of the problems in those spaces and enabling us to take those really deep, trusted relationships we have with companies and banks into the next generation, where we're going to have the ability, regardless of what payment channel you're using, tools that can help businesses run their receivables process more effectively.
• 3:11
  Speaker 2: Well, tell us a little bit about your role Executive Director of Product Innovation.
• 3:14
  Speaker 2: What does that mean?
• 3:16
  Speaker 2: What do you do on a daily basis?
• 3:18
  Speaker 3: Yeah, it's one of those words that, when I introduce myself to people, that everybody hears and can mean a lot of different things and innovation at Deluxe.
• 3:30
  Speaker 3: What it means is really solving problems for our customers, and it doesn't always have to be some flashy new use of technology or some crazy new product.
• 3:41
  Speaker 3: It's really spending time doing some really deep research with customers to understand their needs and really understand their pain points and then working on building solutions that address those and really delight users in ways that they can't really even articulate and can't imagine.
• 4:02
  Speaker 3: So there's a whole world of places we could go and my job is to help focus on the places where Deluxe should go and do it from a customer lens, so that we are not just solving problems we think we should solve.
• 4:19
  Speaker 3: We're solving problems that actually make an impact for our customers.
• 4:23
  Speaker 2: Okay, great.
• 4:24
  Speaker 2: So let's dive into the topic at hand the future of accounts receivable automation.
• 4:28
  Speaker 2: So maybe tell us what does that mean, what is accounts receivable Level?
• 4:33
  Speaker 2: Set on a definition, and maybe talk about the size of companies.
• 4:37
  Speaker 2: You typically work with size of banks and we'll build on that.
• 4:42
  Speaker 3: Yeah, absolutely so.
• 4:43
  Speaker 3: I'll start with companies that we typically work with.
• 4:47
  Speaker 3: At Deluxe.
• 4:49
  Speaker 3: Our core business is mid to large enterprises.
• 4:54
  Speaker 3: From a receivable standpoint, when you think about companies getting paid heavily via check, checks are still one of the predominant channels in B2B payments.
• 5:06
  Speaker 3: So a lot of our corporate customers are in that mid to large enterprise and we work with banks of all sizes to offer our receivable solutions to their customers.
• 5:21
  Speaker 3: So that's sort of the landscape of who we work with.
• 5:26
  Speaker 3: But at the end of the day, it's really solving problems for those customers.
• 5:31
  Speaker 3: That are the AR teams at these companies and what they're doing is working through the process of issuing invoices and managing payments that are coming in, matching payments to invoices and remittance and fielding questions and making sure that the business is getting paid and getting paid on time.
• 5:58
  Speaker 3: And if we think about why that's so important, it's the critical component to cash flow that enables businesses to have working capital to invest back in their teams, in new products, in helping customers.
• 6:14
  Speaker 3: And it's a really interesting space because for us, what we see is a lot of the technology advances that we've seen over the years haven't really made it to this space.
• 6:28
  Speaker 3: There's still a lot of work that's surprisingly very manual a lot of spreadsheets, pdfs, emails, right.
• 6:36
  Speaker 3: There's a lot of things that are in this space that cause a lot of strain on these teams, and one of my favorite things when we go and talk to accounts receivable teams is they often refer to themselves as cash detectives.
• 6:49
  Speaker 3: So they are out doing detective work to figure out this payment they just received.
• 6:55
  Speaker 3: Who paid them, what did they pay them for?
• 6:57
  Speaker 3: And so that work is really what stands in between businesses getting paid and being able to use that cash to invest back in their organization.
• 7:08
  Speaker 2: Okay, great, so we've level set on the AR function.
• 7:11
  Speaker 2: I think we all kind of get that.
• 7:13
  Speaker 2: We understand the types of companies and organizations you work with.
• 7:17
  Speaker 2: Now let's talk a little bit about the future and how AR can be more automated and we often hear this phrase embedded analytics.
• 7:25
  Speaker 2: So maybe let's unpack that a little bit.
• 7:26
  Speaker 2: What is it?
• 7:27
  Speaker 2: What's the goal, maybe?
• 7:28
  Speaker 2: What are some of the challenges around that?
• 7:31
  Speaker 3: Yeah, I love how this is becoming more and more important as companies talk about the use of data and really what it's in service of is decision velocity.
• 7:47
  Speaker 3: It's about arming users with the right insight at the moment it's needed and not making them work for it.
