How to Turn Customer Interactions Into ROI

Jim Marous (00:11):

Every customer conversation, whether it be in a branch, online, or through a call center, holds to the potential to either deepen loyalty or potentially increased attrition. Yet too often these interactions create frustration, higher costs, and lower satisfaction scores.

Jim Marous (00:31):

Today's competitive advantage is not just about having data, it's knowing how to transform conversations into measurable business value; from lowering cost to serve, to boosting net promoter scores, the opportunity is clear, banks that successfully harness AI and conversational intelligence are realizing game changing ROI, while others remain stuck in pilot projects.

Jim Marous (00:59):

In this episode of Banking Transformed, I'm joined by Caleb Johnson, the Vice President of TTEC Digital and Chris Dolan from Cisco. Together we'll explore how financial institutions can build the infrastructure, insights and strategies to orchestrate seamless customer journeys and turn everyday conversations into bottom line results. If you are looking for a practical way to move past AI hype and pilot projects and drive measurable customer experience transformation, this conversation is for you.

Jim Marous (01:34):

So, welcome to the show, Caleb and Chris, before we begin, could you please introduce yourself to our audience? Caleb, we'll start with you.

Caleb Johnson (01:41):

Yeah, thanks, Jim. Thanks for having us. So, Caleb Johnson with TTEC Digital I've been working in this customer experience space for the last 10 to 12 years. And at TTEC for those that don't know we're a global customer experience services company, working with a lot of brands as they go through transforming all of their different customer experiences. So, Chris.

Chris Dolan (02:02):

Yeah, thank you again, Jim, for hosting us. I'm the senior engineering leader for Cisco, supporting the Americas customers within the customer experience technology. I've been with Cisco for 30 years and have seen many transformations starting off with the routing portfolio or platform. And now as we see the huge portfolio that Cisco has with technology solutions, including AI, which we empower businesses to create connected, intelligent and secure customer experiences.

Jim Marous (02:38):

So, Caleb, the current state of AI adoption is changing every day, especially in retail banking. What do you seen in terms of where most financial institutions sit on the AI maturity curve? So, it says. And what's holding back them back from moving beyond just pilot projects?

Caleb Johnson (02:59):

Yeah, I mean we're seeing AI get adopted in a lot of places right now. I think it is still in the infancy when you look at the potential of what AI can do. Inside of retail banking, we're finding that many companies are starting to play with what I'll call conversational AI, going out and looking at ways they can automate some of the front-end customer experiences. Many people have probably seen that we call into the bank, and you get a virtual agent that answers a call and it can help you do some self-service flows, or you might see it in a mobile app.

Caleb Johnson (03:30):

I think that the challenge that we have seen a lot of these companies run into so far is they have a limitation on both the data, how that's available, is it ready to be used by AI, which you see things get started within a proof of concept and then it kind of stalls out.

Caleb Johnson (03:47):

And there's a lot of questions around like from a legal and a compliance standpoint, security is extremely top of mind for these businesses. And so, it's really starting to employ or to deploy a true like enterprise AI strategy, which is what's going to actually kind of drive this into full adoption.

Jim Marous (04:06):

So, both your organizations emphasize the importance of data and driving customer experience decisions. Can you both walk us through a little bit about how banks can move beyond making customer experience decisions based on guesswork or partial data insights to truly a data-driven strategy? Chris, we'll start with you.

Chris Dolan (04:27):

Yeah, I think there's multiple facets to that. Clearly data is king. AI thrives on data and in order to see the full potential of what the banking industry can take advantage of; we really need to get the data silos stitched together. And that way we can then transform the customer experience that we're asking of the technology to deliver to any of our customers coming into the banks.

Chris Dolan (04:56):

One of the areas is clearly being able to secure that data in a way that allows the banking industry to be compliant, conform to the regulations that they need to, and really drive a trusted environment for their customers.

Jim Marous (05:16):

Caleb, what gets in the way? What is the hurdle that financial institutions are having the hardest time understanding or achieving?

