What if your bank could recognize that you needed help before you had to ask for it?
In this episode of Business Technology Perspectives, I speak with Michel Jacobs, Chief Strategy Officer at CSI, about how artificial intelligence and customer intelligence are changing the relationship between financial institutions and the people they serve.
Community banks and regional financial institutions have traditionally competed through personal relationships rather than scale. But digital banking, fintech competition, and changing consumer expectations are putting that advantage under pressure. Michel argues that the future of banking will increasingly be defined by interactions rather than transactions.
That means understanding why a customer is contacting the bank, what may be happening in their life, and which service could provide value at that moment. It also means preparing for interactions initiated through APIs, open banking services, and AI agents, rather than assuming every customer journey begins with a person opening a banking app.
Michel explains how CSI’s Customer Intelligence Suite combines transaction information, card activity, merchant category data, and digital behavior to identify signals and changing patterns. According to Michel, these signals can help a financial institution understand when a customer’s circumstances may have changed instead of relying on the demographic category assigned when the account was opened.
This creates opportunities for relevant financial support, but it also introduces serious questions about privacy, consent, accuracy, and customer trust. Inferring that somebody has changed jobs, bought a home, become a parent, or encountered financial difficulty can be useful when the response genuinely helps. The same capability can feel intrusive when it produces poorly timed sales offers or conclusions the customer cannot question.
We discuss how banks can balance personalization with regulatory responsibilities and why younger consumers are less likely to remain loyal when a provider offers little practical value. As Michel puts it, the era of offering everybody the same account and throwing in a free beach ball has probably run its course.
Customer retention is another major part of our conversation. Michel explains how declining digital activity, money leaving an account, late payments, or changes in income can reveal that a relationship is weakening. Used responsibly, this information could allow a bank to offer assistance before missed payments or financial strain become harder to address.
For community banks, the answer is unlikely to be copying every product offered by the largest global institutions. Michel believes they should decide where they can provide distinctive value, then use technology and data to support that position. CSI’s stated aim is to give smaller financial institutions access to customer analytics capabilities that would otherwise require considerable internal investment.
Can AI help banks become useful partners in their customers’ lives without crossing the line from personalization into intrusion? Listen to the conversation and share your thoughts with me.
[00:00:00] The leading issue of agentic AI in businesses right now is ensuring agents act with compliance guidelines. And Denodo applies guardrails across your entire data estate. By aligning your company's data infrastructure under one system, these guardrails perform consistently across your platform. So start scaling your business and start with Denodo. Simply visit denodo.com to learn more.
[00:00:29] What if a bank could spot that your finances were under pressure before you even missed a payment? Then contact you with help rather than another generic offer. That possibility frames today's conversation because I'm going to be joined by the Chief Strategy Officer at CSI.
[00:00:49] And together we're going to examine how AI-powered customer intelligence could help community banks turn transaction data into timely and relevant support. And he will explain today why banking is moving from transactions toward interactions and exactly what Gen Z expects from financial providers. And it's a lot different from previous generations.
[00:01:13] And we'll also talk about how smaller institutions can compete without matching the spending power of some of those global banks. And we'll also discuss everything from personalization, privacy, open banking, agentic commerce, and why that trusty free beach ball has probably reached the end of its career as a customer retention strategy. I think we all want a little bit more than that now.
[00:01:38] So if your business has plenty of data but struggles to act on it, this episode should give you plenty of useful ideas. Well, enough from me. Let me introduce you to my guest right now. So thank you for joining me on the show today. Can you tell everyone listening a little about who you are and what you do? Sure. Michel Jacobs, born and raised in the Netherlands. Grew up here after my Dutch Air Force time in the international retail payment space. I was involved in the early innovation.
[00:02:08] I was part of the team that did the Festa Payment back in the days in 2007. Moved to the U.S. in 2000. Joined the U.S. payment space. I got head on in a company called eFunds, which became part of FIS. Spent 10 years at a variety of roles in FIS, both large core banking platform as well as community bank strategy, as well as enterprise product strategy. Did it for 10 years.
