Podcast: Rabobank, Santander Brazil see returns from Pega GenAI

Whitney McDonald 12:01:05
Whitney, good day and welcome to The Buzz a fin AI information podcast. My identify is Whitney McDonald, and I’m the editor of fin AI information. Fin AI information has rebranded from financial institution automation information, marking the following step in our mission to guide the dialog on innovation in monetary companies know-how. Becoming a member of me right now, December 16, 2025 is Steve Morgan, international banking business lead at Pegasystems. Steve is right here to debate how banks are utilizing generative AI, together with greatest makes use of of the know-how, and in addition the place Gen AI may not be the very best match. Thanks for becoming a member of us, Steve.Steve Morgan 12:01:36
Effectively, thanks Whitney, thanks for having me on. My identify is Steve Morgan. I’m pega methods, international banking business lead. And Pegasystems is a AI and workflow automation firm that’s been round for 40 years. Nice.

Whitney McDonald 12:01:49
Effectively, we’re going to speak right here concerning the rush of stepping into generative AI. It’s not essentially a shock that folk are desirous about Gen AI and monetary companies, however they clearly have to, they should weigh, you realize, the advantages and the dangers, pace to market and compliance, and typically that isn’t the case. Possibly you may form of discuss us by what you’ve seen within the house when it comes to balancing that, that need for competitors, but additionally the necessity to concentrate to compliance. Yeah, it’s

Steve Morgan 12:02:22
been, it’s been a very attention-grabbing journey the final couple of years as generative AI has change into mainstream, and yeah, for positive, I can present you, share with you, some shopper examples and what we’re seeing out there. I imply, what we did right away was take into consideration how, how and the place is the very best place to construct into our product. And once we thought of that, we thought of within the context of shoppers. I work within the banking sector and in the most typical focus for enchancment and utility of AI basically, AI and automation is kind of in broadly, kind of three huge classes. One’s round buyer engagement, one’s round buyer companies, after which operations extra broadly. And within the final two years, we’ve seen shoppers look to know the chances, the artwork of the potential experiment. Experiment internally, typically first after which do one thing exterior, shopper dealing with. And I believe what’s change into extra necessary, necessary attention-grabbing debate is, let’s take into consideration the enterprise end result first. Let’s take into consideration the correct of AI for the best use case, and the place we’d like AI, the place we the place we don’t want AI, the place we simply want one thing rule pushed or course of pushed to attain the automation and the shopper end result.

Whitney McDonald 12:03:34
Yeah, I believe that’s actually necessary, figuring out that want first, somewhat than working backwards and saying, You realize what we would like, AI, we would like to have the ability to, you realize, connect AI to the to the identify or the model, after which form of figuring out the place to place it later. Possibly we will discuss right here by what the dangers of doing that backwards method is what you may encounter.

Steve Morgan 12:03:56
So yeah, I believe with any huge program of change, and even small program of change, you should take into consideration, sure, as we stated, the end result first, after which the way you’re going to method the undertaking and the change administration. And if you happen to do this, and also you look finish to finish, to finish of the entire course of, you’ve obtained extra probability of success. What we now have discovered is in some organizations, there’s an actual need to experiment, take a look at issues out, attempt issues, and if that’s not executed within the context of the outcomes and the change administration, undertaking administration, you may get points, and it’s broadly identified, and in reality, there’s been virtually like new phrases created about hallucinations, battle, conflagrations, which is principally errors that generative AI could make, which is totally different, to say, statistical AI or machine studying, which may be very disciplined, can be taught and react and create predictions. So perhaps forgive you, an instance may deliver it to life with a shopper, how they’ve approached it, which I believe may be very sensibly so rabobanks, a good sized European shopper of ours, and so they checked out a vital use case internally, which helps clients handle monetary, financial crime and processes round that. Clearly, it’s a kind of like moments of fact for for a buyer, how nicely the financial institution offers with that? In order that they needed to see, firstly, how might they apply AI and automation to enhance the efficiency their workers who’re coping with the shopper, who’re fixing the problem, or attending to investigating it, attending to the underside of it, and so they used a mixture of our applied sciences and others to to actually enhance the information, the steerage, the teaching to their groups. They nonetheless had an individual doing doing the doing the work within the giant proportion of circumstances. However even when an individual was concerned, they’d the power to set off automations. The generative AI allow them to do conversational like chatting with the insurance policies, procedures, all the interior docs, after which they may set off a workflow automation into our methods that would get the work executed routinely. They did that internally, and so they truly talked to our convention this June, simply gone about going from hundreds of thousands of {dollars} of losses to 1000s of {dollars} of losses, which is good, good end result for the shopper and for the again. Financial institution, they then determined to take it to the following degree and have a look at exterior dealing with, buyer dealing with examples the place the know-how is absolutely uncovered, and so they, like many organizations, had quite a lot of totally different chat bots or clever digital assistants. And one good use case is plugging generative AI so it could change into extra conversational, extra entry higher data so to get a greater interplay with the shopper, and in addition then a greater, extra clear motion to finish for the shopper. They usually’ve been doing that with a few their their brokers and and I believe that’s an method we’re seeing most most banks take. Is have a look at some inside use circumstances, you realize, take a look at how what the end result may be. After which have a look at some exterior buyer dealing with use circumstances off the off the again of in some inside success.

