Faster, Better, Cheaper: Conducting Business in Real-Time to Satisfy Customers' Expectations

As customers expect banks and financial institutions to conduct business on their behalf in real time, the world of digital finance is rapidly evolving to anticipate and satisfy the needs of retail and commercial customers that are increasingly demanding products and app services—from instant payments to trading settlement and beyond—that are faster, better and cheaper. Panelists discuss the process for developing a roadmap for the successful implementation and adoption of Innovative products and services in various business lines that will appeal to customers who want an instant-everything experience and results.

Transcription:
Transcripts are generated using a combination of speech recognition software and human transcribers, and may contain errors. Please check the corresponding audio for the authoritative record.

Mary Ellen Egan (00:08):
So I am here with this esteemed panelist and we're going to talk about—first I'll introduce them, but we're talking about conducting business in real time to satisfy customers' expectations. So I have Katie Whalen, head of small and mid-size business, financial institution channels and global SMB strategy, merchant solutions at Fiserv. I also have Lauren Bowes, who's the head of sales, banking and wealth at Plaid, and Carolyn Booth, head of US personal and business banking at BMO. Thank you. You're in for a treat. These women really know their stuff, let's just say. So we think about how the landscape is changing and how competitive it is. And banks are being challenged by a number of competitors: neobanks, challenger banks, fintechs, tech giants like Apple Pay and Google Pay, crypto, decentralized finance, retailer banking services like Walmart and Amazon lending. So you combine that with customer's expectations, which is whatever apps you use—Starbucks or like I just use the Glam Squad app, which is pretty cool.

(01:15):
If you've never used it, you get a stylist to come and do your makeup or your hair. Obviously it didn't happen today, but it will. And then when it comes to banking, then you combine that with a very regulated industry, but there's still that demand. So how do you meet the customers where they are? Katie, do you want to start?

Katie Whalen (01:32):
Sure. Thank you. Thank you very much, Mary Ellen. And thank you guys for joining here today. It's a great event. So I think it's really interesting. It's a conversation we have often with our clients. I work at Fiserv where we work both with banks as well as merchants on both sides of the value chain. And as we have conversations about the engagement with new FinTech players or the large tech players, there's a lot of conversation we have around changing expectations by the consumer. And that consumer can be an individual or a business like an SMB or small business. And that change in expectation is really looking for an adjustment for instant access, engagement in a different way, meeting the consumer where they're at with the values and experiences that they're seeking, and meeting them with the content and alignment and reach accordingly.

(02:37):
And with those changes, that changes the way that most consumers engage with their everyday brands like a bank or with other merchants. And we have a lot of conversations with our clients about how do we make sure we have the right technology, the right data to support that technology, and exchanging the experiences. So personalization of offers or content that meets them where they're at, whether it's on an online banking portal or whether it's on an Instagram post that speaks to that specific individual. And I think what's incredibly important specifically for the banking industry is that the banking industry really is one of the most trusted industries, at least globally, but in the United States. And maintaining that trust while also embracing that instant access is incredibly important and finding that appropriate balance so that it's not a little creepy with the data that's presented or how personalized it really is, is incredibly important to toe that line.

(03:46):
And that's a conversation we consistently have with our customers about how we progress accordingly, but also maintain that trust that is so important for this industry and also aligns to the regulated nature of the vertical.

Lauren Sullivan Bowes (03:59):
Hi.

Mary Ellen Egan (04:00):
Working.

Lauren Sullivan Bowes (04:01):
So Lauren Bowes here with Plaid. And I thought it was really interesting, Mary Ellen, when you kicked this off, talking about banks and financial institutions competing with fintechs or giant technology companies. So I joined Plaid five years ago. At the time, Plaid worked really closely with a lot of FinTechs, technology companies, and startups. At the time, we were just starting to really engage with big banks and financial institutions about how do we deliver this experience? They're seeing it in Venmo. They're seeing it in Amazon; they want that instant experience. It was the middle of COVID, so there was a huge drive. As the branches were closing, how do we compete? How do we keep up with these neobanks? We had a large group of banks and financial institutions that kind of jumped on board and embraced the technology and realized we've got to figure this out to meet our consumers where they are.