[00:02:35] Left, spent four years in the international corporate transaction banking tech space. After restructuring that company, I joined a next-gen core and digital company out of Argentina called Technicis. Laid out a product strategy. Hired a team, brought them in the U.S. After two years, we sold that to SoFi, which is now the underlying SoFi tech platform. Happily rolled into early retirement, enjoying my grandkids and restoring muscle cars, which is my passion,
[00:03:05] until the CEO of CSI, which is a close friend and old colleague, harassed me out of retirement, and here I am.
[00:03:39] Wow. What does maintaining meaningful customer relationships, what does that look like here in 2026? You must have seen so many big changes. It's been a very fundamental shift. I would say the biggest driver that's been influencing the shift, it's the underlying shift in a societal fabric in the U.S. Gen Z has a far-reaching impact on everything that happens.
[00:04:07] It has a far-reaching impact on brand loyalty across any industry. It has a far-reaching impact specifically in banking on willingness for people to shift brand if you can't provide value in a daily lifestyle. If you will, one of our overarching theme in our strategy, Neil, is how do we enable our community banks to become a more integral part of the customer lifestyle? They've always been a part of the community, but they were more typical transaction-oriented.
[00:04:37] And what the shift in the societal fabric, if you will, the demographic requirements are, is that for them to provide value to their lifestyle, we need to give them the tools so they can actually understand what's happening in somebody's life, so they can optimize and maximize the interaction and, by extension, the execution of value for their customers. And I think for years now, banking has been centered on transactions. That's how many people listening will view banking.
[00:05:05] But one of the things that interested me about you is you've spoken about the shift towards interaction. So what's driving that change? Is it Gen Z or something else? And why should financial institutions maybe rethink how they're engaging with their customers? It's a dual-folded fact. So the first one is directly related to what we just talked about, Neil, which is the shift in Gen Z influence, if you will.
[00:05:33] But it started a little bit before, which is if you take a step back, and again, much more earlier adopted internationally than in the U.S., just a shift in society from a willingness to adopt change, if you will. But, you know, the future of banking is not about executing traditional transactions in the traditional channels. It's about managing customer interactions. And that has two impacts.
[00:06:00] Number one, it has to be about, it's not just about the what, but the why. If you understand the context of the interaction, then you have the insight so you can ensure as an institution you can optimize and maximize what the result of that customer would be. And the second thing, managing an interaction doesn't mean it's a human interaction by means of web or mobile. It is very much, if you think internationally, the drive could be agentic commerce. It could be open banking, right?
[00:06:29] If you take, for example, when I was a technicist, a lot of our strong customers and wide adopted were in South America, specifically in Brazil, where open banking called PIX is far reaching a mandate about a government. 48% of every interactions was API based, not necessarily human and web mobile based. So combine that together, it's being ready that interaction could be machine driven, not necessarily human interaction driven.
[00:06:58] And B, whether it's machine or human, we have to understand the context of the interaction so that we have the insight to ensure that the right service or the right capability is offered at the right time and need in that channel of desire. And financial institutions also sit on vast amounts of customer data, but many have traditionally struggled to turn that data into action. I would hope that AI is making that a bit easier now.
[00:07:26] But what would you say are the biggest barriers preventing banks from extracting real value from all that data that they already have? It's a little bit of a change in culture, but also an ability to enable it by means of technology. So if I, for example, look at CSI, we've evolved from your traditional world of regulatory reporting and BI reporting into data insight. So Dell starts with data is the new gold, Neil, right?
[00:07:54] So we have an enterprise data lake that allow us to store and record all of our banks, customers, transactional activity data. It also allow us to store all of the customer card activity level data, which includes level two, level three merchant category type data, as well as digital behavior data. And it's that aggregate of data that would allow us to use technology tools.
[00:08:22] And AI is a perfect example of that to start really going through that data and extract what's happening in somebody's lifestyle.
[00:08:30] So, for example, if I would see that a customer would have been shopping at, let's say, babies or Ross, Neil, and with a high degree of certainty because of the merchant category type product category and a product type data, we can see what a high degree of certainty that they've been procuring, if you will, baby products or baby goods for the last two months.