Caleb Johnson (05:27):

Yeah, I mean there's a couple of things I'll highlight. So, one of them is actually the internal skills around this. So, there is still a skill gap that is in the market around AI, but part of the challenge there is the technology is simply changing at a rapid, rapid pace.

Caleb Johnson (05:43):

So, you might be quite comfortable with how AI was operating three years ago, and then generative AI has happened, large language models has happened. Even within those models, they're changing at about every three months. And so, being able to actually understand how to leverage these technologies have a strategy around it, that's one hurdle.

Caleb Johnson (06:04):

The second piece, and I kind of hinted at it earlier, is really around the compliance side of stuff and the security and kind of the trust of, okay, we're going to go deploy this, but where are we deploying it? Which AI solution are we using to be able to go do that? How much do you know about that organization? And you've got everything from the hyperscalers that have AI to startups that are deploying all kinds of new models and capabilities.

Caleb Johnson (06:26):

And so, there's a function of a little bit of indecision that's happening right now inside some of the companies, do you start investing now, am I build onto an ecosystem or am I going to wait another year? Am I going to wait another two years while things kind of settle down? So, we run into those from a hurdle perspective.

Caleb Johnson (06:47):

And then the last piece, I'll kind of touch on this — and Chris, I'd love to get kind of your thoughts on what you're seeing too is from an actual internal, being able to decide which is the best use cases to go with. And so, there's a hundred different applications of AI right now from data engineering to code development to conversational AI.

Caleb Johnson (07:07):

And so, it's being able to get some level of consensus inside of the business to say, alright, we believe there's an ROI, we believe there's a use case that we can help improve our customer experience, improve the business, save money but somebody's got to be in charge. Somebody actually has to make a decision, own that, be accountable for it all the way up to the executive layer.

Chris Dolan (07:26):

Yeah, for sure, and I think everything that we've seen so far has been start small, start inside versus outside, inside the company, so you're not putting your customers at risk and your brand at risk, but then iterate quickly. So, figure out what your ROI is going to be, what you're looking for in terms of success, make sure that you're measuring upfront, and then be able to iterate quickly so that you can take advantage of the momentum that you get internally.

Chris Dolan (07:54):

A lot of this as you look at AI tools and being able to do pilots internally, it's around change management as well. Being able to keep the entire business up to speed with what this looks like and how this feels when it actually hits your particular organization allows you then to use those early adopters to help educate the middle of your teams, the ones who are ready to take advantage, but don't want to be out on the edge of the limb taking a risk.

Jim Marous (08:27):

It's interesting, Chris, as I look at financial institutions overall, both you and Caleb, what I see is there's a lot of emphasis on internal operations, automation, simplification, cutting costs, working on back office scenarios, and quite a few less, even though there's a lot of talk about it, quite a few less being spent and exerted towards customer experiences. We've got to move them off that, I mean, we really have to have AI solutions that really help the customer journey and customer experience.

Jim Marous (09:00):

Chris, from your perspective, what signals should finance institutions be looking for to identify where maybe the most impact can be made in the customer experience operations?

Chris Dolan (09:13):

Yeah, I think clearly an advantage for the banking industry is that there is a lot of questions that customers are asking banks that are rudimentary or repetitive in nature. And so, there's high volumes of repetitive questions and interactions that customers are having with the banking industry, being able to capture that and figure out what those high volumes are, with the questions, the interactions are, and automating that in a way that then makes it far more seamless for the customers to self-serve, to be able to get answers to questions 24/7.

Chris Dolan (09:55):

And at Cisco, we actually leverage a technology, which is AI powered called topic analytics that allow us to do that seamlessly. So, it captures the customer interactions with the contact center today, and it will analyze what the questions are and how deep the customers need in terms of the answers.

Chris Dolan (10:18):

And that gives a footprint for our leaders to be able to then take that information and craft automated virtual assistance to answer those questions succinctly with the bank's own information, their own knowledge banks. So, it becomes very secure in terms of, it's not using outside data, it's using the bank's own knowledge banks to provide information back to their own clients.