Whitney McDonald 12:06:52
Yeah, that’s positively one thing that we now have been seeing and following as nicely. Utilizing these inside use circumstances first form of having the ability to apply and see the way it works inside, throughout the firm, earlier than deploying something on the Gen AI facet externally. Do you suppose coming into 2026 we’re going to see extra of these ahead dealing with, shopper dealing with, Gen AI functions?

Steve Morgan 12:07:16
Yeah, positively. We’re already seeing a number of. I imply, two weeks in the past, I used to be at one of many giant retail banks within the UK. They’ve obtained a software which does, does take some if you happen to’ve obtained any additional deposits in your account, it’ll sweep it and put them in a like greater curiosity saving or make investments them, if you wish to. They usually have been speaking about that software and saying it’s fairly primary. It’s fairly primary automation in the mean time, however they need the power to set off like a subsequent greatest motion for the shopper, and even set off probably both the shopper routinely decides, you realize what, there’s sufficient there. I need to make investments it out there, or put it in a time period deposit or one thing else, or I’d truly like to speak to somebody and get some wealth recommendation, some funding recommendation, and recommendation on my pension. So it’s taking a easy say, automation and making a bit extra superior. After which we had a shopper this 12 months, truly, Santander Brazil, and so they did. They talked as nicely at our convention in June, who took a very attention-grabbing case, a vital space as nicely for a financial institution of authorized operations. They usually needed to not solely enhance the interior operations of it, however for the shopper. You possibly can think about, with authorized circumstances, you realize, banks have to offer data to the shopper, to the choose, to the legal professionals, plus they’ve to make use of a bunch of legal professionals typically assessment paperwork, and nobody likes paying cash for legal professionals. In order that they checked out, how might they enhance that course of, each internally and the shopper dealing with side. And once they launched generative AI to it, they took what I believe is a really smart method round going, we’ll level it simply internally, at paperwork we all know are the right procedures, the right insurance policies, the right escalation paths, and we’ll see how good it may be. After they first did it, it was 67% correct, which isn’t adequate. Their greatest workers member doing it was 95% correct. In order that they skilled the mannequin with specialists in authorized and authorized operations space. They skilled over a interval of three months, and so they obtained it months, and so they obtained it to 98% correct, so higher than the very best particular person doing that function. And a few of that function was taught boring stuff, you realize, like 200 web page paperwork, extract the data, analyzing it. In order that they enabled some boring work to be made redundant. They redeployed folks into some extra attention-grabbing stuff, which is like, you realize, I’ve to speak to you, Whitney, the lawyer, or I’ve to speak to the shopper and provides them sure paperwork and stuff like that. And the very best results of all wasn’t eradicating the redundant work. Wasn’t eradicating the the steps that have been pointless or boring. The most effective outcome was for the shopper that the service ranges went to love 96 to 100% and the service ranges was kind of 50, 60% you realize, like, so I imply that nice end result for the shopper and in addition for the financial institution, as a result of they they’re releasing up workers to do way more attention-grabbing work.

Whitney McDonald 12:09:55
Yeah, that’s a fantastic instance of the way it’s, you realize, enhancing inside operations and what you you realize, need to do manually or not, but additionally enhancing {that a} buyer expertise. It form of exhibits each side of exhibits each side of the coin. So thanks for that instance. Now I need to discuss by this concept of immediate and pray that you just’ve talked about earlier than. Clearly, with generative AI, you should have the best immediate you discuss by the coaching and why that’s necessary, perhaps form of inform us what immediate and pray means to you and the way monetary establishments can keep away from that, you realize, I hope this works.

