Alogent Webinar: Simplify and Streamline your Deposit Channels: Gain Measurable Efficiency Gains and Cost Savings

Hi. Good morning. Good afternoon to all that are joining us, from around the country today. We have a really good turnout. I appreciate everybody signing on to to spend a few minutes with us and the Allogen team about simplifying, our modern deposit solutions that we have out there and and how to how to approach the the the strategies that are being presented to us in the market today related to deposit activity and and how to automate, many of that with with tools that Allergan has. For those of you who don't know, I'm Allergan's, chief strategy officer Jason Schwabwein. I appreciate, again, the time you're taking with us, today to go over our our list of solutions and other together. We will hope it's highly interactive, which very short period of time today, thirty minutes. So in and out with good data and showing you some product. So with that said, I'm happy to turn it over to the two gents that are actually helping this with me today. It's Mark Bixle, our VP of sales engineering, as well as Alfred Givens, our principal product manager in the payments arena. So, Mark and Alfred, take it away. Yeah. Thank you, Jason. And good afternoon, everybody. My colleague and I, Alfred, are gonna take you through a journey on how to simplify and modernize, your deposits including your back office today. If you have any questions, please put that in the chat and we'll address those, towards the end of the session today. Alright. Listed here are some financial institution goals that we hear commonly, from our customers, whether we're meeting with them at their office, we hear this type of topics at trade shows and webinars, etcetera. But most financial institutions set these goals, without really a plan to get there. And I'm gonna ask Alfred. Alfred, what are your thoughts on how an FI can accomplish each one of these? Yeah. And and good afternoon, everyone. So, Mark, I think one of the things is I mean, obviously, lower cost comes first. Right? And as well as and and we we take all these into consideration. They are all they're all, you know, important. And I'm gonna plagiarize something that, Jason, did a, he did a he provided some information not too long ago in a blog. And the main thing around this is that with we know how the the with the current market conditions. And, you know, combined with, you know, agent technology that that that that we all know and and work with, it drives up the process the processing cost of of of items. So determining a strategy that keeps the overhead down as much as possible as and at the same time, keeping efficiencies up or making sure that the efficiencies in processing the items are is is as high as possible is critical for for every FI. Finxtra did a survey not too long ago, in July. And one of the things that it ranks reducing processing cost through payments modernization as much as seventy nine percent, which is which is huge. Right? So Yes. In terms of increasing, deposit consistency, I mean, Unify that we're gonna be talking about today provides a common solution across all deposit channels, a very, you know, vague statement for the, you know, for the most part, but we can dive deeper into that as well as reducing risk. We had our conference, earlier early last month or early October. And one of the big things that came out of that was everyone was interested in real time validation. Everyone was interested in fraud. So those are the things that we want to bring to the table. Our we know that Unify brings to the table and that we want to talk about today. Yeah. And, also, Alfred, real time posting as well. Right? And real time posting. That is correct, Segment. Yes. K. As it relates to check volumes, right, we've heard of check volumes decreasing. But one of the things one of the critical pieces of information that we haven't that we probably aren't honing honing on is the fact that checks is still a payment method that remains an integral part of the payment ecosystem. Where the volume of check may be decreasing, the value of the checks are increasing because they're being used for larger transactions such as such as paying earnest money to or down payment on a car. It's also good for record keeping. It's it's, checks form as an, more like an instant receipt. You know you know who the date when you made the check payment. You can know who it was written to and and the amount. Right? So it it forms as a, hey. This is my receipt, for the payment that I made. It's also more secure. Check is is more secure than debit or credit card transaction, for example. It requires a signature on the check on the item, which is harder to which makes it harder to forward. I'm not saying it it it cannot be forced, but it makes it harder. And one thing I I've I've heard in the news lately is that and and I'm sure we're we're all dealing with bankers here, is, you know, when we are talking to our customers not to put large dollar checks in their mail, take it to the USPS office location and put it, you know, put it in a bin inside. But it all forms part of, you know, we're we're we're addressing this as a community, and we're taking everything into consideration as we talk through, you know, the rise the the decline in check volumes. But the cost of the checks or the value of the checks are obviously increasing. And the last point I wanna make on this is, obviously, there's no fees for making a check payment as opposed to other forms of payments that we have there out there in the market. Yep. All good points, Alfred. Yep. As it relates to data inconsistencies, there are inherent issues associated with that, not being able to support your reporting needs. Am I getting the data when I need it, and am I getting