Jim Marous (10:46):

Caleb, it's interesting, the concept of customer journey orchestration, which honestly, I was unfamiliar with until recently. It really seems extraordinarily relevant in places, in industries like banking where the customer might start a loan application, lets say online or on a mobile device, even then call in for some questions, then visit a branch. How does TTEC help banks orchestrate these really complex multi-channel journeys?

Caleb Johnson (11:15):

Yeah, there's a few things that we try and do around customer journey orchestration. And I'll say the nice thing is that as technology has advanced, there is so much data available now about, to your point where somebody starts, where they drop off, what's the next place they contacted you, how they get to the next stage, and also like what do you want to be able to do with that?

Caleb Johnson (11:38):

So, we will go in and do a lot of workshops and kind of road mapping sessions with clients we're actually drawing out these customer journeys. It's a traditional thing we see in customer experience. But then we're also going in and really kind of auditing the technology stack that companies have. And what we find many times is they have a lot of different technology components that don't speak to each other.

Caleb Johnson (12:01):

So, you've got a lot of isolated information that's sitting out there. And so, it becomes, today you look at how some of them operate. They really will manage their business in a reactive way where customers are jumping from one place to the other instead of shifting into this more of a proactive or kind of concierge type model to where you can start to use things like AI to actually guide somebody through an experience or through a journey, but then also start to proactively make the suggestions, the recommendations to them on what they should be doing.

Caleb Johnson (12:30):

Next, you can start to do things like automation from a communication perspective to be able to remind them of where they dropped off. And I'm sure many people in your audience have seen these types of things. You go onto a retail site, you put something in a cart, you abandon the site, and you get an email, five minutes later that says, “Did you forget to check out that?” Those types of things.

Caleb Johnson (12:47):

So, I think there's some adoption of these strategies that we work with a lot of companies on that you'll start to see coming more into the banking sector, it is going to help move everything forward, it'll be much better customer experience at the end of the day.

Jim Marous (13:02):

That, even though it's very typical for most organizations, that's still the basics, being able to make it so that we can keep track of the customer and where they are in the journey across channels. Your solution mentions conversational intelligence as being a key capability needed by retail banks and credit unions, for banking leaders listening, can you explain a little bit how analyzing conversations can actually reveal hidden insights about products, maybe friction and even the customer sentiment?

Caleb Johnson (13:35):

Yeah, absolutely. So, maybe I'll kick this off and Chris, you can kind of add into how you're enabling some of this. So, what we find with conversational analytics is that you have a direct, real-time view into what customers are actually saying.

Caleb Johnson (13:49):

Historically, if you look at how companies gathered information about kind of the customers and their sentiment and what they were looking to do, it was really through surveys or maybe just a random anecdotal conversation. And surveys you look at it from an NPS standpoint, it was, do they either like you or they not like you? And typically, the only people that are responding to that are somebody that had a really good experience or a really bad experience.

Caleb Johnson (14:10):

So, now you're getting the entire collection of every conversation that's happening, whether it's with a human agent, a virtual agent, through a chat conversation, whatever that is, and you're able to start to see both macro and micro trends in those conversations.

Caleb Johnson (14:25):

So, you can start to be able to use that information to both determine why are people contacting us? Why are they calling us? And be able to shift into things like self-service on the front end to where you see trends of very common requests that people are getting, but also the sentiment of those conversations where you can start to establish that if every time that somebody fills out a loan application, they actually have a negative sentiment. Why is that? Is it because it's difficult? It takes too much time?

Caleb Johnson (14:51):

And so, you're able to find these types of deep insights that historically those just wouldn't bubble up from the other ways that we would collect data in the past.

Chris Dolan (15:02):

I think that what I'd add to that is, most of our companies, they large companies anyway and even some of our company banking for instance, with a lot of branches that may have multiple contact centers that may have a contact center that handles loans, it may handle fraud detection in a different organization. It might handle just customer onboarding. With all of this data in a lot of cases it's very siloed.