(04:54):
Now, the conversations we're having aren't any more about just the FinTechs or just the neobanks. They're talking about their competitor across the street, because there's been a huge shift of people that have embraced it and worked with that change. And our team works with top five banks all the way down to regional banks and credit unions. Not everybody has this massive technology budget and not everybody has a crazy amount of resources. So we work really closely to help every bank and financial institution not only compete with technology companies as well as the neobanks, but competing with each other. That's been a huge shift and a huge focus. I'll stop talking in a minute, I promise, Carolyn. I think another thing that's really important is that because banks and financial institutions are so highly regulated, there's a lot of internal debate and a lot of internal conversations about, yes, we want to deliver this amazing experience.

(05:53):
However, we have to do this in a secure and compliant way, and we don't have the luxury of basically screwing this up. So the fraud team sometimes wants to lock it down so tightly that you're really compromising that user experience. And great, you're fighting fraud, but nobody can actually onboard or get anything done with your financial institution. So we're working really closely to be able to manage that fraud before it happens with our technology and also deliver that great user experience.

Carolyn Booth (06:26):
Awesome. So the benefit of going last is you can say what they said. Isn't that beautiful? We didn't rehearse this, so I didn't know what they were going to say. So I'll echo a few comments and then I'll maybe add one other perspective. So as head of US Personal and Business Banking, I am not the technology specialist, but I am the person chasing partners like these two ladies to say, "I see a client need and how do we help them and how do we close that need?" So I come at this conversation a little bit through that angle. So we do see clients today; they expect their digital experience to mirror every other digital experience they have. And they're no longer comparing us to another bank. They're comparing us to all providers. And there's just that sense of need for immediacy, immediate satisfaction, instant affirmation that what I wanted to get done got done.

(07:25):
The way I think about it is clients aren't looking for speed for the sake of speed. I think that there are a lot of underlying reasons for it. So we do what's called a real financial progress index at BMO. And what we heard in the last index is 53% of American consumers are feeling highly at risk and vulnerable with respect to their financial situation. So I think some of this need for immediacy—I want to know my paycheck is in my account, I want my paycheck early, I want the pre-approval on my loan, I want that instant payment to know it went through so some other payment doesn't go through ahead of it—I think some of that need for immediacy is really grounded in this sense of financial vulnerability. And so it's incumbent upon us as a bank. Part of building that confidence I think is supporting those client needs.

Mary Ellen Egan (08:21):
Is there a difference between what the consumer wants and what a business client wants per se?

Carolyn Booth (08:26):
I would say it depends on the spectrum. I would say definitely the micro Soho businesses are very much in that same space as our consumers. And I think I would say that further to what Carolyn was saying, there's probably more near time use cases for Stablecoin and that with some of your larger corporate clients that is closer on the spectrum in terms of bringing AI and those kind of capabilities to play ahead of some of the consumers. So I think the higher up you get on the commercial side, those needs evolve, but on the lower end, I would see them as fairly similar.

Mary Ellen Egan (09:10):
Interesting. Okay. So let's talk a little bit, because you touched on it, Carolyn, so maybe you want to kick this off, about how technology is shaping banking. I mean, AI—we're all hearing AI, AI, AI. I think I'm getting sick of hearing AI because I don't use it enough probably, but it is important and it is impacting so much of what everybody does either on a personal level or professional level and on a banking level. So how are you using AI or what other technologies are changing how BMO handles banking?

Carolyn Booth (09:39):
Sure. So when I think about how technology and AI is impacting banking, we used to be the providers of products in brick and mortar. And I think today of the role of banking and my role, a lot of it is how do I become the orchestrator of all these platforms and the different ways that we're going to bring capabilities together to serve the clients. So I think that that is a big part of the evolution for us in banking and finding and establishing those right partners and balancing the need to move quickly without eroding the trust that we spoke about. Because we have so much equity and trust with consumers today, that is probably the advantage that banks have and not wanting to put that at risk. So we are using AI. I would say mostly gen AI in terms of accelerating processes and getting work done faster.