the date the the it's in the right form? Is the data really just data, or am I transforming it to information? What we see is that when data is inconsistent, processes become more siloed. So there's there's no consistent behavior or outcome as it flows through the system, which, you know, obviously leads to longer processing times, higher probability for errors, and misindicators that something may be wrong. For example, a fraud a fraud hit or to be able to detect fraud easily. And the idea with UNIFY here is to normalize the data as soon as possible so rules can be applied and the process flow from one module to the next, which includes metadata associated with each process and help to find anomalies easily and allow the financial institution to act accordingly. Yeah. And and, Alfred, that also helps with, historical research because we have good data and then also helps to determine future trends as well. Right? That is that is true. Yes. And and then now that again, you can you can trust the data. Right? Because, you've normalized it. It's it's more it's more consistent. It's flowing between departments and between entities, which which also helps to make sure that you you know, the data that you get or the information that you get from the data collected can be trusted. Yes. Yep. All good points. Alright. Alfred, what about stakeholders' needs and questions? That's that's the big piece. Right? Different areas of the organization and and different touch points. They need data in different forms, and they need it at different times as well. Right? If you look at customers, customers in my mind normally drives, the objectives for, you know, wanting information readily. Right? The financial institution may may want to know, you know, for example, that we have there is, you know, how do I monetize my data? And and and I think the biggest part is too not just to monetize the data. You monetize it by making it usable and making it transforming it to information. The back office needs to needs this information as well because, you know, I need information to be able to make decisions on items that are being processed in this in the in you know, throughout the ecosystem of the of the FI infrastructure. I wanna I want to reduce time spent on deployment of the system. I want to I wanna be able to, scale easily when volumes rise or volume falls. Right? And I wanna be able to make sure that every single point of contact with the data and as it moves from one place to the next, that it is secure. The business unit, wants a mechanism to increase deposits. You know? You want more customers. You wanna be able to have, to be able to collect more data as we go through the system. And in increasing deposit means that I'm increasing my footprint, as an organization. So reducing friction and risk is is utmost importance. And then like we said, it comes back to the customer who drives most of the need for this information because they are the ones who are the users of the systems and are the the the the the touch point into the organization itself. Yeah. Exactly, Alfred. So so how do we get there? Right? By having a single flexible API that supports all transaction types, we can be consistent of acquiring all these deposits regardless of the channel. Right? Whether it's a simple transaction, whether it's a complex transaction. But realistically, having a single API ensures consistency across the entire enterprise. Alright? Yes. Yes. That's that's that's correct. Yep. Yeah. And and as we continue here, you know, we just learned that Unify has a single API that allows you to have a, consistent deposit experience. But, Alfred, why don't we drill down into Unify a little bit more and and provide some more information? So other than the single API, what else should should they know about Unify? Well, there's also the ability to to to detect anomalies. Right? So we talk about and you mentioned real time. Right? Real time, in line data and image validations are performed during the deposit process. And it doesn't it regardless of the channel, right, whether you're getting an x nine or you're capturing an item from a scanner or a mobile device, we can, we can, you know, take those items or based on the piece of data that we collect, we're sending it through different points of validation to ensure that the item is fit for processing or it's it's negotiable. Right? So it's it's item and transaction centric solution. So there's no batch or jobs associated with this. So I use the example all the time. You're not you have a a transaction that's a a million dollars or has a million dollar item in it, and there's an item for one dollar that's holding up the whole the whole process. Right? Here, with this with this item or transaction centric process, that will no longer be an issue because as soon as an item goes through the system, it's it's recognized. It's negotiable in terms of the business rules I set up. That items flows through and is available for other downstream processes. The other thing too is that, you know, lot of the inefficiencies that we spoke about before, the data inconsistencies and so on and so forth, Allergan, you know, Unify addresses those, right, which obviously reduces, cost and also risk, which is at the forefront of everything. How do I reduce my risk? Because the longer it takes for you to process an item or find an issue with an item, the more costly it is to process that item. Yeah. So, Alfred, our industry, basically, we've always been reactive in everything we've done. Right? Now that we have the scoring models already unified, talk about how we're being proactive in trying to get out ahead of fraud and and some of the the, abnormal behavior around deposits. Yeah. I and I can use an example for that. Right? So the scoring model that's