Chris Dolan (15:29):

So, we talked about the customer journey, well, this is part of the customer journey and being able to stitch all of those interactions together and then allow us to really look at what are the behavioral insights. So, if you're looking at fraud detection, how do you take the behavior of a customer and really understand what is abnormal, what suspicious actions, and then act on that accordingly in a proactive manner.

Chris Dolan (15:56):

And so, it's not just proactive notifications that we can send out based on behavioral insights that we have, but it could also be just suggestions on how you may structure your banking app a little bit differently, how you might put different security protocols, how you might change your passwords, because you haven't done that recently.

Chris Dolan (16:16):

Like there's many personalized aspects to this that will allow us to then build a trusted relationship with our customers, which we didn't have before, or we kind of lost in the evolution of banking. Where we used to have somebody walk into a branch, they were there for years and years, and they'd be able to create this really trusted relationship with the brand. That's how we're really trying to get back to it with AI and leveraging the power of AI to build that real trust relationship.

Jim Marous (16:52):

It's interesting, recently I've read quite a few articles, and while there's a lot of great talk and momentum and enthusiasm about AI, there's still a lot of organizations that are saying they're getting zero or unmeasurable results from their implementations. And there's nothing worse than to be the proponent of AI solutions in a financial institution. Only have it come back, and nobody can put a number on it.

Jim Marous (17:17):

How do both your organizations help banking clients build a clear, actionable roadmap that can connect maybe a pilot project to concrete business outcomes? I mean, in one of the case studies I read about which certainly stuck out in my mind, there's a 388% ROI mentioned in one of your case studies. How do you move it from a shot in the dark to something that can generate revenue and build the ROI that's expected or even better than expected?

Caleb Johnson (17:48):

Yeah. Chris, do you want to start off?

Chris Dolan (17:50):

Well, I really think it's TTEC that is helping us do this. Caleb mentioned the workshops; there is a absolute need for us to be able to sit with customers and work through their business practices and what they're actually trying to achieve. Once we can do that, we can set clear metrics, clear outcomes that they're trying to drive.

Chris Dolan (18:16):

Part of AI use cases and virtual agents is very much around how do you establish the right criteria, the right knowledge bank, the right approach to the customers, the way that they would like to be answered.

Chris Dolan (18:32):

So, when you think about AI virtual assistants, they can have a lot of different personas. That is all part of your brand and establishing how you want to show up with your customers. But I think it really rolls back to these workshops and being able to really go slow, understand how you set the right use cases at the right time to drive a successful momentum into the ROI that you're talking about.

Chris Dolan (19:00):

And there's other components to this when you look at helping our internal agents. So, looking at our agents and empowering them to be successful. So, things like suggested responses and real-time transcription and call summaries, all of that helps reduce the wait times. It helps to provide a more accurate collection of the data, which again goes back to our regulatory things that we're trying to hit with the banking industry.

Chris Dolan (19:32):

If we can keep really concise and auditable transcriptions of the customer interactions, we then have a better idea of one, how do we measure success and how do we make sure that the company is not only gaining cost efficiencies, but also helping from a customer set, Caleb?

Caleb Johnson (19:54):

Yeah, for sure. So yeah, let me add on a couple of things here because I think it's important around this ROI concept. If you go look at the last three years, I'd say that pretty much every company has attempted some type of AI project, and they've tried to put some financial metric around that. What we have found is the traditional financial metric was, I'm going to go automate something and then I reduce my labor cost as a result of that?

Caleb Johnson (20:22):

What we have found is companies are starting to evolve in a different way, or kind of broaden the scope of what is actually a return on investment. You start thinking about like from a fraud perspective. We run into this with financial institutions all the time, that somebody might have a hold on an account in one system is not necessarily reflected in another system. And you're asking an employee for the bank to be able to go validate, yes, I can release this hold, but did they check every system?

