Optimize Loan Notice Management with Xceptor

Transcript

We're really excited to talk about, this particular use case, loan notice processing, because it's become super popular over the last year and we've actually implemented it a number of times with fund admins, banks and and asset managers. So we're really familiar with it and, and it means we can bring our expertise to the problem and I am happy to step you through a bit of a, a demonstration of, of that process.

First, just to set the scene. So in 2024, the syndicated loans market grew by 1.2 trillion. So the, the, the, the private credit market keeps growing. Bank lending made a little bit of a comeback last year, but we're still seeing a lot of growth in in private credit. And what that means is for our customers, whether you're a fund admin, a bank with a lending department or you're an asset manager, it's really likely that the number of loan agent notices that you receive, you know, on a daily basis, but also, you know, at the end of the quarter has gone up.

And it can be very, very hard to deal with that those that that that level of processing or that volume. The documents are very variable. They can be very complex.

So they have multiple transactions within them, and you know the the two options for processing really are to to manually process them in-house or outsource it. And as those volumes go up, it becomes more and more expensive to do that. So really good that Xceptor’s able to to provide an automated solution here. So I'll walk you through the the steps in that automated solution.

So first of all, agent loan notices come in from either the agent of the syndicate or directly from borrower occasionally and they are semi structured or unstructured either in the body of the e-mail or or an attachment to as a as a PDF. And you have multiple transactions broken down within those notices.

There could be between 1-16 different transactions in there depending on what's happening with the loan. It could be rolling over, could be paying down a chunk of it, and so on and so forth.

So Xceptor constantly monitors that mailbox so you don't have to. And when it sees that an e-mail is dropped in there, it'll actually pick it up and identify it, figure out what transactions are in there, and then extract them as individual payloads that are ultimately connected together. Then the real hard work starts.

So all of those different transactions require a lot of data treatment, you know, a lot of data cleansing, but also applying those kind of loan accounting rules to to those transactions, matching that back using a look up to the Security Master or or in this case, you know, to your your lending system to to validate, you know, things like the currency, etcetera.

But then actually creating those activities that have to happen, those payloads that have to be posted to the downstream system in order to update your accounting records of the the changes to the loan.

At any point if any of those rules fail or if there's interaction needed from a human, we're able to surface that through the user interface of Xceptor. So you can action it really quickly, but in a controlled environment. And this is just to say then that we, we push that data all the way from the e-mail to the end system in a truly digital state, which, which really get allows you to kind of capture that value.

So I'll dive into a quick demonstration here. So this is the home screen of Xceptor.

Someone has multiple processes set up here in Xceptor, which, which is, is quite a familiar way to approach Xceptor. And you can see if the process was to remain as is, humans would have to dive into the mailbox. They'd have to open the PDF, highly complicated set of instructions in there and in some cases completely unstructured data. So that all goes away.

Human no longer, or the operations analyst, no longer has to spend time looking at those e-mail boxes. Instead, they can come into the Xceptor dashboard and the dashboard gives you your kind of landing page, your day in the life, like it tells you what's important for the day.

And you can see I've organized my dashboard there to show me what was already processed today and and also what was requiring review. This is one of those items that had already been processed.

So on the left, we get the document, on the right, we get all the data that's been extracted from the document. It tells us a little bit of a story here. We can see we've got an interest payment, a principal amount has been paid off and therefore we have a resulting new contract. That's all really important information and we can see we've got a good level of control or certainty about that.

We're also here breaking down the actions that then need to be carried out to the end system. And see, we've got that relatively complicated set of steps that have to be carried out over API to the downstream system, to be able to get all the way from e-mail to the system.

Finally, you know, we've got another example here. This is the one that was held up. This one needed review from a human being because the effective date couldn't be read.

But of course, now someone can come in, they can carry out that task, they can hit Go that'll rerun all of those business rules.

And very quickly, we'll be able to push this document or this set of transactions through to that downstream system, taking that process from something that would have taken a couple of hours to something that can be handled in just a a couple of minutes.

Really, really powerful.So just ending here with a couple of configuration screens.

You know what we always like to call out with Xceptor is that what's important is that you own the config and it's something that can be configured through the user interface by someone who's not technical, even doing things like applying controlled AI to the digitization or mastering those business rules.

Really, really important that you can react quickly to changes in your environment through configuration here.