Podcast: Rabobank, Santander Brazil see returns from Pega GenAI

Whitney McDonald 12:01:05
Whitney, hi there 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 subsequent step in our mission to guide the dialog on innovation in monetary companies expertise. Becoming a member of me in the present day, December 16, 2025 is Steve Morgan, world banking trade lead at Pegasystems. Steve is right here to debate how banks are utilizing generative AI, together with greatest makes use of of the expertise, and likewise the place Gen AI may not be the perfect match. Thanks for becoming a member of us, Steve.Steve Morgan 12:01:36
Properly, thanks Whitney, thanks for having me on. My identify is Steve Morgan. I’m pega techniques, world banking trade lead. And Pegasystems is a AI and workflow automation firm that’s been round for 40 years. Nice.

Whitney McDonald 12:01:49
Properly, we’re going to speak right here concerning the rush of moving into generative AI. It’s not essentially a shock that people are desirous about Gen AI and monetary companies, however they clearly have to, they should weigh, you recognize, the advantages and the dangers, velocity to market and compliance, and typically that isn’t the case. Perhaps you possibly can type of discuss us by way of what you’ve seen within the house when it comes to balancing that, that need for competitors, but in addition the necessity to concentrate to compliance. Yeah, it’s

Steve Morgan 12:02:22
been, it’s been a extremely fascinating journey the final couple of years as generative AI has change into mainstream, and yeah, for certain, I can present you, share with you, some shopper examples and what we’re seeing available in the market. I imply, what we did right away was take into consideration how, how and the place is the perfect 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 software of AI generally, AI and automation is form of in broadly, form 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 doable experiment. Experiment internally, typically first after which do one thing exterior, shopper dealing with. And I believe what’s change into extra vital, vital fascinating debate is, let’s take into consideration the enterprise end result first. Let’s take into consideration the proper of AI for the proper use case, and the place we want 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 client end result.

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

Steve Morgan 12:03:56
So yeah, I believe with any huge program of change, and even small program of change, it’s worthwhile to take into consideration, sure, as we stated, the end result first, after which the way you’re going to method the challenge and the change administration. And in case you do this, and also you look finish to finish, to finish of the entire course of, you’ve acquired extra probability of success. What we now have discovered is in some organizations, there’s an actual need to experiment, check issues out, attempt issues, and if that’s not performed within the context of the outcomes and the change administration, challenge administration, you will get points, and it’s extensively identified, and in reality, there’s been nearly like new phrases created about hallucinations, battle, conflagrations, which is mainly errors that generative AI could make, which is totally different, to say, statistical AI or machine studying, which could be very disciplined, can be taught and react and create predictions. So possibly forgive you, an instance would possibly carry it to life with a shopper, how they’ve approached it, which I believe could be very sensibly so rabobanks, a good sized European shopper of ours, they usually 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 effectively the financial institution offers with that? In order that they wished to see, firstly, how might they apply AI and automation to enhance the efficiency their workers who’re coping with the client, who’re fixing the problem, or attending to investigating it, attending to the underside of it, they usually used a mix of our applied sciences and others to to actually enhance the data, the steering, the teaching to their groups. They nonetheless had an individual doing doing the doing the work within the massive proportion of instances. 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 techniques that would get the work performed robotically. They did that internally, they usually truly talked to our convention this June, simply gone about going from thousands and thousands of {dollars} of losses to 1000s of {dollars} of losses, which is sensible, sensible end result for the client and for the again. Financial institution, they then determined to take it to the subsequent stage and take a look at exterior dealing with, buyer dealing with examples the place the expertise is totally uncovered, they usually, 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 may change into extra conversational, extra entry higher data as a way to get a greater interplay with the client, and likewise then a greater, extra clear motion to finish for the client. And so they’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 take a look at some inner use instances, you recognize, take a look at how what the end result might be. After which take a look at some exterior buyer dealing with use instances off the off the again of in some inner success.