Caleb Johnson (20:50):

And so, there are new use cases coming into play with AI where it's moving outside of just the traditional conversational AI and I'm deploying self-service. As you start to get into things around agentic, especially where you might have a process that took 30, 45 minutes in the past to go validate does somebody have a fraud hold on their account and why? You got to go pull all kinds of information together.

Caleb Johnson (21:11):

And so, you can take a 30-minute process down to 30 seconds now, and you can have the AI start to even be able to provide deeper insights into why was this done? Even establishing recommendations. Maybe you don't want AI going and doing reasoning at that point on fraud necessarily. But you can start to create efficiencies in that way but you also start thinking about the metric around what is the actual cost of fraud in the bank itself.

Jim Marous (21:34):

And so, if you can start to actually establish prevention of some of these things, and you're moving that, that changes the whole financial conversation that we're running into with companies right now.

Jim Marous (21:45):

Well, it's interesting Caleb, because Chris mentioned, and it was mentioned I think by you earlier, that you have a TTEC interactive workshop for customer experience and operational leaders that really gives a hands-on approach to try to define experience objectives, pinpoint opportunities, and really peel back the layers of the contact center and the customer conversations.

Jim Marous (22:09):

Can you tell us a little bit more about that workshop? Because by the way, in the episode notes you'll see a link to the interactive workshop that they're providing at TTEC. So, can you tell us a little bit more about that?

Caleb Johnson (22:21):

Yeah, absolutely. So, this is something we've been working with companies on the last couple of years. And, and there's several things that we try and accomplish in these workshops. One of it is truly an education of what is possible.

Caleb Johnson (22:33):

You kind of get into the art of the possible, being able to actually see some of these AI applications and tools in motion and really start to look at breaking down the traditional understanding of what AI is. And it's very common we walk into these workshops, and somebody will bring up something like agentic or generative AI, and four or five people have different definitions of what those things are.

Caleb Johnson (22:53):

So, it's starting to level set inside of a company to have a kind of a common language around here is AI, then you start to kind of pull back the covers of why have we had struggled to deploy these things in the past, or are there processes that we would've wanted to automate make more efficient in the past, but we couldn't, and what's really holding those things back?

Caleb Johnson (23:13):

So, starting to kind of establish this roadmap of priorities, identifying what the hurdles and the roadblocks are, and then starting to put together a priority plan that says, “Okay, if we actually go and accomplish these three or four projects to start, we can build a foundation using AI, get some of these applications in place, pick the right ecosystem.” And then it starts to give you something you can build on.

Caleb Johnson (23:35):

And kind of going back to the other comment around the proof of concepts and where things have struggled in the past, we have found that companies will go deploy something like a proof of concept coming out of these types of workshops. And if you don't have a plan on what's next, they typically will die off pretty quick. And you also don't want to just have throwaway costs; that's a part of this. You want to be able to say this investment created a foundation, that's something we can build on, and you've got the right technology that can actually support it.

Jim Marous (24:03):

So, actually these interactive workshops really number one, provide a common starting point. So, you really help, because you've helped so many financial institutions and other organizations, but this really helps to make sure everybody's on the same page to begin with. But you also kind of get rid of extraneous thoughts that are out there because you can end up all over the place.

Jim Marous (24:24):

Obviously, AI can touch everything and you may never get started because of that. And if you don't set up a measurement process as part of that, a lot of times people are saying, “Well, we haven't shown any results to date.” Sometimes just because they haven't set up a measuring process.

Jim Marous (24:41):

So, you really put things into context and say, here's how you can help definitively achieve success as you did in your ROI that I mentioned earlier, but also you get rid of all these other thoughts that may distract from your overall goal, correct?

Caleb Johnson (24:56):

Yeah, you're absolutely correct. And we also put to bed some of these messages that are out in the market at times. So, we've worked with Cisco for many years, Chris and I have worked on a lot of different things together. And in that we can walk into some of our clients and look at and say, “Hey, you have this technology deployed and it has AI capabilities in it.” You weren't even aware that it was available to you.