inherent to the archive solution as as part of our archive solution allows us to collect data about, activities, whether it's a deposit activity or check you know, check being drawn on your account. So I always say that the fraudsters are intelligent people. Right? They know what's going on. They know the industry. Right? So think of, you know, RT, being able to calculate the RT validation, the check digit routine on an item. Think about, oh, I need to remain all my transactions need to be less than a certain dollar amount because then, you know, FIs normally don't look at those as being, you know, critical. They look at large dollar items. So our fraud model or the this customer score allows us to collect this data on deposits as well as items presented and are able to detect anomalies, weather frequency. I have customer who's depositing two hundred dollar items or two hundred making two hundred dollar deposits, but it's it's it's doing it at a more frequent basis more than the average that they would normally do it on. As well as I have this customer who's they're getting they're used to getting, their average amount that's normally drawn on their accounts is three hundred dollars. But, you know, suddenly, we see a spike in the amounts being, you know, five hundred or upwards. So it's a different amount. We flag those automatically and present it to the user, the FI for them to review those. So the scoring model is is really meant to it's collecting the data as we mentioned. It's processing the data, and then it's acting on new deposits or new items that are presented, as part of the processing system. Yeah. And, also, Alfred, the scoring model can help accelerate those deposits through the system based on a high enough score that can bypass review. Right? That is correct. I can you can use the scoring model. So based on the user's, or the depositor score so we keep a score for every depositor. So depending on the deposit score, for example, you can use that as a means of making an automated decision. Say, for example, their daily limit is ten thousand dollars. They they're making a deposit for ten thousand five hundred dollars. We can use the scoring model to help to make that decision, to automatically approve that this the, that check as a part as opposed to send it to review or or rejecting that item upfront. Excellent. Yeah. Alright. Alfred, in your past lifetime, you were a back office ops guy. So what about the back office here? Yeah. So, this is something that, you know, takes me back to when I started, because my career started in back office. And I know how it feels. Right? Because the back office was seen as an era where, alright, nobody goes there if you're not you're not supposed to be there. Right? And it was it was almost like a black box, but it's it's a very integral part of the of the organization. This is where everything happens. It's, as it says, the rubber meet the road. All your day one, day two process are done. Right? All your validations are done there. There. All your item protection, is done at in the back office. So, you know, we don't want to, we don't want to forget or we don't want to we wanna make sure that whatever, solutions that we come up with, the back office is an integral part of that. Because if we don't take care of the back office, we can't take care of the finance institution because then, you know, that's where, you know, we talk about fraud. That's where that happens. That's where issues occur. That's where missed missed detection, you know, of anomalies occurs. So, everything that that we're doing, we're making sure that the back office is essential to those processes and make sure that back office has the information it needs to complete the processing transactions for the EFI. Yep. All good points. So it comes to the unified at a glance. Right? As it relates to as we we we we've we've hopefully, I've I've kinda touched on it. But from the you know, you go from the different inputs, or what I call the channels, whether it's back counter, teller, image ATM, mobile commercial deposit, or you're getting a new clearing file from a partner or from the Federal Reserve, you know, it goes through the, the there is the capture layer or the the processing layer where every single item goes through a certain set of rules. And those rules can be set up by channel. It can be a consistent set of rules, for each channel, to verify the RT, to verify the account number, to take it through, you know, different fraud modules, to verify that the check is is is negotiable. And then once that is complete, it there's a dashboard or there's a a presentation layer or UI that helps you to manage the system. So whether you're, you know, I'm gonna say, whether you're a back office or you're a manager or you're the CEO, looking at the dashboard gives you an overall view of everything that's happening in the system at that point in time. And then anything that is that that that fails any of the rules is, like we mentioned, you know, fraud or any other business rules that is configured. The item is taken through a review process where the FI users have the ability to to, you know, make decisions on those, whether to accept them or to reject the item. And then it comes balancing on reports, as well as, you know, the returns process. Right? One of the things that Unify does is that it's, it the processes that is inherent with the system allows you to do, you know, returns and chargebacks. So when I say returns, I mean outgoing returns as well as chargebacks within the same processing day. So it's it's it's blurring the lines between day one and day two, which also helps you to accelerate the the negotiability of the item and to validate that, you're you're reducing your risk as you go through the process. And then