Steve Morgan 12:10:31
Mentality, yeah, we now have a I adhere to this personally, however the firm, we now have a agency view on this, which is grounded, wouldn’t shock you in our workflow automation or course of insurance policies, background, any necessary piece of labor at a financial institution has insurance policies, procedures, escalation, paths, you realize, audit, danger oversight, proper? After which, in lots of circumstances, regulatory oversight as nicely. Simply because we’ve obtained new AI and automation instruments, none of that stuff goes away. None of that stuff goes away. So if you wish to exchange an individual with an AI agent, they nonetheless need to comply with so. And insurance policies, procedures, escalation paths, oversight, checking, you realize, QA, so you realize the immediate piece, immediate and pray piece is referring to folks considering they may simply use a generative ai, ai agent, not grounded in insurance policies, procedures, escalation paths, not grounded in a repeatable course of with clear levels and steps, and, you realize, virtually permitting it to have some ingredient of creativity. Effectively, are you actually going to need creativity when somebody’s making a call on a small enterprise mortgage or a house mortgage with with the financial institution already has a set danger urge for food. They’ve a set danger profile of consumers. They need to lend to, quantities they need to lend, exposures they need so there’s an, there’s a, there’s an opportunity of doing a misusing generative AI, which may be good for creativity, good for summarization, good for pulling data out. However except you level it and inform it to haven’t any creativity and simply have a look at a sure set of paperwork, you may you may have errors developing. You could possibly have errors, or they name them hallucinations. I hate that phrase. It’s errors. It’s errors. And also you there’s no tolerance for errors or restricted tolerance in right now’s processes, even when they don’t have some AI and automation. So Why would, why would you deal with these procedures any in another way by making use of AI and automation?

Whitney McDonald 12:12:23
Jeremy, yeah, yeah. I believe that’s nice. And I believe that it’s it’s a fantastic reminder that you should have these insurance policies in place. You should have, you realize, some kind of guardrail that’s nonetheless going to will let you be compliant, nonetheless function how a financial institution operates.

Steve Morgan 12:12:39
Simply, yeah, yeah. The opposite factor I believed, You imply, it’s necessary to consider, is that is auditability, Governability, transparency. I imply, we’ve, we’ve had constructed into our AI for a minimum of seven or eight years now what’s referred to as a transparency swap on our decisioning AI, which is for subsequent greatest actions, subsequent greatest selections. However an important factor that we’ve executed, I believe, is have a look at being having the ability to be clear and clear on what’s the AI doing. So, whether or not you’re utilizing predictive machine studying AI, whether or not utilizing generative AI, whether or not you’ve obtained an AI agent, it must be explainable to the extent, like a financial institution has to do right now once they go to the once they need to go and see their regulator as soon as a month, with the chief danger officer and like head of credit score evaluation or lending, and say, how are your algorithms working? How are your selections working? Are you seeing any uptick in collections whenever you’ve modified your automated lending procedures? Have your guide procedures stayed in line? How are you checking that your individuals are doing the best factor? Identical factor applies to an AI AI agent or AI or automation. How have you learnt it’s working the identical method? How have you learnt what’s occurred whenever you’ve made a change? How have you ever made positive it’s gone constantly throughout all channels. How has it gone constantly throughout your workers? What’s the shopper expertise? So I believe there’s an enormous ingredient there which individuals underestimate, that any regulated business, however particularly banks, need to, need to and will adjust to in order that they will be sure that the end result is the best one for the shopper in the end,

Whitney McDonald 12:14:05
yeah, I’m glad you introduced up auditability, since you want to have the ability to comply with that path backwards of how sure selections have been made, or, you realize, what, what was offered to a shopper. You’ve got to have the ability to, you realize, cross these t’s and dot these, i’s alongside the best way. That’s 100% vital. Now, you talked about a few examples with a few of your shoppers. Possibly we might go slightly bit additional there and discuss by some use circumstances, each on what Gen AI ought to be used for, what are some good functions, after which perhaps what it’s not prepared for, what it shouldn’t be used for? The place’s the danger not price it?