Caleb Johnson (25:19):

So, instead of going and investing in yet another technology, or you need to bring in something else, starting to actually utilize the technology you have and being able to build on that immediately get real time like near immediate value out of some of these things. So, that kind of goes back to that just making people aware that you've got these capabilities, just take advantage of them.

Jim Marous (25:40):

It's interesting, I talk about it on a lot of the podcasts, the fact that every financial institution has Salesforce somewhere in the shop, but a great number of these don't understand what the ROI on that implementation is. And it's a common challenge, but I think what you're saying is let's do an inventory first before we start jumping all over the place and trying to do something new, let's figure out where you are, what you have, how you can leverage it, and if you're leveraging it to scale.

Jim Marous (26:11):

So, Chris, what are the most common technological and organizational hurdles you see when financial institutions try to implement AI solutions at scale? And how can leaders prepare their teams and their overall infrastructure for success?

Chris Dolan (26:30):

Yeah, I think we've talked about some of them already. I guess the first one would really be the data silos and really normalizing your data. AI thrives on data and it's necessary for us to ensure that the teams that need to be working together, IT, business units, data scientists, we need to make sure that those teams are working in a manner that really looks at the data that they have and are able to normalize it so that the business can take advantage of it.

Chris Dolan (27:04):

Now, again, that requires a good plan in terms of understanding what the outcome is that they're shooting for. Because at the base of all of that is security and compliance. Whenever you start to think about data and think about where you're going to store the data, how you're going to store the data, how you're going to make it secure, what is the framework that you're going to be using in terms of AI? It's really a conversation that needs to be had upfront.

Chris Dolan (27:35):

Not a lot of companies have really sat down and put governance around what their AI strategy will be, and it's imperative that they do that before really diving too deeply. So, some of the efforts I think that need to occur first and the leaders really need to think about is, where is all this going to be residing and how are they going to keep it secure?

Chris Dolan (27:59):

On top of that, I think there is a team component to this, an organizational employee component to this. How are you getting everybody upskilled? There's not a lot of talent in the industry around AI. So, it's really helping the organization understand what AI is and what it isn't. And Caleb mentioned that in the workshop, is just level setting, but there's also a component of just general training around AI tools for productivity, AI tools for business and what that really means.

Chris Dolan (28:34):

And we hear in a lot of places that AI is taking people's jobs, well, really helping people to understand the essence of AI can really give them the assurance that it's not going to take their job. It's actually going to empower them even more to be far more productive and help them actually be more successful in what they're doing. So, there are a few elements, there's lots more that needs to be considered, but the big rocks are really around the data and the security components.

Jim Marous (29:08):

Well, and as you mentioned too, Chris, it's the people aspect. I think while people don't always state it, I think most employees get concerned, is AI going to replace my job, as you mentioned? And the reality is, this is where the partnerships with organizations such as Cisco and TTEC really come into play in that if you have good partners that have done this before and continue to do it, you've dealt with these hurdles, you've dealt with these conversations before.

Jim Marous (29:35):

It's a lot easier to come in and say, “Here's how your job may change, but it also secures your job for the future and makes it so that you as an employee are resilient and you can use the outcomes from this and help us move the whole organization forward.”

Jim Marous (29:52):

I think we sometimes talk a lot about the tech and about the regulatory issues and the technology issues. And I think what we forget about, is how important the people issues are from both the leadership and from an employee perspective.

Jim Marous (29:52):

Obviously, everything's changing at lightning speed and financial institutions are playing catch up at best, and sometimes they're still at a status quo, not moving at all. How do each of you see AI transforming the customer experience going forward in the next year or so, and what emerging capabilities should financial institutions be preparing for to make themselves more resilient in an AI driven world?

Caleb Johnson (30:39):

Yeah. Well, I think there's a ... it's interesting as you start thinking about how they can use it because one of the things that really comes into play here is the adoption of AI is going to be disruptive in every industry. Some of the industries have already been disruptive. Financial institutions, 100% are leveraging it, we know they are from all kinds of financial evaluations to the backend data engineering, definitely on the customer service side of stuff.