(10:41):
We use Microsoft Copilot. So I think it was maybe Jana said she lives in it. I live in Copilot. I live in ChatGPT. It's how I run my life, I think. And so we're on the cusp. It's really becoming a bigger priority for us and making sure we have the talent in the organization is critical. And data, data governance, data modernization is something that is no longer a nice-to-have. You have to have it in our industry.

Lauren Sullivan Bowes (11:14):
Yes. So AI is literally at the center of pretty much every conversation that we have, whether internally or externally. It has been so incredible in our speed and innovation at Plaid. So our engineering teams have been able to develop at a rate that I've never actually seen at a technology company in my life. We use maybe 20 different—it's not just Copilot or ChatGPT. If you saw the things that I asked ChatGPT on a regular basis, I use it for everything, work, and then I'm asking it crazy questions about where to get my hair done. It is—Glam Squad. Yeah. I'm not a paid spokesperson. It is so critical. And I think the way that I'm seeing it show up and how we're partnering with banks and financial institutions is some of our credit products. So what we're able to do in terms of understanding consumers, the full picture, right?

(12:14):
And how do we offer them an ease of anxiety like we're talking about? How can we get them a loan that they actually need and how can we give them advice? People don't just want, "Oh, I have this full financial picture." They want the full financial picture, they want it right away, and they want you to help them make decisions or what to do next with their finances. We are using AI to be able to analyze mass amounts of data because of the size and scale of our network to really help consumers make better choices and manage their money better.

Katie Whalen (12:49):
Excellent. And I think if I was to reflect on really the last year or so with AI, about a year ago, it was really a technology looking for a use case or a problem to solve and now we're really embedding it into every aspect of our business in terms of the progression and the intelligence and the access to the different models that have been trained to solve for different problems. The core question that we consistently ask ourselves at Fiserv—and at Fiserv, we are really the technology behind a significant amount of the banking and the merchant industry—and we're constantly asking ourselves, "Okay, if we apply this technology or this model to this part of the value chain or this part of a process, what is the financial outcome that it's going to drive?" And making sure that we're grounding ourselves in the expense reduction that it's going to drive or the revenue uplift that it's going to produce.

(13:48):
And I think that's an important question as you apply AI into everything you can do because you could find a million different applications for it, but really what is the business outcome that it is driving, whether it's for you or your customer base. We've started within our small business sales team, really looking at the end-to-end funnel of how we apply AI for sales, both for the sales we do, and then we also support the sales teams at our bank partners. We've been in the process of, just as an example, deploying a digital onboarding tool that has been like a science in the consumer space for years, but really is absent with the exception of Square who has a good process—but not an amazing process—in the flow for onboarding a small business effectively and looking at how we use AI to look at data sets, whether it's data that the bank has from our bank partners or a third party data set, and how do I then apply an LLM model to then find intelligence about that customer base to make sure that I can then propagate through the appropriate offer or the right experience, or make this flow dynamic to make sure that there's appropriate throughput, and then also a reduction of fields that they need to then fill out and make sure that it's really a product-based decision flow.

(15:11):
So using AI to pull information from disparate points of different data sets to then drive intelligence to get a different outcome is how we're applying it in all aspects of our business. And it's not just about in the call center, but it's also about how you can then use the tools to get revenue faster into your four walls. So I think as we then further apply it, it'll be really interesting to see the various different applications. And ultimately, I at least personally think that those with the data is really where it's going to be quite powerful in the application of AI and the data really sits with the banks, which is why it's so important and powerful to apply it to this particular industry relative to just being a technology provider in market.

Mary Ellen Egan (15:57):
Let's talk a little bit about fraud because obviously you're in a highly regulated industry—banking is a highly regulated industry. Fraud is, especially with how fast technology is moving, which is very scary, and then you're balancing that with customers wanting everything right away. So how do you juggle those things and what kind of safeguards are in place? Lauren, do you want to start?