[00:08:54] Because we know with a very high degree of certainty that he or she has just became a proud parent. That insight allow us not only to ensure that if a bank would resell, let's say, a student financing program for college, that they can offer it at the right time. Because remember, the oldest rule of conversion or sales is the right product at a time of need and a channel of desire.
[00:09:18] But more importantly, it allows a bank to actually have a dynamic view of what's happening in somebody's lifestyle. Do they have a job? Do they have a promotion? Do they get a house? Do they get a divorce? Do they have children? All of that is important so that the bank has the insight based on the data and based on the technology to ensure life is dynamic. It's not static. Right.
[00:09:42] So we have to ensure that the data gives the financial institution the insight to adjust their interaction and adjust the appropriate products that fit the changes in the lifestyle of a consumer. And before you join me on the call today, I was doing a little research. And one of the things that stood out is CSI recently launched its customer intelligence suite to help banks turn some of these everyday customer interactions we're talking about into AI powered insights.
[00:10:10] So tell me a little bit more about the platform, how it works, and maybe some real world examples of how it is helping banks anticipate some of those customer needs in real time. I think it'd be great to bring this to life, what we're talking about here. Yeah, it's a little bit in summary of what we just talked about, Neil. So the data lake will give us a vast amount of data to have that insight.
[00:10:35] So it's not just the account transactional data that gives the insight, you know, who bought what type of product and what type of value and where. The merchant category type data, the procurement debit day by day, if you will, that gives us a lot more granular insight to say, hey, but what type of product did he or she buy? And then what type of product store did he or she buy that?
[00:10:59] You can then overlay that with digital behavior data so we can see how are people behaving across the digital channel. It's that combined insight, that data that will allow us to assign signals, right? Signals will allow us to attach specific category. Hey, something's happening with that data, with that data.
[00:11:20] And AI is a tool where we use for customer intelligence, we need is a perfect, powerful tool that will allow us to infer based out of signals. Hey, what's happening in his or her lifestyle? And the most important is not only that allow us to say this is happening in the lifestyle and therefore you as a financial institution will now have the insight to ensure that you can have the right offer or capability that matches the need of the customer.
[00:11:49] But more importantly, it allow us to assign those behaviors into a demographic category. And that would allow us, more importantly, to also allow a bank to dynamically adjust demographic categorization. Because the historic challenges that bank had, if you would open up a, same goes in the UK, if you would have opened up a bank account with, let's say, you know, Lloyd's. And you open it up when you were 28 years.
[00:12:20] During that opening day, assign you as near you in some form of demographic category, however their marketing have joined it. That typically never changed. You could have been 20 years further, had bought four houses, moved to a different country, had three divorces, 10 children, a big school bus, driving them all around, Neil. And the bank had no idea what changed in your life.
[00:12:42] So data, the insight and the tool will give us the power with customer intelligence suite to give our community bank the same capability that very large super regional banks or the biggest global banks like Bank of America and Chase have built years of investment around historically to build that analytical insight and a capability.
[00:13:02] So AI is bringing us at a very even ground and allow us as a technology and a service provider to our community bank to give them the same capability so that they actually do have the insight. And more importantly, as a community bank focus on a community to be truly part of a community by understanding what matters to the people in the community so they can optimize and maximize the value to them.
[00:13:29] And personalization has become an expectation in just about every industry from retail, entertainment and e-commerce is an old line. Our last best experience we have anywhere becomes that standard expectation for what we expect to see everywhere. And I suppose when we look at Amazon knowing what we want to buy, Spotify and maybe knowing what we want to listen to and Netflix knowing what we want to watch.
[00:13:52] How can banks deliver that same kind of relevance but also while maintaining trust, privacy, not being too intrusive or creepy and also meeting regulatory compliance? It feels like the stakes are a little bit higher here. It is very much.