Caleb Johnson (31:04):

But there's also this existential threat of not using it right now, which is, you are going to have new digital native type of companies coming into market that are going to leverage AI from the core foundation of what they are. And so, when they are setting up their ecosystem, their hiring staff, it's always going to be done from the very beginning of being able to leverage AI and automation.

Caleb Johnson (31:28):

They don't have the same baggage or tech debt that some of the longstanding companies do. And so, there is an existential threat of like, “Hey, if you don't do this and figure out how to modernize some of the applications that might be holding you back or figuring out a strategy for it, there is definitely somebody else that is figuring that out and they're going to come into your market.”

Caleb Johnson (31:47):

So, there are a real world applications today of like companies being able to go in and automate many of their customer experiences on the front end which this next generation of people coming up that are going to have money, they are going to want to be able to operate and through a mobile app first, they're going to want to be able to interact with banks directly that way and a virtual agent 24 by 7. So, their behaviors are going to dictate, and if you don't have those things available, they will find someplace that does.

Jim Marous (32:16):

And at the same time, from an agentic capability, there are plenty of opportunities to start going in and deploying even simple automation on the back office where it doesn't require tremendous investments, it doesn't require tremendous time but it does take effort for people to go in and put an enterprise strategy together, start executing on it instead of just waiting to see kind of what happens. But Chris, I'd love to kind of get your thoughts too.

Chris Dolan (32:44):

Yeah, I think there's a few things that I think about the future of AI. Just the pace of AI right now is tremendous. So, everything's shifting within a week or a month, things have shifted.

Jim Marous (32:56):

Yeah, exactly.

Chris Dolan (32:59):

Caleb's, right, there are companies that are going to come in just like any transformation that are niche experts in a particular field. What I would say is, in the banking industry, in the FSI industry as a whole, there is a need to ensure that there is still the foundation of your compliance and your regulatory and your security.

Chris Dolan (33:25):

So, in an AI sense, really understanding, do you have explainable AI models that will actually answer how they found the answers, that are really good at giving you the transparency behind the data, behind the technology. I think that's critical for this industry to build the trust and the transparency that they need.

Chris Dolan (33:51):

As we move forward, there's a lot more technology and biometrics and just understanding where that field is going to go in terms of BFSI. And there's also hyper personalization in a banking world, understanding what then becomes really automated from a personalization, at some point, do they start investing low risk things for customers based on a profile, just the world is, completely open up to us.

Chris Dolan (34:30):

On the technology side though, like TTEC, Cisco, we're all about making sure that the technology that we are providing customers is secure, that we have the right guardrails around it, that we are not using customer data to train our models, that we ensure that there are responsible frameworks around everything that we're providing the customers.

Chris Dolan (34:55):

So, keeping that first and foremost when you are looking at implementing AI is going to be really critical as the pace continues to pick up. And companies yes, they need to get into this space, but they need to do it with their eyes really wide open.

Jim Marous (35:12):

It's so interesting because the foundation of the banking industry is built on trust. And when you look at the potential for AI, it can make it so that the financial institutions, can be even more trustworthy than they ever have in the past, because if you're providing value in response to using data and value being maybe faster solutions, better solutions, more personalized solutions, that makes it so that trust will actually go up and make it so the whole process is easier.

Jim Marous (35:47):

But we continue to see financial institutions stuck on stop, for lack of a better term, on a hamster wheel of some sort, talking a lot about what's potentially able to be done, but really being all over the place on how to implement and actually not going forward. Certainly, not as well in the customer experience space as they are in the risk compliance and fraud space.

Jim Marous (36:10):

So, in both your situations, if you were going to a mid-size financial institution and be the head of marketing, the head of customer experience at a mid-size financial institution, what is the very first step you would recommend yourself in that position to do?

Caleb Johnson (36:28):

That's a tough one. Chris, you want to start?

Jim Marous (36:33):

That was fun.