Lauren Sullivan Bowes (16:18):
Sure. I would love to. So like I said earlier, we have these conversations every day. If you are detecting fraud at the point of where it's happening, you are too late. So what we are doing, what we are talking about, what we are living and breathing and really focusing on is the power of the Plaid network in that one and two Americans have used Plaid. We work very closely with large financial institutions. We work very closely with fintechs, technology companies, and startups. So because of the nature and the power of our network, if there is a user trying to come in, we have the data to be able to realize before all of these different things that they've done—they've opened up 17 bank accounts in the last five minutes, they were in Chicago 30 seconds ago, but now they're sitting overseas. So we are using that data to be able to stop it before it happens.

(17:15):
We also have amazing tools to be able to track the money. So things happen, but in order to catch these fraudsters, you have to be able to follow the money and follow the chain. So we have a unique ability to do that, which has been really amazing. So we've doubled down in this space, I would say in the past two years. As a salesperson five years ago, I got to talk to all the directors of innovation and all the user experience people. Now it's fraud. So now every day, those are the people that we're having the conversations with because it's critically important. We are using AI to fight fire with fire and yeah, happy to talk to anybody about it at any time. It's something that we're really proud of and something that we're dealing with every single day.

Carolyn Booth (17:59):
Yeah, sure. And you're absolutely right. The speed with which all this is happening—the velocity is just mind boggling. And what we see is the minute we put too much friction in the system and you overswing, I mean, you just see volumes deteriorate immediately. So striking that right balance between prevention—and getting preemptive fraud detection—is really critically important. And I think if you're not one of the G-SIB banks, it's also a reliance on consortium data and partnerships that help to bring you those expertise because you do need to be able to identify that individual fraud incident, but also the more systemic portfolio risks that you were talking about. I think too, again, going back to the consumers, I think about fraud like AI: it brings a whole new type of fraud. Someone had brought up hallucinations, deep fakes, voice biometrics don't work the same way that they did before.

(19:05):
So getting ahead of all of those emerging risks is so critically important for banks and getting the right advice on that. And I see as a bank, we also have a social responsibility to make sure our consumers understand the risks that they're taking, whether it's with us or elsewhere. So we talk a lot about what is our social responsibility to protect consumers.

Katie Whalen (19:33):
Great. And I think Lauren said it perfectly: it really is grounded on the network. Fraud is one of those areas, as well as cyber, that is so important for the industry to really come together and make sure that there's an appropriate data share to collectively fight against the trends and then have predictive trends based off of the collective whole as opposed to the individual players in the market. And so it's something we've also done across our business in terms of bringing together how we sit across the different banking platforms as well as merchant platforms to establish that network and then build off of that collective knowledge base to have the predictive models that can be applied in the actual strategies of the toolsets themselves. I would just punt off of what Carolyn had mentioned here though about educating the customer base about what fraud is and how to be best positioned to fight against it as an individual, but also in the collective whole.

(20:32):
And this applies to both consumers, but especially for businesses. We operate and have millions of small businesses and medium-sized businesses in our portfolio, and they oftentimes trip over themselves in trying to prevent something, or the tools that they're adopting, or not really knowing what to do or how to navigate it. And so we have a new program we're starting with regards to cyber consulting for medium-sized businesses just to prevent against ransom attacks or whatnot. But I recently had an example of a medium-sized business out of California. They're an herbal supplement company that's an online company, but did sizable volume with us. And they just got into a pickle that was their own doing where they changed strategies and then adjusted how they were using their gateway. And what had happened was it then flowed through the system—red flags that they were inadvertently doing that they were doing to themselves.

(21:34):
But what happened was it flowed through as the merchant and then got into the network of issuers on the other side of the transaction. And then they were then flagged on all the issuer strategies, not just with the large banks, but also the small credit unions and were getting a crazy amount of declines because they had made some adjustments to the strategies in their gateway system. And it was just such an example of trip ups. We untangled what had happened, and then you need... It's almost like when you have to fix something like that, you have to almost go to PT. It's not an immediate fix, but you have to take a few months to do corrective action through the system. And we were working with them to do this and their level of frustration was so crazy.