• 7:54
  Speaker 3: So if we think about one of the ways we sort of architect decision-making, as I look at helping businesses, it's built on sort of a three-stack pyramid of data at the bottom and data then creates insights as a middle layer which drive action at the top layer.
• 8:16
  Speaker 3: So for me, embedded analytics is all about action and the challenge is, without good data at the bottom layer, the insights might not be good, which means the actions are potentially not the right actions or not specific enough to actually make an impact on your business.
• 8:36
  Speaker 3: So, as we think about why something like embedded analytics would be important, it's because teams need to make faster decisions.
• 8:45
  Speaker 3: We talk about enabling faster payments and we want organizations to help them get paid faster, but if you can't use that to then make faster decisions and smarter decisions, then it's not really that beneficial to get paid faster, because you're still held back by the challenges that your data is causing problems when it's not actually useful for the decisions that you're trying to make.
• 9:15
  Speaker 2: Yeah, I'm going to double click on something you said.
• 9:17
  Speaker 2: You know that bottom layer of data.
• 9:20
  Speaker 2: Is that data that's like always there, it's there or are they having to go out and get the data, and that adds even more complexity.
• 9:29
  Speaker 3: That data exists, but it's in a bunch of different systems.
• 9:34
  Speaker 3: The data from ACH and wire payments is with the bank.
• 9:39
  Speaker 3: The data from lockbox payments is with a company like Deluxe.
• 9:44
  Speaker 3: The data about their open invoices is in their ERP.
• 9:49
  Speaker 3: They've got data in a CRM.
• 9:51
  Speaker 3: They've got data in Salesforce.
• 9:53
  Speaker 3: They've got data everywhere.
• 9:56
  Speaker 3: And the challenge is all of that data is in different models, is in using different fields using a field that means one thing in one data set and the same field using a different label in a different data set.
• 10:13
  Speaker 3: So it causes a lot of problems when you're trying to use that data effectively because it's not mapped right, and even bringing it into a consolidated Excel spreadsheet still requires a lot of work to make sure that it actually makes sense and that the labels are right and that you can actually then use that data to be effective.
• 10:36
  Speaker 3: So one of the areas that Deluxe has really spent a lot of time in is the data piece.
• 10:43
  Speaker 3: It's not the most glamorous part of the problem spaces that we're looking to solve, but without it everything else kind of falls apart.
• 10:53
  Speaker 3: If you don't have really strong data and really trustworthy data, even the most advanced tools can't really deliver their value.
• 11:05
  Speaker 2: Yeah, that makes perfect sense and I guess that's sort of why it's at the bottom of the pyramid.
• 11:10
  Speaker 2: Right, it's the foundation and getting that foundation right.
• 11:13
  Speaker 2: So what are some of the metrics the user metrics or operational metrics that you know the businesses typically have and they're trying to track, and how does that equate into defining, maybe, their future needs and and how they help and to and I'm sure you guys help them prioritize that AR roadmap?
• 11:34
  Speaker 3: Yeah, so you're going to have your stock standard ones like day sales, outstanding payment velocity, unapplied cash rate, percentage of auto match to invoices.
• 11:48
  Speaker 3: Those are all core insights that can be generated.
• 11:54
  Speaker 3: But again, as I was mentioning before, those are just insights.
• 11:58
  Speaker 3: You need to have the tools in place to turn those insights into action that your team can take.
• 12:03
  Speaker 3: But I see a lot of organizations struggle with even some of those stock standard ones because of the disconnected data set.
• 12:12
  Speaker 3: So you have those pieces of the puzzle that are really important.
• 12:17
  Speaker 3: But what I've seen when I go out and talk to CFOs and talk to leaders of receivables teams and ask about what types of insights are they using and share ideas for new insights that they could be generating, there's a whole wish list of things that are so far from their reality because even some of the basic ones they're struggling to really get their arms around.
• 12:48
  Speaker 3: But once you have better data sets and cleaner data, you can get better insights right and you can start to see things like what payment exception types are driving the most manual work right, what's the collections workload by collector and what's the forecast of your cash position versus your actual cash position.
• 13:13
  Speaker 3: So these are things that teams really want to be able to have to make those types of decisions and drive action.
• 13:22
  Speaker 3: But without the full set of data being organized in a way that can generate those types of insights, you're sort of left struggling to figure out that on your own, that on your own, and that's why, when it comes to how to prioritize, where to go from here, it's really about looking where you have bottlenecks today to start.