there's archive and business intelligence with which which, again, as we talked about, the the customer scoring model helps you to make decisions upfront and collect information to be able to do that on the fly. Yeah. Alfred, when we get into the, into the demo portion of the meeting, I'll be able to represent and show that how everything is on one screen and, as you said, blurring the lines from day one and day two. Yep. Alright. So, basically, we've got all this data. Right? And we have different types of associates that work at NFI. And, basically, by being able to consolidate all the data and validate all the data, and correct it, we're able to have a meaningful reporting. A reporting could be from the dashboard, like a visualization that you see here. It could be a search. Obviously, it could be a report as well. But transforming data in in into information is powerful. And now day that data now can become personal to that associate's role as each one of these folks has something that does a different role within the the within the financial institution. The reports, the visualizations that will sit they see will be personal, to them. And that being said, let's go ahead and move in into, the demonstration piece of of the webinar today. And I'm gonna go ahead and log in to the, into the Unify portal. Okay? And, you know, again, Unify is a single system, so we're seeing all of our deposit capture. We're seeing all of our day one day one image exchange. We're seeing all of all of returns processing. We have a bunch of widgets here that represent certain areas where an associate may need to do things. These are all configurable, you know, based on size and location and things like that. But I'm just gonna leave these here. But you can see, you know, we have our inputs here. We have our workstation processes here. We also have our outputs, down here, in a purple color. This is, you know, again, a very high view. As I drill down, if I'm in charge of of processing for the current day, here I have all my inputs. Right? I have my captured channel points, you know, ATM through tele capture. I also have in clearing files. I could have return files here as well. But as we drill down, the screen is designed to be very simple. You know, if I were to go ahead and click on local clearing house, you can see that, I have the name of the file. I also have the item count, dollar amount, and what time it came in. Okay? From an output perspective, we wanna automate everything directly through the system. So we have multiple ways, to go ahead and get these outputs. Here, everything can be scheduled based on an item threshold, a dollar amount, and even time schedule and interval schedule. Right? Cash letters, people mostly do, at the end of the day. Some do it throughout the day. Very easy, and configurable. Alright? Again, as I mentioned, every module within Unify is driven from this dashboard. If I were to go ahead and click on, co line correction, I get the screen that pops up. This is all browser based. It's browser agnostic. Right? The user can be challenged to be logged in. I am already in I had already logged in. But as you can see here, we have the image. We have our, correction message. We have our point of capture or where the file came from. Very easy screen, to use. Now if you're not directly on that screen and you wanna go ahead and set up bookmarks like I have up here to moving to to move into the balancing module where I may need to do some type of deposit adjustment, We'll go ahead and move into that. Right? And I'll go ahead and pick my deposit. And at this point, again, similar look and feel. We have, you know, the channel that it came in. We have the issues with the the items here. As you can see here, we have a duplicate. I also have a fraud. So in this case, right, we've made a real time web service call, out to a third party, service. Right? We have a closed account. We'll go ahead and and reject that. I now we also have a duplicate here. I double click on it. We're gonna present the image back. We're gonna do duplicate detection up to a hundred and eighty days. So, again, we're really, automating this and and running through this. Right? Now the last thing I would have to do with this deposit is go ahead and adjust it. And at this point, what I'm gonna do is just go ahead and do a deposit adjustment for the items that I rejected. At this point, I'll insert the adjustment here. And once I go ahead and hit commit, I go to the core, and I post this deposit. Fast, simple, and easy. You can pick by workflow, that's, basically in the queue here, and and go from there based on whatever parameters or business rules, that need to be configured within within the system. From a research perspective, I will go into AWARE, which is the archive, that is, with UNIFY. It does, a hundred and eighty days duplicate detection. It's where the scoring model is. All that data's in there. And, really, there's four ways to represent the data that's in a system. Right? We can have visualizations that we're gonna have up here that's popping up here. We can run reports. We can output into Excel or CSV. And we also have our regular PDF reports if if need be. Right? But how that data is, it's all in the system. And as Alfred talked about the metadata that's that's being captured, we do store about sixty pieces of data around each item. We know the source. We know the depositor. We know who fixed it, within, within the back office. We know the time it went to posting. We know if it went on a cash letter. We have all this data we're storing off. In the event that I needed to do a search here, and we'll just do a quick search in here in a second. And I'm just gonna go ahead and choose my my current business day, and I'm gonna go ahead and look for a check for fifty