[00:14:35] It feels like the stakes are a little bit higher. And if you have a lot of competitors and people who have a lot of competitors, people switch brands quicker, right? And you can even see that back in history. The ability for people to switch the hurdle is no longer that large anymore. So what's really important when you bring all of that together is that, you know, within the guardrails, if you will, of regulatory compliance and what the bank does with the privacy data, Gen Z expects that you have the ability,
[00:15:04] based on that insight to ensure you understand what matters to them and you have the right offer. I mean, simply stated, the days, Neil, of saying open up a bank account, it's spring and we'll get you a beach ball for the summer. Those days are over. That doesn't count Gen Z anymore. They're expected that you will have the insight and have the appropriate offering. That means don't give me a cookie cutter product for everybody else. The product
[00:15:33] better be adjusted to match what I need and my lifestyle at a time that I'm interacting with you, which could change over time, but it better be personalized to what is value for the consumer and what they perceive as value to the lifestyle. And I have read that many community banks sometimes worry that AI could create a distance between them and their customers. But from what you're seeing
[00:15:58] here, how are you seeing AI strengthening human relationships rather than replacing them, particularly in financial services, shall we say? I'd say that loyalty is driven by a joint relationship and more importantly, driven by value in a relationship. That makes sense. Loyalty in an airline is about, I have value out of my loyalty relationship, which is why I keep coming back to the airline and I'm
[00:16:26] building on my reward point because there's direct value to me. If my financial tuition has no value for me, it's basically an interim hotel for my deposit accounts and then my salary check goes anywhere else. There's been a history that people will switch into those financial institutions. Originally, a lot of the fintechs that actually do cater more to the younger generation. In the UK,
[00:16:53] you've got the examples with Monzo, right? You have the example with Chase in the UK. A lot of the earlier fintech banks came in the UK. Now, we all know they had lower balances than high street banks, but they actually addressed the need of the younger consumer by providing the right value, not a kooka-kooka or the same for everybody. That same motto reflects back everywhere in the US.
[00:17:18] And it's actually, you know, societal shift is a global phenomenon. It's not a US or a UK one, right? So even though it traditionally idled a little bit longer, like, you know, open banking was years ahead in the UK than it was even contemplated in the US, frankly. But having said that, that shift becomes very important for community banks so that we can use technology and AI
[00:17:42] capability to give them equal footing so that they have the ability to not only provide that insight, but more importantly, as a community bank, to actually know the community, they need to know the people within the community and what matters to the lifestyle. And that is the lifeblood of a community bank to not only address on the business banking and have the right to win and to be the enabler of SME, which is the backbone of US commerce across all of the states, but to ensure that they can
[00:18:12] provide that equal value and insight to each and every one of the communities and the members that live within the communities so that they have the right offers. And I suspect most people listening will agree that customer retention is becoming equally as important as customer acquisition, if not more so. So what would you say are the most effective ways that banks can identify some of those early warning signs that we've talked about today that the customer relationship is beginning to weaken and
[00:18:39] take action before it's too late? Are there any big warning signs that you see very often here? The data will allow you to detect signals and trends months before they become an issue, right? Whether those are late payments, whether they're declining engagement on the digital behavior, seeing there is a deposit flight happening, you know what I mean? So that literally the bank account
[00:19:05] just becomes a parking ground for a direct deposit account that then it moves out. Or you can see that, you know, if their income suddenly drops substantially in comparison for their payables and their loan obligations and their forward schedule payment obligations, then it gives the bank the insight to see if something happening in their personal life, there's something happening that we should be
[00:19:31] aware of so that the bank actually can come in. It's not only, hey, I cannot cross sell something, but if you see that something's happening financially, it is the job of a bank to be able to say, hey, what's happening? How can we help you? We can see that you have a shortfall or you're going to have a shortfall or we can see that you haven't been able to keep up with your loan. It's something there. The more we have the data and the insight to enable a bank to be proactive instead of reacting
[00:19:57] after the fact, it is the foundation for loyalty because in the end, the member true loyalty and customer retention is all about ensuring that you do the right thing when they need it. And that's what people will respect. Something will happen. Problems will happen in every relationship and every business and any service provider. It's the oldest rule in the book. It's how you act on it.
