From data to trust: Why banks must get personal now

Caroline Béguin: So why do you think personalization has become such a key expectation for today’s banking customers? 

Andrew Steadman: Well, I think what we see in other industries is data being used to personalize service to a level that is actually impacting the customers. The experience is good. It feels like you’re understood, and I think financial services needs to catch up and use the data that’s available. I think we’re in a fairly unique position within financial institutions about the sheer amount of data we have. We have all your transactional data. Legally, we need to capture a lot of demographic data about you to ensure compliance with things like AML regulations. But really if I can understand that data and what it’s telling me from a financial institution’s point of view, I can actually offer products and services to that customer that they value, which will support their aims, their goals, their ambitions in life, and not just be a transactional relationship. 

Caroline Béguin: So how do you explain the pain points that prevent banks from having to catch up? 

Andrew Steadman: I think one of the biggest challenges for banks is where their data lives and how they can get their hands on it. Banking systems are complex. Data resides in many places, and it’s often very difficult to get hold of that data. And the big challenge, I think, moving forward is bringing that data together and being able to use it at the point of need. And of course, as customers, we don’t typically tell you when we’re gonna log on to our online banking app, we just do. And so I think the historic approaches of putting it in a data warehouse, crunching the information overnight and sharing it the following day, no longer apply. I think data lakehouses and in the future, data fabrics are going to be essential in order for a bank or financial institution to bring that data together, but then use it in context when the customer arrives at a channel. 

Caroline Béguin: Can you share an example where data-driven personalization led to stronger customer loyalty or growth? 

Andrew Steadman: Yeah. I think a good example is in activity around collections. So if you think about where a customer has gone into arrears and, you know, there’s a problem with the relationship, a traditional approach for a bank was to ring up and say, “Give me money, give me money, give me money.” And the idea of that collection approach was to recover the debt for the bank. I think where we see financial institutions using the information to tailor the conversation with the customer, understand their circumstances, and build a repayment plan that’s much more aligned to them as an individual, you can actually come out of that collections activity, which is often a negative experience, with a positive relationship, because the customer trusts you to do the right thing, you’ve helped them through their period of difficulty, and you come out the other side stronger. It’s like any relationship, you know, if you take away from banking, think about personal relationships, they will often have friction at times, and the way in which you get through those is being open, being honest, and communicating and understanding each other’s positions. I think the more financial institutions can do that, the more trust they will build up with their customers, and even through rough periods, the relationship remains strong, even though there’s a degree of tension. I think we see the relationship with the bank, you know, traditionally it’s been just very transactional, but I think there’s a role for the bank to play to help people through their financial journey, and the role of data becomes critically important in that. And so, yeah, for me, collections, I think there’s many examples where you see collections, if it’s done right, the relationship is stronger on the other side. Because most people who have financial difficulty today may well continue earning well into the future, and if you’ve got rid of them as a customer, you lose that future value. 

Caroline Béguin: I like the comparison with the relationship. 

Andrew Steadman: For me, I think it’s, we use the word banking relationship, right? 

Caroline Béguin: Yeah. 

Andrew Steadman: And it’s probably one of the longest relationships you have, right? How long do people stay with their bank? 

Caroline Béguin: Yeah, true. 

Andrew Steadman: It’s often a very long time. I mean, I think of my parents, of course, in their era, it was all about I chose a bank and I remain with them for life. Probably the longest relationship you have type of thing. But in the modern world, I look at my daughter who’s 25, she’s looking for something more. She doesn’t just choose a bank. She will move banks if she gets better service. And so I think technology is enabling her to move more easily but also technology is available to let the banks do a better job if they can. 

Caroline Béguin: So how can banks balance the need for data with the need to maintain customer trust? 

Andrew Steadman: To me, the whole issue about trust, it’s, again, think of personal relationships, right? It’s about being open and honest and communicating, and that builds trust over time. I don’t necessarily need to agree with you to trust you, but trust is not something that people typically get immediately. You have to earn trust. I mean, that’s the expression, right? And that is typically done through behavior. It’s demonstrating that you’re doing the right thing. Looking out for the customer. You’re using the information they give you responsibly and to the benefit of the customer. And I think all of those things over time build trust. And of course, once banks have trust, maintain it, right? It’s not a point of time thing. Once I’ve got it, it doesn’t mean to say I can’t lose it. So I think they need to think very carefully about how they show behaviors to build trust and then maintain it. It’s like onboarding with a bank, it’s almost like courtship. You’re getting to know each other, right? You decided to go out on a date, you’re getting to know each other, and over time you learn to trust the other person. Same thing. 

Caroline Béguin: So what are the biggest risks if banks fail to be transparent about how they use customer data? 