• 13:50
  Speaker 3: It's about prioritization based on where your needs are that you can start to chip away at, because it's not something that you can implement, a system, and then all of a sudden all of your problems are solved.
• 14:02
  Speaker 3: You have to look at the spaces where you need help and look at the foundational spaces to be able to build from a core and have those more advanced things come later a core and have those more advanced things come later.
• 14:20
  Speaker 3: If you're asking to start with an analysis of your cash position but you don't really have a good way of assessing your day sales outstanding, your analysis on your cash position isn't going to be as good because your foundational data is still missing some pieces.
• 14:38
  Speaker 3: So that's where I would say start where there's bottlenecks.
• 14:42
  Speaker 3: Start where there's the foundational layer of the core elements to help you make those decisions and drive those actions.
• 14:52
  Speaker 3: Once you have those, then you can see what the next set of actions that need to be better informed are.
• 14:59
  Speaker 3: What are the next things that you can start to prioritize from there?
• 15:04
  Speaker 3: So, in a world where I, as a product leader, am constantly thinking about prioritization, it's about taking things one step at a time and making sure that you're not over committing and setting yourself up for a massive project that isn't going to yield results for years.
• 15:27
  Speaker 3: You want something that's going to yield results in weeks and months.
• 15:31
  Speaker 3: Right, and those are the things.
• 15:33
  Speaker 3: How do you take those right-sized approaches?
• 15:35
  Speaker 3: So those are just some questions to ask yourself as you're trying to prioritize.
• 15:41
  Speaker 3: What are those right-sized spaces for us to start?
• 15:45
  Speaker 2: And Deluxe often emphasizes that this automation for I mean really anything but certainly for accounts receivable, this automation is really a journey, right.
• 15:56
  Speaker 2: And so how do you develop or work with your customers to develop that kind of implementation approach?
• 16:05
  Speaker 2: You know what does that look like.
• 16:06
  Speaker 2: And then from a timing perspective, I mean you mentioned obviously there can be projects that take years and there can be projects that take days, but sort of what do you lay out as typical timelines when you talk to customers and what's the implementation look like?
• 16:21
  Speaker 3: Yeah, the reason why we say that it's a journey.
• 16:27
  Speaker 3: Everybody wants the destination right, everybody wants the end of the road and the straight line forward, but that's the hardest thing to get to if you don't take the time to deal with some of the mess and chunk out the work in a way that allows you to take steps in that direction.
• 16:50
  Speaker 3: And also in this space, there's a lot of risk in change.
• 16:55
  Speaker 3: So, if you think about where we started this conversation, receivables is the lifeblood of the organization.
• 17:02
  Speaker 3: Right, and they have the receivable teams have processes in place.
• 17:07
  Speaker 3: They have mechanisms to help them turn a payment into applied cash.
• 17:12
  Speaker 3: So we are injecting into an existing ecosystem of work.
• 17:19
  Speaker 3: And coming in and saying we're going to tear down everything and start over and have a brand new process in place isn't going to work for any team and we don't want it.
• 17:30
  Speaker 3: That's not what we want, because that is a major disruption to the ability for that team to be effective.
• 17:39
  Speaker 3: So where we look to start as to no surprises is on the data.
• 17:46
  Speaker 3: So identify what your data sources are and automate the ingestion into a data platform that can allow for that data to then be used for research, reporting, insight generation and structuring that remittance data in line with the payment data, being able to match it to open invoices.
• 18:16
  Speaker 3: Those types of things allow you to then take those next steps.
• 18:22
  Speaker 3: And taking those next steps then looks like how do we get some of the more unstructured data sets into the mix?
• 18:31
  Speaker 3: If you have an email inbox that you have for customers who are paying invoices digitally and they send emails saying, hey, I paid this invoice, that's not really a structured set of data.
• 18:44
  Speaker 3: So don't start with some of the more complex data sets.
• 18:48
  Speaker 3: Start with the ones that have some structure that's just a little disconnected and then move into those unstructured data sets that can then power the core platform to be more effective, because now you have an additional layer into what you're using for matching, for research, for reporting and then from there, now you have all of the pieces of the puzzle.
• 19:15
  Speaker 3: You have your payments, you have your remittance, you have your invoices, you have your customer information.
• 19:21
  Speaker 3: Now you can start to then apply that in those layers of intelligence that the CFOs and the leaders of these finance teams really are craving.