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

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 massive retail banks within the UK. They’ve acquired a software which does, does take some in case you’ve acquired any further deposits in your account, it should sweep it and put them in a like increased curiosity saving or make investments them, if you wish to. And so they have been speaking about that software and saying it’s fairly fundamental. It’s fairly fundamental automation in the intervening time, however they need the power to set off like a subsequent greatest motion for the client, and even set off doubtlessly both the client robotically decides, you recognize what, there’s sufficient there. I wish to make investments it available in the market, 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 yr, truly, Santander Brazil, they usually did. They talked as effectively at our convention in June, who took a extremely fascinating case, a vital space as effectively for a financial institution of authorized operations. And so they wished to not solely enhance the interior operations of it, however for the client. You possibly can think about, with authorized instances, you recognize, banks have to offer data to the shopper, to the choose, to the attorneys, plus they’ve to make use of a bunch of attorneys typically evaluate paperwork, and nobody likes paying cash for attorneys. In order that they checked out, how might they enhance that course of, each internally and the shopper dealing with facet. And once they launched generative AI to it, they took what I believe is a really wise 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. Once they first did it, it was 67% correct, which isn’t ok. Their greatest workers member doing it was 95% correct. In order that they educated the mannequin with consultants in authorized and authorized operations space. They educated over a interval of three months, they usually acquired it months, they usually acquired it to 98% correct, so higher than the perfect particular person doing that position. And a few of that position was taught boring stuff, you recognize, like 200 web page paperwork, extract the data, analyzing it. In order that they enabled some boring work to be made redundant. They redeployed individuals into some extra fascinating stuff, which is like, you recognize, I’ve to speak to you, Whitney, the lawyer, or I’ve to speak to the client and provides them sure paperwork and stuff like that. And the perfect results of all wasn’t eradicating the redundant work. Wasn’t eradicating the the steps that have been pointless or boring. The perfect consequence was for the shopper that the service ranges went to love 96 to 100% and the service ranges was once form of 50, 60% you recognize, like, so I imply that nice end result for the client and likewise for the financial institution, as a result of they they’re liberating up workers to do rather more fascinating work.

Whitney McDonald 12:09:55
Yeah, that’s an awesome instance of the way it’s, you recognize, enhancing inner operations and what you you recognize, must do manually or not, but in addition enhancing {that a} buyer expertise. It type of reveals each side of reveals each side of the coin. So thanks for that instance. Now I wish to discuss by way of this concept of immediate and pray that you simply’ve talked about earlier than. Clearly, with generative AI, it’s worthwhile to have the proper immediate you discuss by way of the coaching and why that’s vital, possibly type of inform us what immediate and pray means to you and the way monetary establishments can keep away from that, you recognize, 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 vital piece of labor at a financial institution has insurance policies, procedures, escalation, paths, you recognize, audit, danger oversight, proper? After which, in lots of instances, regulatory oversight as effectively. Simply because we’ve acquired new AI and automation instruments, none of that stuff goes away. None of that stuff goes away. So if you wish to substitute an individual with an AI agent, they nonetheless must comply with so. And insurance policies, procedures, escalation paths, oversight, checking, you recognize, QA, so you recognize the immediate piece, immediate and pray piece is referring to individuals 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 phases and steps, and, you recognize, nearly permitting it to have some factor of creativity. Properly, are you actually going to need creativity when somebody’s making a choice 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 wish to lend to, quantities they wish to lend, exposures they need so there’s an, there’s a, there’s an opportunity of doing a misusing generative AI, which might be good for creativity, good for summarization, good for pulling data out. However until you level it and inform it to haven’t any creativity and simply take a look at a sure set of paperwork, you possibly can you possibly can have errors developing. You can 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 in the present day’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 an awesome reminder that it’s worthwhile to have these insurance policies in place. You have to have, you recognize, some form of guardrail that’s nonetheless going to help 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 vital to consider, is that is auditability, Governability, transparency. I imply, we’ve, we’ve had constructed into our AI for not less than seven or eight years now what’s known as a transparency change on our decisioning AI, which is for subsequent greatest actions, subsequent greatest selections. However crucial factor that we’ve performed, I believe, is take 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 acquired an AI agent, it must be explainable to the extent, like a financial institution has to do in the present day once they go to the once they must 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 while you’ve modified your automated lending procedures? Have your handbook procedures stayed in line? How are you checking that your persons are doing the proper factor? Identical factor applies to an AI AI agent or AI or automation. How have you learnt it’s working the identical approach? How have you learnt what’s occurred while you’ve made a change? How have you ever made certain it’s gone persistently throughout all channels. How has it gone persistently throughout your workers? What’s the client expertise? So I believe there’s an enormous factor there which individuals underestimate, that any regulated trade, however particularly banks, must, must and will adjust to in order that they’ll ensure that the end result is the proper one for the client 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 recognize, what, what was introduced to a shopper. You’ve to have the ability to, you recognize, cross these t’s and dot these, i’s alongside the best way. That’s 100% mandatory. Now, you talked about a few examples with a few of your shoppers. Perhaps we might go a little bit bit additional there and discuss by way of some use instances, each on what Gen AI needs to be used for, what are some good purposes, after which possibly 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, certain, it’s a extremely good query. So and we like to remain in contact with the market by way of each our shoppers, but in addition our companions which might be actually vital that we work with. And actually, it was simply three weeks in the past I had like, the heads of banking from our key companions, you recognize, like Accenture, ey, cognizant, Capgemini, et cetera, get collectively, and I truly requested them this query. I shared with them a listing of, like, form 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 recognize, a few primary areas the place it’s actually relevant and is being checked out and might be used extra subsequent yr. And I believe the primary one is unquestionably customer support and operations groups, which most operations groups now have a a component that touches the client, a component that doesn’t contact the client, non buyer dealing with. They’ve a mixture 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 all the pieces that’s all over the 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 massive value swimming pools for the banks. However the actual different vital factor is there the service ranges form of offer you an excellent purpose. Of how pleased the client is, whether or not they’re going to be occupied with renewing no matter they’ve acquired product clever 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 effectively. The opposite space I’d spotlight can be simply broadly, the one among 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 mix digital and getting, you recognize, actually seamlessly or frictionlessly to to an individual to assist. I believe that, once more, is a vital space the place you need to use generative AI with no create with restricted creativity. So you can nearly set the creativity to zero, however get it to assist with procedures, insurance policies, choices, after which at a sure level, both the client would possibly request, you recognize what, I wish to discuss to, somebody stay, or the financial institution could go, You recognize what? It is a level the place we should always intervene to present them some recommendation, talk about some choices. Yeah, so I believe there’s, broadly talking, these, these the principle areas, the areas the place you don’t wish to use, we don’t use use any creativity linked to generative AI, however you can nonetheless use components of generative AI for like summarization sort issues could possibly be areas like funds, fee exceptions, fee disputes, fee fraud, the place there might be fairly advanced instances, fairly large ranging, particularly on the business aspect. So there, it’s fairly useful to have one thing like generative AI that may enable you to summarize it, summarize the state of affairs, summarize the case. However once more, it’s once more trying internally. It’s taking a look at your reality base, your data base. It’s not what some individuals consider as Gen AI as a big language mannequin that’s public and getting used, you recognize, for everybody on their cell phone, for instance. So I believe the opposite areas the place you’d avoid can be just like, just like the fee fraud dispute instance, areas the place it’s it’s very clear, and you recognize, very clearly set what the method is, the insurance policies are, and there’s a excessive quantity of interplay. So until you need some conversational factor, 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 trying into Gen AI, approaching it, you recognize, type of beginning to consider what their what their pathway or journey to Gen AI needs to be, what can be the first step earlier than taking up a challenge. You recognize, you possibly can, you possibly can take into consideration, what is going to the returns be? Or, you recognize, how will this enhance our operations? However actually, what’s the first step? In case you take it all the way down to the naked bones,