Andrew Steadman: I think there’s two things. I think you lose that trust very quickly, and also customers will not be willing to give you the data in the first place. So I think you have to demonstrate very clearly how you’re using it, how you’re using it in a responsible manner, what you’re doing with it, and also showing the customer that there’s value for them in sharing that information with you. So if you use it properly and do the right thing. I think we see, a lot of times where the response from a financial institution is, “No, you can’t have that.” The immediate question is, well, why not? It’s really important, that’s the communication element of the relationship, that financial institutions explain why they’ve made a decision, right? Potentially I’ve said no because based on what we know about you, we don’t believe you can afford this loan and it will put you in financial jeopardy. We don’t think that’s right, therefore, we’re protecting you. I may not like the decision, but I trust that it’s the right decision. And I think that’s the element of where banks need to get to rather than just saying, “No, you’ve had your loan declined.” Because that makes you feel a negative experience, whereas I think if they approach it properly and explain why it wasn’t appropriate to give you the loan, you sit there and think, “Okay, they’re looking after me, even though I don’t like the fact they’ve not given it to me, I understand.” And I think that’s gonna be the key element moving forward, and particularly with AI, right? When we see AI being used more and more by financial institutions, one area where they’re still hesitant is where it impacts the customer because they need the explainability. AI that operates in a black box is very difficult ’cause I can’t just say, “The machine said you, said no.” I need to be able to explain why. So I think as we see the evolution of explainable AI, it’ll be much more prevalent in the industry, particularly for customer interactions. 

Caroline Béguin: Also, AI requires regulations, and regulators play a big role in the banking activities. So how do regulations help or challenge banks in their personalization efforts? 

Andrew Steadman: So I think they sometimes do help actually. Most regulations, of course, are always seen by a financial institution as a headache, something that is a burden. But I think we have a good example from the UK, where the UK regulator implemented some consumer duty legislation, and effectively that consumer duty legislation required the banks to do their due diligence about individuals and provide a focus on ensuring that the customer could afford what they’re buying. It wasn’t gonna put them in financial difficulty. They understood it was more them being a bit more proactive than they had been in the past. The banks obviously resisted it ’cause it was new regulation, it would have new costs. But interesting, there was a report published recently that showed, as a result of that consumer duty legislation, customers trusting their banks more because they’ve been more open, they’re visible of what they’re doing with the data, and therefore customers are saying, “Okay, yeah, I understand you more, I trust you more.” And I think that openness and honesty is really what’s critical to ensure that you can build a proper relationship that evolves over time. And again, it’s not a one-time thing. It’s something you have to continually evolve during a relationship, pretty much like a marriage. And so I think the banks, whilst regulation is there for a very host of reasons, to protect us, to protect the industry, to protect economies, the way in which banks apply it, are open about applying it, I think I don’t see it as a hindrance at all, really. You know, if you think of GDPR as a good example, when you collect data, you have to be explaining what you’re going to use it for. Well, if, if your bank says to you, you know, “I’m gonna make you financially healthier if you can supply me this information,” it’s why would I not do that? You know, if you’re gonna help me. And I think that’s the thing, the perception is they’re gathering it for their own benefit, not my benefit. And if they can turn that round, I’d share a lot more information. 

Caroline Béguin: Okay. We were talking about artificial intelligence, and I was wondering how it can be used for today’s personalization, and how can banks ensure that AI-driven recommendations are both effective and understandable for customers? 

Andrew Steadman: Yeah. So I, I think dealing with the last point, the understandable piece has got to be explainable AI. That technology, I think, is gonna be really key to be able to say, “Here’s what we suggest, but here’s why we suggest it.” And I think that becomes really important. In terms of how it can be applied, I think it can be applied in so many ways. As a tool to guide me through my financial journey. There’s loads of data available, all the information that a bank holds, all the information it can obtain through open banking. I mean, even arguably the information it could obtain from my social media. You know, if you think about people who travel, they post their holidays, tells you something about the individual. So I think gathering all this data together is really important, but then applying it in the context and saying, “Okay, what are you trying to do? Well, I’m trying to figure this out.” I think that’s where AI becomes really important, to be able to look at all that data and interact with it at that point of need, and be able to help the customer be guided into the financial strategy they want, if that’s the right word, but to achieve the financial outcomes they’re looking for. 

Caroline Béguin: I’m curious to have your opinion on this one. So at which stage of the customer journey, whether onboarding, engagement, retention, or loyalty, do you see the greatest opportunity for impactful personalization? 