(22:17):
But again, it's an example of how do you make sure that you're helping your customer base help themselves in the process, but then also acknowledge that as a collective whole, how do we help those smaller players at the different endpoints to make sure they don't get in trouble in the collective system?

Mary Ellen Egan (22:38):
Let's talk a little bit about the future. So where do we think the industry is heading and what are banks' unique advantage in this environment? Carolyn, you want to start?

Carolyn Booth (22:48):
Sure. Okay. I was going to just add on to Katie's comment. I mean, it's a great example of human-in-the-loop, because as much as all of this technology enables and helps with fraud prevention, when something does go wrong, I think all consumers, all businesses are still going to want to come back to that human for help and support in untangling the situation. So looking forward, to me, this is a really interesting one. When you think about the amount of information that is available today, the amount of information that is coming at consumers—AI, technology, all of this is just enabling us to saturate customers and consumers with too much information. And so I think there is this era of resonance where we're really going to have to be thoughtful around—it's not the quantity of outreach, it's not the quantity of communication with clients that will matter.

(23:56):
It's really going to be the relevance and how do you, as a provider of financial services, a bank or otherwise, differentiate yourself on that point of relevance? So using AI, using all these capabilities really effectively to drive true personalization—and it's got to go beyond what is the next best product because that's part of this inundation of information. How do you get to that place of really differentiating with a client and being heard and seen differently than others?

Lauren Sullivan Bowes (24:33):
Yeah. And I think it's changing every day. I heard Carolyn before us talking about how she still pays the piano teacher with a check; that made me giggle. I still write checks sometimes and I do a horrible job. I mess them up quite frequently. And we were looking at a study the other day actually, and it was saying like 66% of Americans, if you're not giving them the digital experience that they want and need, they will switch banks. My husband lives in Boston—he's a very Irish, Catholic, loyal person—is an attorney that drives his paychecks or mails them to his credit union in Dorchester that we live 40 minutes away in traffic and that's how he wants to bank and that's what he's going to do. Fine, right? But I'm like, I'm keeping my top-five bank account where it is. I demand a digital experience.

(25:26):
He does not. That's okay because I have the tools to be able to work with that credit union, work with my big bank. Our children, I'm guessing, are not going to use that credit union unless it's going to deliver them the digital experience that they demand. They're going to be on their phones, unfortunately. I wish that they weren't. That is how they want to bank. They do not want to talk to humans. So everybody is evolving. There's no question anymore; this is happening. So we are seeing banks big and small really try to figure this out and get on board. At the same time, I do believe that people are going to want that personalization. They're going to want to talk to people. And I think we all have to work together to figure out what's that balance and what's that mix and how much do you invest in each area to be able to continue to meet people where they are?

Katie Whalen (26:17):
Lauren, I'm going to count on you. I know they don't want to talk to humans, but they'll want to talk to a human when something is wrong. When something goes wrong. So it's like, okay, great. Don't talk to me until I actually need you. "Operator, operator." Yeah, exactly. And I think that's where the... I love the example you have about your husband driving to Dorchester because that's amazing. But I think it goes to show the value of trust when you're managing someone's financial accounts and security is still so paramount to the consumer base for both ensuring that there's security behind it, ensuring that there's that human contact that you can still have or somebody standing behind the digital interface that you're interacting with that can help you when something goes wrong. Establishing that fluidity between the digital environment and the branch network or the human touch is still so important.

(27:15):
And probably even more so for our industry relative to other consumer spaces to ensure that there's that clear fluidity between those environments. And I still don't think we've really cracked it as an industry. I think there are some bigger players that are working to do so where there's a significant investment into customer service, not just the digital footprint, but that's going to be something that—it's not an either-or game. It's about how do you create that seamless omnichannel experience between the experiences and touch points that you have with your customer base?

Mary Ellen Egan (27:49):
I like what you... A couple of the speakers yesterday talked about how you're in the customer service business, which you really are. And I liked that, Carolyn, that you touched on social responsibility, because I mean, you're holding people's livelihoods and their lives in your hands, and it's really important. And also, so how do you keep that with keeping with real time, keep that personalization going? I love that your husband drives the credit union deposit check.