thousand dollars. And at this point, right, I'm on my current day. I have fifty thousand dollar check. I've been able to find it. Right? And here's some of the metadata that Alfred mentioned and and that we spoke about. Right? We know this came in through the remote deposit channel. We know it as a mobile deposit. We also have some extended data here. Right? Did it go through deposit review? Did it go through fraud review? Did it go through pay name verification review? Right? Not a suspect and then not required. Right? So we have all this data around the item. In the event that I wanted to see the virtual deposit ticket, I can basically pull that up. And then if for any example, I needed to provide this a copy internally or externally, I do have the ability to quickly create a PDF report with this. Alright? So quick and easy. Obviously, this is role based, within the system itself. And the last thing I wanted to basically show was, I know we spoke briefly about the the scoring model. Right? And that is the ability to try to figure out and anticipate is the is the customer or a member transacting, in a normal fashion. Right? We've created this dashboard that is that that's actually really good from a summary perspective. I can see over a certain date range. I can go by channel, like, maybe I care more about my ATM than my mobile. But, basically, between the fifteen tests that it does and an import of data from the core around available available balances, age of the account, and also number of NSFs, we can create a really we can create a score that can actually be used and meaningful within the system. As Alfred said earlier, you know, to push that into review, or as I said, let's run it through get it through review in an automated fashion. If that depositor makes a deposit a hundred dollars over their limit, today, it's gonna stop. And and the user is gonna look at the the deposit, they're gonna look at the core, and they're gonna accept it. In this case, we have all that information depending how the parameters are set. That would automatically go through we we would market that the system actually, that the system actually forced review that, and we would know that. Every deposit would be stored, with that score then. Alright. We got a couple minutes left. Alfred, any you wanna take a couple questions here? Yeah. Sure. Sure, Mark. Of course. Yes. Yeah. So let me take the first one here, and I think we may just have time for one. Is Unify available for my financial institution? We only have five branches. So the the the good thing as we as we worked with architect or design in Unify is to make it available to all FIs. Right? CUCBs, large financial institutions, whether you're processing, you know, a hundred items a day or two million items a day. Right? It's it's it's scalable as well as it is architected to be able to address the needs of the FI and not just based on their volume, but just but based on what they're looking for in terms of, you know, like we said, addressing fraud, processing an item, making sure it's negotiable, and everything else. So the volume in this case as we relate to to and and the number of branches, I guess, with the number of branches would would would denote that it's a smaller volume FI, but the benefits to be, you know, derived from it in terms of what we offer from an item processing solution point of view holistically is is at the forefront of this regardless of the volume. Yeah. Excellent. Alright. One more question, Alfred. This is important because it's about fraud. Talk about the different fraud detection tools and processes that are within UNIFY today. So one of the things that you mentioned I mean, we brought up the customer score model, which is more internal, right, that we that we offer as part of the our archive solution. But we also integrate with other fraud, third parties to be able to detect items or to be able to look up items and validate them and present them to the user if anomalies or errors are returned as part of that. So any third party, fraud module, that supports an API web service call, we can support that. We also support one where we provide the files to the to the third party, and they process those files and use that as their, you know, the as their, knowledge base or as their their system of record to be able to do the lookup against a fraud module. So, and we also are working on one with one, third party where we can validate the RT. We've seen where, you know, like I mentioned before, users or fraudsters know what the the the what is going on in the payment payment Mhmm. World. Right? And what we're doing is we're working with an API, working with a cert party to to call an API to validate the RT even if it's you know, if it looks like it it seems like it fit it passes the, the mod check routine for the check digits. Excellent. Well, Alfred, we're at our end of our session today. We have a few more questions, which I think we will follow-up with, as part of our, process and through our marketing department. But I'm gonna turn it back to Jason and Alfred. I enjoyed today's session and this chat with you. Same to you. Same to you. Same to you. Thanks. Thanks, guys. I I appreciate it. I appreciate everybody who grabbed their time. It was nice to see that everybody stayed for the entire period. I appreciate it. This will be available on our website. As always, there's a preponderance of information available to you. If not, directly reach out to marketing. This is gonna be the first of many that we continue to talk about, the refinement around deposit activity, Unify, fraud, all of that, and how it plays together. So appreciate your time today. And, gents, appreciate what you did today. Take care, everybody. Have a safe, good day. Thank you, everybody. Thanks. Bye. Thanks.