• 19:35
  Speaker 3: But if you start with those trying to solve for your intelligence layer without solving for your data layer, you're going to have a big problem when that data may or may not be trustworthy.
• 19:51
  Speaker 3: You want to be able to trust the data, so that's where we spend the majority of our time is making sure that we have the highest level of data integrity with what we bring into our products, our tools, so that we can start to unlock the value of automation and intelligence with that data set, assuming a client has kind of mastered the foundational and has the data, maybe they're looking at activating some of these more advanced things or even integrating other technology, but, as everyone knows, they're not the ones doing the development work right?
• 20:29
  Speaker 2: There's no development team in AR automation that I know of, so how do they do that?
• 20:34
  Speaker 2: How do your clients kind of take advantage of those things without overloading their IT and dev teams?
• 20:41
  Speaker 3: Yeah, this is one of my favorite parts of where we've been focused is let us handle the complexity for you.
• 20:52
  Speaker 3: That's part of the mantra of our team, because a lot of what we've seen over the years and, candidly, what Deluxe had done before our pivot to a payments and data company is that if you want to bring this data into our system, you have to follow this format, which means development work on your end to build a file that fits that format that then can be imported into our system.
• 21:24
  Speaker 3: We've made fundamental changes to how we think about that, and a big part of our platform is rooted in just give us the data as it exists today.
• 21:38
  Speaker 3: You have data you can export from a system.
• 21:41
  Speaker 3: Don't worry about formatting it.
• 21:43
  Speaker 3: We will take care of that.
• 21:44
  Speaker 3: Let us handle that complexity for you so you don't have to spend those resources to enable a product to work.
• 21:54
  Speaker 3: We want to take that on because that's really where some of the biggest hurdles for organizations to adopting these tools lie is in getting resources, and it's why, as I mentioned before, the accounts receivables teams haven't really fell to the advancements in technology that other areas in the organization have is because they don't get as much time and attention from internal resources, technology resources as other parts of the business that are more revenue generating.
• 22:29
  Speaker 3: And I think that that's really one of the big opportunities for leaders in this space to really think about is how do you reframe your receivables team from a service provider to the organization to a strategic advisor to the organization, and that then allows you to have more a seat at the table for resources and things like that.
• 23:00
  Speaker 3: So we want to take on that complexity and enable you to have those types of conversations that really pivot.
• 23:08
  Speaker 3: You know where you're positioned in the organization and do it in a way that you don't have to.
• 23:15
  Speaker 3: You know spin up a technology project and you know beg, borrow, steal for resources to be able to do it.
• 23:25
  Speaker 2: Sure, makes a lot of sense.
• 23:26
  Speaker 2: So what do you see as, beyond obviously trying to get more IT resources or development resources, what do you see as other internal barriers that keeps AR from really scaling their automation?
• 23:45
  Speaker 3: I think there's a couple things I'll point out, one being just not knowing where to start.
• 23:52
  Speaker 3: It's a big hairy mess when you go through and try to unravel all of the different pieces of the puzzle here, especially if you think about a mid-sized business who has gone through an acquisition of another business.
• 24:10
  Speaker 3: Now you're dealing with two ERPs, or maybe even more, and two banks and other payment channels, and now you're trying to even that consolidation effort is now multiplied beyond just trying to handle it for one organization, and so you run into this scenario where you don't even know where to start and everything feels like a mountain to climb, and so I think that that tends to be one of the barriers there, and a lot of that can be rooted in some more legacy mindsets.
• 24:46
  Speaker 3: If I think about I'll use a technology and product analogy here where traditional product development was more of a waterfall approach, where you build out all the requirements and then everything's defined, and then you give it to a technology team to build, and then they build the whole thing and then it's ready for a customer Versus an agile approach, where you define what is the way you can deliver value and solve a customer need, but not everything, and build towards everything over time, incrementally releasing value.
• 25:28
  Speaker 3: I think a lot of parts of different businesses still kind of operate in a more waterfall mindset where, okay, well, if we're going to do this, it has to be everything, and I would challenge teams to really change that right.
• 25:41
  Speaker 3: Change that mindset so you're not thinking that it has to be this massive project in order for us to get funding, in order for us to get time of day from different teams.
• 25:54
  Speaker 3: Don't think about making these big swings.