Steve Morgan 12:14:38
Yeah, positive, it’s a very good query. So and we like to remain in contact with the market by each our shoppers, but additionally our companions which are actually necessary that we work with. And in reality, it was simply three weeks in the past I had like, the heads of banking from our key companions, you realize, like Accenture, ey, cognizant, Capgemini, et cetera, get collectively, and I truly requested them this query. I shared with them a listing of, like, kind of our primary pipeline areas and areas of focus with banks. And I stated, which areas are you guys and women all seeing as being the important thing areas for the applying of agentic AI and Gen AI. And there was unanimous agreements that there was, you realize, a few primary areas the place it’s actually relevant and is being checked out and will likely be used extra subsequent 12 months. And I believe the primary one is certainly customer support and operations groups, which most operations groups now have a a component that touches the shopper, a component that doesn’t contact the shopper, non buyer dealing with. They’ve a combination typically. So these areas of customer support, which individuals have a tendency to think about as contact facilities and space and branches, after which operations, which tends to be every thing that’s in every single place else, however nonetheless buyer dealing with and non buyer dealing with, these are among the greatest use case areas for the applying of Gen ai, ai and automation extra typically. And a part of the explanation for that Whitney is as a result of they’re giant value swimming pools for the banks. However the true different necessary factor is there the service ranges kind of offer you an excellent objective. Of how completely happy the shopper is, whether or not they’re going to be fascinated about renewing no matter they’ve obtained product sensible with you, like a house mortgage or extending and utilizing different merchandise. In order that they’re a great influencer to the income stream as nicely. The opposite space I’d spotlight can be simply broadly, the certainly one of buyer engagement, the place, wherever you’re interacting with a buyer, whether or not it’s digital and digital solely, or whether or not it’s with a mixture digital and getting, you realize, actually seamlessly or frictionlessly to to an individual to assist. I believe that, once more, is a crucial space the place you should utilize generative AI with no create with restricted creativity. So you might virtually set the creativity to zero, however get it to assist with procedures, insurance policies, choices, after which at a sure level, both the shopper may request, you realize what, I need to discuss to, somebody dwell, or the financial institution might go, You realize what? This can be a level the place we should always intervene to provide them some recommendation, focus on some choices. Yeah, so I believe there’s, broadly talking, these, these the principle areas, the areas the place you don’t need to use, we don’t use use any creativity linked to generative AI, however you might nonetheless use parts of generative AI for like summarization kind issues could possibly be areas like funds, cost exceptions, cost disputes, cost fraud, the place there may be fairly advanced circumstances, fairly vast ranging, particularly on the business facet. So there, it’s fairly helpful to have one thing like generative AI that may show you how to summarize it, summarize the scenario, summarize the case. However once more, it’s once more wanting internally. It’s your truth base, your information base. It’s not what some folks consider as Gen AI as a big language mannequin that’s public and getting used, you realize, for everybody on their cell phone, for instance. So I believe the opposite areas the place you’d avoid can be much like, just like the cost fraud dispute instance, areas the place it’s it’s very clear, and you realize, very clearly set what the method is, the insurance policies are, and there’s a excessive quantity of interplay. So except you need some conversational ingredient, Gen AI might be much less relevant in a few of these examples.

Whitney McDonald 12:18:06
I’d like to shut out with with this last considered, let’s say you’re an establishment that’s wanting into Gen AI, approaching it, you realize, form of beginning to consider what their what their pathway or journey to Gen AI ought to be, what can be the 1st step earlier than taking over a undertaking. You realize, you may, you may take into consideration, what’s going to the returns be? Or, you realize, how will this enhance our operations? However actually, what’s the 1st step? When you take it all the way down to the naked bones,

Steve Morgan 12:18:36
I believe the 1st step is, what’s the artwork of the potential? You realize, if you happen to’re there, fascinated about your space, no matter processes, no matter space you’re working at within the financial institution, what’s the artwork of the potential. After which when you consider the method and what’s potential, you then, clearly, by implication, have a look at the best way to rework, re engineer the method, but additionally what supporting applied sciences can do. So So that you have a look at the non know-how and know-how side of an finish to finish course of, and yeah, suppose the place do you need to get to and what’s potential? And I there’s quite a lot of shoppers doing this in several methods, having alternative ways, having issues like hackathons, the place it’s a combination of concept technology, plus utilizing know-how to provide you with a, you realize, a prototype resolution rapidly, in a matter of hours a day. I believe these types of issues are very efficient, as a result of then you definately’ve obtained some concepts gone by some course of, you’ve checked out Tech and non tech processes, then you may put collectively a very robust enterprise case, get help and put collectively a great undertaking staff, you realize, after that. So I believe that some folks name it ideation. I don’t significantly like that phrase. Issues are made up phrase, however yeah, like kind of

Speaker 1 12:19:37
creating concepts, ideation and hallucination, yeah, made up phrases.

Steve Morgan 12:19:43
It’s principally developing with the concepts and the place you need to focus, after which that results in every thing else. I do suppose Gen AI and AI and automation proper now has such a huge impact potential on most industries, particularly banks. I do suppose the change administration items are going to come back increasingly necessary as a result of it’s affecting it’ll have an effect on a lot of folks’s jobs, processes, the best way issues are executed with the shopper, so the change administration turns into crucial with

Whitney McDonald 12:20:08
all of it. Effectively. Thanks a lot for becoming a member of us on The Buzz. It was a pleasure to have you ever and discuss all issues. Gen AI, wanting ahead to having one other dialog about this sooner or later.

Steve Morgan 12:20:17
Thanks very a lot. Whitney, it’s been nice being on thanks.

Whitney McDonald 12:20:22
You’ve been listening to the excitement a fin AI information podcast. Please comply with us on x and LinkedIn, and as a reminder, you may fee this podcast in your platform of alternative. Please you’ll want to go to us at finaI information.com. For extra finaI Information. Thanks for listening. You.

Transcribed by https://otter.ai