Chris Dolan (36:36):

So, saying that everything is taken care of from a governor … like they've put the framework in mind, the business has decided what they're going to be doing in terms of the risk and reward, risk and ROI then I would say the first thing that I would look at in terms of being able to use AI in a way that is advantageous to my business would be more in the world of helping my contact center agents today so that I can start to build a database of understanding of what my customers are asking of me.

Chris Dolan (37:17):

If I can understand what my customers are asking of me, then I have a path forward to actually address the biggest needs or the biggest concerns that my customers have. That's the direction I would take to move forward.

Caleb Johnson (37:34):

No, look I think you're spot on and my thoughts not too far from where you're at in that, from the first step type of thing, what we're finding is that companies that are being successful at deploying some of this innovation have gone in and they have centralized a group of people that are responsible for actually going and finding use cases and deploying it.

Caleb Johnson (37:54):

So, it's not about so much going and taking the first action, hey, we're going to go and take this single process and let's just go do that as your first step. It really is enabling and empowering a group of people, somebody that's accountable for it, that's going to own innovation for this type of thing across the business.

Caleb Johnson (38:11):

That will allow you to actually go start collecting the use cases, putting plans together and executing on it. But if it's not an organized initiative that's been empowered from the executive layer down, then there's a good chance you're going to be in the same spot a year from now still talking about it, and you haven't actually executed on anything.

Jim Marous (38:30):

Yeah, and I'm going to go one step further and say, most of these organizations can't do it by themselves. They probably can even define their North Star with regard to AI by themselves. We have so many exceptional solution providers in the marketplace, TTEC and Cisco being two of them at the very top. You have a tool, you have a workshop process that helps them understand where they are, where they need to go, and how to unlock business value.

Jim Marous (39:02):

Shameless plug on your behalf’s, but I think that the first thing they should do is take advantage of the workshop that we referenced in the episode notes and move forward in trying to find out what they don't know before they try to set a stake somewhere and say, this is what they're going to do. Because you have 40 people in an executive suite, 20 people in an executive suite, you're going to get 20 to 40 different answers as to where to start.

Jim Marous (39:28):

I think this helps move the process forward in a way that builds on your experience that you've already had with a number of financial institutions who were in the same space before they were. So, I think that's a good way to go about it, at least.

Caleb Johnson (39:43):

Yeah, you're spot on. It's a pretty easy risk-free conversation to get people aligned and get a strategy going. And the nice thing is, like Chris and I get to have a lot of exposure to a lot of different industries, not just financial institutions. And so, you can start to bring in kind of best of breed from a lot of different viewpoints on how to go, what's been successful, what hasn't been successful. You get the advantage of not having to run into some of the same walls that other companies have as the result of our experiences.

[Music Playing]

Jim Marous (40:13):

Yeah. So, honestly, if you're serious about turning customer experience into a competitive advantage, now is the time to act. Explore TTEC's digital interactive workshop to help you define your top customer experience priorities, identify where AI can make the biggest impact and build that roadmap that not only can refine your thought process, but deliver results.

Jim Marous (40:37):

Again, I'll say it again, for more insights into the future of banking and an AI driven world, also, don't miss my recent presentation I did in Abu Dhabi where I unpacked what's next for financial services. Thank you both for joining me on the Banking Transformed Podcast.

Caleb Johnson (40:53):

Thanks, Jim.

Chris Dolan (40:54):

You're welcome. Thanks, Jim.

Jim Marous (40:58):

Thanks for listening to Banking Transform the winner three international awards for podcast excellence. If you enjoy what we're doing, we would really enjoy a positive review. Also, check out my recent articles in The Financial Brand, the research you're doing for The Digital Banking Report.

Jim Marous (41:13):

This been a production of Evergreen Podcasts. A special thank you to our senior producer, Leah Haslage, audio engineer Chris Fafalios and video producer Will Pritts. If you want to hear more about the Debbie Platform and how can boost engagement by rewarding positive credit behavior, check out our previous discussions with the Debbie Founders on the Banking Transformed Podcast.