• 25:57
  Speaker 3: Think about the incremental gains you can have by just changing some pieces of the puzzle.
• 26:05
  Speaker 3: Just take your lockbox and ACH and wire data and just have it all in one place.
• 26:13
  Speaker 3: That doesn't seem like a lot, but I'll tell you that's not easy.
• 26:18
  Speaker 3: For companies to just then have one portal for being able to research and have access to all the data in one place can start to then change some of the other behaviors.
• 26:29
  Speaker 3: And now all of a sudden you're like, okay, now we can do this, now we can do this.
• 26:32
  Speaker 3: So back to your question on prioritization.
• 26:35
  Speaker 3: When you prioritize a big transformation and then try and do it in one big swing, it's going to take forever and it's not going to yield the results you want it to.
• 26:47
  Speaker 3: So transform in the most important areas first and take those smaller steps.
• 26:54
  Speaker 3: Think in a more agile way instead of a waterfall way, to get you to the outcomes you want to achieve.
• 27:02
  Speaker 2: All right.
• 27:02
  Speaker 2: Well, it's been a great discussion so far.
• 27:04
  Speaker 2: I mean, you've shared a ton of incredibly valuable insights and wisdom, obviously with your experience.
• 27:11
  Speaker 2: But if you could try to boil all of that down to maybe one piece of advice for the leaders in this AR space, what would that be?
• 27:20
  Speaker 3: Yeah.
• 27:20
  Speaker 3: So I think my advice would be don't fall for the flashiness of AI, automation, all of these new tools that are out there for teams to be able to take advantage of.
• 27:42
  Speaker 3: Make sure you understand the data that's underpinning it, because it's easy to fall into that trap.
• 27:52
  Speaker 3: And one of the things you asked me about what my role is and what innovation means.
• 27:58
  Speaker 3: At Deluxe, one of the things that we see a lot of is innovation theater in the marketplace, where it's using flashy words, buzzwords, ai, all of these things that generate a lot of buzz in the market, but value-wise, I think there's still a lot to be understood about what the true value of those tools are if they're not run on a data platform where data integrity is priority number one.
• 28:36
  Speaker 3: So that would be.
• 28:38
  Speaker 3: My biggest piece of advice is, as you're looking to transform, as you're looking to take advantage of all of the things that exist today and new technologies, don't fall for what seems like the flashy thing to do without truly understanding how it works and what data powers it, because you can end up in a situation where you think you have automation but your team's actually doing the work.
• 29:07
  Speaker 3: Their day-to-day doesn't actually get any better, gotcha.
• 29:10
  Speaker 2: Well, before we go, I'm just going to open the floor and see if there's anything else you'd like to add to the conversation.
• 29:15
  Speaker 2: Anything maybe you feel like we missed or you wanted to double click on, so just going to open the floor for that.
• 29:20
  Speaker 3: Yeah, no, I appreciate the time.
• 29:23
  Speaker 3: I love this conversation and I hope for folks that know the Deluxe name and know us as the check company, you can start to see that we've come quite a long way from the core product that we've had for the past 110 years.
• 29:43
  Speaker 3: It's really been a very specific focus of ours.
• 29:50
  Speaker 3: It's allowed us to enter into these new conversations, but our core goal is still the same Helping businesses get paid faster and be smarter about the decisions they make and remove friction from the processes that they're operating on a day-to-day basis.
• 30:14
  Speaker 3: So it's been an awesome journey to be a part of over the past four years here and excited to really see the next things that we're bringing to market.
• 30:27
  Speaker 2: All right.
• 30:27
  Speaker 2: Well, pat, thank you so much for being on the show today.
• 30:29
  Speaker 2: I know your time's very valuable.
• 30:29
  Speaker 2: So, Pat, thank you so much for being on the show today.
• 30:30
  Speaker 2: I know your time is very valuable.
• 30:31
  Speaker 2: So again, thank you so much for being on the show.
• 30:34
  Speaker 3: Thanks for having me.
• 30:35
  Speaker 2: And to all you listeners out there.
• 30:36
  Speaker 2: I thank you for your time as well, and until the next story.
• 30:40
  Speaker 1: Thank you for listening to today's episode.
• 30:42
  Speaker 1: If you'd like more information on the transformative potential of AI and automation in modern finance, please visit wwwdeluxecom.
• 30:52
  Speaker 1: Slash receivables hyphen management.
• 30:54
  Speaker 1: Slash cash hyphen application.