Carolyn Booth (28:16):
I hope he doesn't ever see this. I'm the one who puts the check in the mailbox two minutes before the mail truck comes, because I'm afraid it's going to get stolen, right? I'm far more confident in the digital.

Mary Ellen Egan (28:29):
So, but how do you do that? Because I think when you hear from somebody, usually, especially if you're in the customer service center or whatever else, they're not happy when you hear from them personally, and obviously you don't want it to get there, but how do we keep this immediacy going, but also not lose the personal touch?

Carolyn Booth (28:48):
Yeah. I think one of the speakers spoke this morning, ways in which we're using AI for our frontline employees, particularly whether it's in a contact center or in the physical branches, is how do we serve up the answers to them more quickly? So using chatbots and AI tools to be able to help them navigate, particularly—usually when a client comes in with a problem, it's complex. They have not been able to solve it through a self-serve channel. And so being able to make sure that we can help them navigate quickly through the ecosystem to find the answers, and if they can't find it, then they're no longer waiting 40 minutes to speak to an internal contact person in our operations group. It's a much shorter queue now because we're getting, even within the organization, people self-serving in terms of finding the right answers.

Lauren Sullivan Bowes (29:42):
Yeah, I think that's right. I was actually yesterday in a meeting with a top five FI and we were talking a lot about customer service in the call center and how hard it is and the cost to maintain it and how do we make it better. So we're looking at what are the number one complaints or problems that people were coming in with. And a huge one is people thinking this is fraud—they don't recognize this transaction. I'm kind of guilty of this sometimes. I'm looking at the bank statement, I'm like, "I don't know what that was." And they're calling in. Come to find out, "Oh yeah, actually I know what that was. That was me or that was my husband." So we're working really hard to develop products that help end users really understand: what is this transaction? Enhancing transactions, making them easier to read.

(30:32):
And that has dropped significantly in the incoming calls. I think the other big piece is identity verification now. So we're talking about fraud, right? So people put in really stringent controls online, which makes sense, but they have a process there where if you get flagged, you need to take your ID and go into a branch. So great from a fraud perspective. For an end user customer experience perspective, that's really difficult.

(30:58):
But some people, we could say like, "Yeah, use Plaid. Here's this link, log in." They're not going to do that. If they're speaking to somebody and that person has tools to be able to say, "Hey, you could walk into this branch. I can also send you this secure link or this secure email that you're comfortable with and we can verify your identity that way." That's another huge use case and something we've been talking about a lot. It's all about reducing the number of calls so that you can better serve the people that actually really need you. So that's really common. We're talking about it every day.

Katie Whalen (31:32):
I think just summing on that point, Lauren, we talked earlier about the application of AI and AI is so powerful when you actually apply it to disparate data points or different points of data that you might have. And that can apply to the various different touch points or interactions that you as the bank have in the external ecosystem outside your call center. And that could be how somebody logged in, what actually happened with their card, and looking at the trend of touch points that may have existed that leads to that phone call. So that the phone call doesn't start on touchpoint zero. It's starting with all the disparate data points and information that you have about what that person did or interacted in the environment outside of that phone call. And ultimately, I mean, we at Fiserv have this—at least in our small merchant space—have this in our customer service spaces like level one and then level two.

(32:30):
There really shouldn't be level one. There shouldn't be the level one customer service rep being like, "Okay, let me try and figure out your problem first and then I'll route it to somebody else to then solve that problem." We should already have the touch points or the information points to then feed into the appropriate team that's going to then resolve that specific problem so that if you're a merchant and you're closing your books at night and you're not getting your settlement come through and you can't close the books, that shouldn't happen at two in the morning and then you have to wait another 24 hours for somebody to solve your problem. So those are the things that we're really evaluating: how do we pull the disparate data sets to then feed into a more seamless experience? And I think that goes back to establishing that fluidity between an external environment or digital environment or however they're interacting with your card swipe or using a terminal or whatever it is, feeding into that servicing experience so it's informed and can be triaged quickly.