[00:20:22] How do you have the insight and how do you solve for it? That builds long-term retention and truly brand and brand loyalty. And looking ahead, it does seem inevitable that AI, analytics and customer intelligence are all going to be collectively becoming deeply embedded into financial services. So to give people listening a few actionable takeaways here, what do you think will separate institutions that thrive in that future from those that struggle? And what should a banking leader
[00:20:50] listening today? What should they be doing to prepare for that inevitable future? That's a really good question because there is so much noise and hype going on in the market, as you're aware of Neil, that it could be easily, you'd be overwhelmed, right? Also, whether it's the community banks in the US or whether they are some of the building societies in the UK,
[00:21:15] none of them have the capital and the intellectual capital needs to be at par with the chasers of the world or the HSBCs of the world, frankly, right? Having said that, it is about the leadership that understands how can they become that more integral part of not just a customer lifestyle, but also a business financial supply chain. They have to look at about how they can leverage data
[00:21:42] to provide that value. They don't need to be everything to everybody. They need to focus on where they really want to be good at because remember, everybody use technology, everybody uses electricity, everybody uses capability. In the end, it is how you establish yourself as a brand that determines your loyalty. It's about what you specialize in. And then how can you use that,
[00:22:07] whether or not that is related to traditional banking or enabling embedded finance where you provide your financial services in the fabrics of a fintech or a large enterprise customer, right? If you think about these days in a lot of international countries around the world, Neil, cars are no longer just a vehicle for transportation. They're actually a wallet, right? That means they are
[00:22:31] connected to your funding account. And the car manufacturer like to build a car standard that has all the gadgets in there. And after three months, you have to pay for it if you want to use them, right? So that type of capability. Then of course, we have a future that will include non-fiat-based money movement, right? Especially coming from Europe, faster payment was very early adopted in
[00:22:58] Europe, at a payment service directory, all this association with open banking. So we all know fiat money movement and how we can make it quicker. That's the whole notion of faster payment to begin with, especially in the birthday in Europe. We will have a future of non-fiat-based money movement. That's an integral part of it. Whether that's CDBC, which is mostly driven internationally or it's tokenized depositors taboo coin. The book is being written, Neil. We're in chapter one. Nobody knows
[00:23:26] how it's evolved. But it does mean for community banks and by extension for us as technology and service provider that we need to give them the foundation. We need to do the investment so that they have the ability to select what they want to specialize on, give them the data and the enabling capability so they can double down and differentiate as a brand, differentiate as a service organization, and differentiate as a financial integral part of somebody's lifestyle.
[00:23:54] Wow. I think that is a thought provoking moment to end on. And for anyone listening, whether they want to dig a little bit deeper on CSI customer intelligence suite, how that is helping financial institutions deepen customer relationships with AI insights, or just learn more about anything that we talked about today, connect with you or your team. Where would you like me to point everyone? Anybody who wants to learn more about CSI, just visit us at www.csiweb.com. And we are excited to
[00:24:24] engage and help the people to understand not only what we intend to do for our community banks, but what type of capability that we bring to them. Well, I, for one, have loved listening to you today talking about how AI is helping financial institutions strengthen relationships, boost retention, and drive long-term growth. That is the ROI there. And there's a lot of talk around AI and ROI right now. So I will add links to everything that you mentioned there, urge people listening to check that out. But more than anything,
[00:24:53] thank you for sharing your time and insights today. Really appreciate you. You're very welcome, Neil. I enjoyed it. And thanks for having me on the podcast. I think my guest argument gives community banks a very useful place to start. Treat customer data as a way to understand need rather than just another sad excuse for another sales prompt and generic offer. Because declining digital activity, deposit flight, late payments, and changing income could offer
[00:25:21] warning signs that somebody is in need of a little extra help. And the opportunity here is to respond before the problem grows, while also respecting their privacy and regulatory boundaries. And this balance matters because personalization becomes rather less charming when it feels like surveillance wearing a friendly logo. So a massive thank you to my guest for showing how customer intelligence can support retention, relevance, and stronger financial relationships.
[00:25:51] So I'll include links in the show notes for everything that we talked about today. But after hearing this conversation, maybe ask yourself whether your organization recognizes exactly what customers need today, or just keeps placing them in a category they occupied 20 years ago. Love to hear your thoughts on this one and how you're dealing with this issue, whether you're in the financial world or a completely different industry. As always, techtalksnetwork.com.
[00:26:19] That's where you'll find me and all my podcasts. And I want to hear from each and every one of you. So keep those questions and observations coming in, and I'll be back again real soon with another guest. Thanks for listening. Bye for now.