Steve Morgan 12:18:36
I believe the first step is, what’s the artwork of the doable? You recognize, in case you’re there, occupied with your space, no matter processes, no matter space you’re working at within the financial institution, what’s the artwork of the doable. After which when you consider the method and what’s doable, you then, clearly, by implication, take a look at the right way to remodel, re engineer the method, but in addition what supporting applied sciences can do. So So that you take a look at the non expertise and expertise facet of an finish to finish course of, and yeah, suppose the place do you wish to get to and what’s doable? And I there’s quite a lot of shoppers doing this in numerous methods, having alternative ways, having issues like hackathons, the place it’s a mix of thought technology, plus utilizing expertise to give you a, you recognize, a prototype answer shortly, in a matter of hours a day. I believe these kinds of issues are very efficient, as a result of then you definately’ve acquired some concepts gone by way of some course of, you’ve checked out Tech and non tech processes, then you possibly can put collectively a extremely sturdy enterprise case, get assist and put collectively a great challenge group, you recognize, after that. So I believe that some individuals name it ideation. I don’t significantly like that phrase. Issues are made up phrase, however yeah, like form of

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

Steve Morgan 12:19:43
It’s mainly developing with the concepts and the place you wish to focus, after which that results in all the pieces else. I do suppose Gen AI and AI and automation proper now has such a big effect potential on most industries, particularly banks. I do suppose the change administration items are going to return increasingly more vital as a result of it’s affecting it should have an effect on numerous individuals’s jobs, processes, the best way issues are performed with the client, so the change administration turns into vital with

Whitney McDonald 12:20:08
all of it. Properly. 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, trying 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 thrill a fin AI information podcast. Please comply with us on x and LinkedIn, and as a reminder, you possibly can price this podcast in your platform of alternative. Please you should definitely go to us at finaI information.com. For extra finaI Information. Thanks for listening. You.

Transcribed by https://otter.ai