Mary Ellen Egan (33:29):
We have a few minutes for questions. Does anyone have a question? Oh, over there, Mason. Thanks.

Audience Member 1 (33:41):
Hi. So my question is kind of the other side of the coin maybe of customer expectations. And so with all this data that the banks and financial institutions have, I think sometimes customers' expectations can be almost to save them from themselves in some ways and that the bank is somehow an insurer of their funds or in certain situations a fiduciary where they may not be in a deposit relationship or something like that. And so they'll say, "You have all this data. You should have known this was fraud. You should have known that this was a scam. You should have known this and now I want you to reimburse me." So how do you balance that where we have all this data, but yet customer education is a huge part of it, but how do you manage their expectations that you're supposed to be their insurer of last resort when they've been scammed or defrauded in some way?

Carolyn Booth (34:44):
Sure. So that is a question I think every bank and every organization thinks about. And I know the way we think about it is we have a very heightened sense of responsibility and accountability to make sure we are doing everything we can with the data we have to detect those patterns that at the individual level look unusual so that we can try to have a moment of intervention. Where it becomes really difficult is when you have these kind of instant irrevocable payment situations where all the disclosures in the world don't always protect the client. And so that's where I come back to the accountability and the responsibility. I know our frontline employees work relentlessly with clients when they see something that is obviously a scam happening. And we have a lot of processes, both automated and otherwise, that happen around those kind of situations. But it is like the great dilemma, I think.

(35:55):
Clients and consumers do want to be protected from themselves. They want to have the ability to use all these digital channels and the conveniences, and they want us to protect them. And those two at times are still in conflict. But hopefully as we look to the future and get even better at some of that fraud detection, those instances will diminish.

Lauren Sullivan Bowes (36:19):
Yeah. I think you raised a really important point. And I don't know a bank or financial institution that's not struggling with this right now. It's a center of a lot of conversations. And I think the conversations that we're having is: yes, you have all of this data. What do you do with it now? How can you get smarter with it to actually help that consumer? It's difficult. There's no easy fix. We're constantly developing products to be able to help banks and financial institutions do that because we're hearing this over and over again. And the other piece is, if you have information from one bank or financial institution where somebody banks, great, but they might work with six. So again, the power of the network is being able to actually use that data from several different places and bring it together to try to prevent it.

(37:07):
I don't think anybody's doing it perfectly right now.

Katie Whalen (37:10):
I think you're spot on. And I think one of the reasons why the industry as a whole is struggling with it is that the industry's built on mainframe technology and I think every single one of you that works at a bank probably is under some tech transformation that's been going on for 15 years. But I think that the end goal of any tech transformation exercise—and even Fiserv's growing through years of acquisitions—and our focus right now, at least internally, and I know this is the case with a number of banks, is getting to a place where you have a data repository that's a relational data set where you can pipe in the data into a place that you can action it off of some sort of event-driven architecture, if you will. And that is going to take time, but that's what is needed from an infrastructure standpoint in order to get to the solve and talking to the individual in the moment.

(38:07):
And whether it's a conversation in the branch that somebody's walked in that you can see that information or getting to a place where there's a very clear communication strategy where it's a notification to their phone or an email or a phone call based on the severity of the incident that occurred or the trend of the data you're seeing on that account. The unfortunate truth is that today a lot of that data sits in various different places that aren't connected and that's really the crux of being able to get to a place where you can then take an action off of it. And in the interim, one of the things we worked very closely with a lot of our bank partners on is developing and investing in a communication strategy that is sound and isn't overly bothersome for the consumer, but also is acting off of the right set of data sets and isn't spamming.

(38:56):
And I think those two things are probably the most critical to get to a place where we do further the industry to achieve and answer the question for the person standing in the branch that you just talked about. So that's at least where I see some of the biggest barriers to being able to achieve that response.

Mary Ellen Egan (39:14):
We're out of time, unfortunately. I want to tell you that there will be a quick half-hour break following this discussion. I want to thank Carolyn, Lauren, and Katie; I think it was really informative. I'm sure that they'll be happy to answer some questions you have afterwards. And thank you so much. Thank you.