Andrew Steadman: I think all stages. Like, you know, I mean, I mean, it sounds like a bit of a cop-out. But I think, again, you think about a relationship, there’s no one point in that relationship that’s more important than another, right? It’s all about being personalized all the way through. And I think, you know, at onboarding, yes, there’s personalization in a particular context, but equally 10 years later, when, you know, somebody has their first child and they’re thinking about how they’re gonna pay for schooling, it’s a different context, but it’s equally as personal. And so I think the trick is not necessarily specific points in a journey, it’s about using the information that I constantly learn from the customer to guide those future conversations. So, you know, we’ve all applied for an account with a bank we already bank with, and the first thing they do is ask you for your name and address on the form. And you think, “Well, they know my name and address. Why are they even asking?” That’s a simple element of data. But if you think about all the behavioral information you’ve had from me over the years, you better understand me, right? I mean, if I think about my bank account, you will have seen me paying for nursery fees. You will have seen me paying school fees. You will have seen me sending money to my daughter while she’s at university, and now you don’t see me sending her any money at all because she’s working on her own, and every now and then she rings up and says, “Dad, can you help me with something?” There’s a pattern there, and you can understand that pattern because it’s a very common pattern. So if you look at your database of customers, you’ll see that pattern over again. But it also would help you understand where I am on that journey. Using that knowledge, you can then support me, but why wouldn’t you say, “Has your daughter just left university? Does she need some help?” Why not establish that personal relationship with her as well as me? And so I think the opportunity’s there for banks to constantly reinforce the strength of the relationship, the trust in the relationship, by applying personalization when it’s appropriate on that journey through, through life.

Caroline Béguin: Where do you think the line is between helpful personalization and being too intrusive?

Andrew Steadman: I think it can be a fine line and a difficult one. I think when it becomes obtrusive is where it starts leaning more heavily towards the bank’s agenda rather than my agenda. If I see you trying to help me, then I don’t think it becomes intrusive. I think it’s, “Okay, that’s really interesting, but not today.” But if I see you trying to push things that are your agenda that don’t really quite fit me, then I think that’s where people feel it’s intrusive, and I think you have to be careful there, right? You know, I think again, I think back to my days at Bank of America, it’s a good few years ago now, but we’d moved to the US. Of course, we had no credit history, and I didn’t have a credit card because obviously I couldn’t get one. My salary was going into my Bank of America bank account, and they would periodically send me credit card applications saying, “You’re pre-approved for a credit card.” And so I’d say, “Okay, I’ll have one.” And they’d go, “Sorry, can’t approve it.” Clearly, it was their agenda, right? They wanted me to have a credit card. But yes, it would’ve helped me enormously, but then they’d take it away and say, “Actually, we can’t approve it.” And it was only after we’d been there six months and they said, “Oh yes, you can have one.” But that type of thing, it was pushing their agenda. They knew how long I’d been in the country, but they didn’t use that information. They just went down the route with their agenda, and I guess that was what? 20 years ago. And I’m recounting that story here because it was stuck with me. 

Caroline Béguin: So what would be the advice that you would give them if they were starting their journey toward responsible data-driven personalization? 

Andrew Steadman: When you look at it, people think, “Oh my God, it’s a big thing.” So I think the first thing is get your data in order, ’cause without the data being accessible and usable, you’re really gonna struggle. And then it’s a question of starting small. Focus on one area where you can help. Use that to drive that personalization and test it, see how it goes, and grow from there. I think if you try and do too much too soon and bombard the customer and jump into it, that can feel a bit intrusive. Whereas I think if you step in and say, “Oh, you know, this seems to be happening. Would you like some help? Oh, if you continue in this path, you’ll probably be overdrawn at the end of the month. Do you want some help with that?” “Oh, I didn’t realize. Oh, thanks very much for letting me know. I’ll need to just curtail my spending for the next week or so.” So it’s that, that’s how you gain trust, right? Just small, helping, guiding, and it builds trust. Once you’ve built trust, the more trust you have, the more you can step in and say, “We think you should do this,” or, “We would like to do this for you,” or you can step in more fully. But I think if you haven’t got your data in order, it’s really difficult to do any of this. And also I think people are often jumping into AI ’cause it’s the answer to everything. Not sure it’s the answer to everything, right? It potentially can solve a lot of things, but it’s not always the right tool, and I think that’s the other thing that banks need to be careful of. I was talking to one of our clients this week at Summit, and they’re beginning to see a challenge whereby they have so many AI agents, they’re struggling to manage them all now.  And they don’t know which ones actually are valuable to the business as opposed to which ones are just being used ’cause you can use an AI agent to do it, but actually it’s driving more cost to the business. So I think you just need to be careful and start with the data, start with a focused use case, and start growing from there. 

Caroline Béguin: Yeah. Thank you, Andrew, for sharing your insights and being with us. 

Andrew Steadman: You’re very welcome. Thanks for inviting me back.