Banking on Data Products at Santander

During Big Data LDN, Claire May and James Pitchforth discussed how an accurate, enriched view of their customers is improving experiences and increasing customer loyalty at Santander.

We’re committed to your privacy. Tamr uses the information you provide to contact you about our relevant content, products, and services. For more information, read our privacy policy.

Oops! Something went wrong while submitting the form.

We’re committed to your privacy. Tamr uses the information you provide to contact you about our relevant content, products, and services. For more information, read our privacy policy.

Oops! Something went wrong while submitting the form.

Clean, trustworthy customer data that delivers results

  • Hear firsthand how Santander successfully navigated challenges in data quality
  • Learn how Santander is building on its customer success with forward-looking data product strategies
  • Gain practical advice on how to get more from your data stack through strategic partnerships

Clean, trustworthy customer data that delivers results

  • Hear firsthand how Santander successfully navigated challenges in data quality
  • Learn how Santander is building on its customer success with forward-looking data product strategies
  • Gain practical advice on how to get more from your data stack through strategic partnerships

No items found.

Rather read the transcript? Dive right in.

Speaker: Suki Dhuphar

Timestamp: 00:00:00

Good afternoon, everyone. Well, it's almost afternoon in four minutes time. Thank you for joining us today. In the data stacks theater. What we're going to be talking about today with my esteemed colleagues here. It's banking on data products and how Santander deliver clean, accurate and trustworthy data for corporate banking.

Joining me today. I have Claire May, UK head of business and change management for corporate and commercial banking. And James Pitchforth, who's the head of data management at Santander. So what I'm going to start with, I'm sure the audience is familiar with the brand Santander. Hope so. wHat will be great is for you guys to provide sort of what your roles entail, what you're doing there and, and, you know, just generally about yourselves.

So let me start with Claire.

Speaker: Claire May 

Timestamp: 00:00:47

Thanks, Suki. So hi, everyone. I hope you're enjoying the day. And thanks for coming and listening to us today. So as Suki says, my name is Claire May. I head up business and change management, but essentially that means I look after transformation change, anything to do with change programs, our data, we have continuous improvement, client experience in there. So really looking to make things better for our corporate and commercial clients. That's my role. Corporate and commercial banking. Sorry, I'm just going to move this a little bit. Oh, Corporate and commercial banking within Santander UK is part of obviously Santander UK. We look after businesses from two million turnover all the way up. We are part of Santander group. James? 

Speaker: James Pitchforth

Timestamp: 00:01:32

So hi, everybody. Good afternoon. My name's James Pitchforth. I head up data for a corporate commercial bank. My main responsibilities are really to nurture and govern the data that the corporate bank consumes and creates. We operate in Santander closely with a central data office, a central data function.

And inside of that, inside the CDO itself, there are several different directorates, all of which manage data. So there's a head [00:02:00] of data in each directorate. trees at the heart of everything that we do, and we try our best to make sure that we create an infectious data culture across the whole of the corporate commercial bank, but some UK wider.

Speaker: Suki Dhuphar 

Timestamp: 00:02:15

Excellent. Thank you very much, Claire and James. So hopefully the roles are cleared. So what we're going to talk about as we go through this is the journey that Santander are on. And as we know, with all these journeys, they're constantly changing, right? So, you know, like any other organization, you're having to constantly adapt to market needs, market trends, customer needs, technology, process, changes, regulation, the list goes on and on and on. But how do you bring your organization on that particular journey? Not just from a data perspective. We've had this conversation. Data is obviously important, but it's also people and technology and process that needs to follow.

How do you bring? How do you bring the organization on that particular journey? 

Speaker: Claire May 

Timestamp: 00:02:54

Yeah, thanks. And I think that's, you know, absolutely massive. We all know Change is constant. It's the only thing that we do know. And I think COVID, especially in our industry of financial services taught us absolutely heaps.

And the positives that came out of it was how quickly we can adapt to the change, how we can come together as a collective and really come to decisions quickly. And we've really tried to keep that ethos within corporate and commercial banking around actually if there's a problem that needs solved quickly, let's get together and embrace the fact that we need change.

Okay. Also just really establishing education at the heart. So you referenced things are changing all the time. We can't expect our people to just know what's going on and what's happening. So. We really focus on education, but at every single level. So, you know, just because you're in a senior position, there's some new technology hitting us really fast, and they won't necessarily know any more than, than, you know, someone in a more junior grade.

So we focus on all of it. We have a digital skills program that anyone can join. And they can get involved with solving problems, real problems for the business in a sprint format, which is fantastic. And consistently, James and I probably bore everyone in the organization, but we talk consistently about the power and the importance of data.

And I come at it from a, you know, point of view that if you don't understand how your data flows through technology, if you don't understand and own that data, you're not going to get any of the value out of it. So getting that data culture really, really strong, understanding the data flow and how it works with your technology.

And like I say, people complain about rubbish data and roll their eyes and data becomes like the dirty word. And we've tried to turn that on the head and just understand that if it's not the data team's problem or fault. This is an ownership thing that we all have to work out what the solution is.

Speaker: Suki Dhuphar 

Timestamp: 00:04:58

Absolutely. I mean, that's music to our ears to start off with, but it's absolutely true. I mean, it's the same with other organizations that we've worked with. We see that you have to bring everybody on the journey. It can't just be a set of individuals, a small group of people. a particular department.

It's everybody top to bottom and constantly sort of training and enabling them to, you know, move with the times, move with the technologies, move with the process, move with the changing world that we're in. And actually, just as a follow up question on that, we know that the world is moving and I'm sure there's a number of people sitting in the audience have probably heard of AI and machine learning.

I'm sure there are quite a few. How are you sort of educating your organization around these new technologies? I know you mentioned you have these sort of forums, but how do you actually sort of educate everybody to take them down that particular journey and to make them comfortable? Because I think that's the key thing.

The messages that you'll see constantly, AI, chat, GBT, large language models, Yeah. What does it actually mean to you? How do you educate your team and your leaders? 

Speaker: Claire May 

Timestamp: 00:06:02

Yeah, absolutely. Spot on. And I think if I start on the journey that we are on and have been on, so in corporate and commercial banking, we've been on our digital transformation journey for some years.

And about five years ago, we really turned that up and started to invest in cloud based technology. And that was really to take advantage of big efficiencies. And we also reorganized ourselves so that we've got end to end journey teams. So we really focus on what the client does literally from the moment they start solving that problem with us to the moment that we solve it for them. So we're organized in that way and we've, we've started, but as I said, we did.

We did really do a big change program during COVID. And what that meant was we implemented at pace and when people were at home and that did lead to us losing a little bit of hearts and minds, if I'm honest, and because on reflection, we didn't Spend enough time at the beginning thinking about data and we were getting really excited about the new technology and we got the new technology in and then everyone went, but it hasn't solved all our problems.

Well, no, it hasn't because we didn't solve our data problems and this new technology is amazing and it has amazing capabilities, but the, what happened was our people were like, where's the difference? Where is that utopia that you promised me? Right? So. If you've got that backdrop, you've really got a star.

And I talk again about culture. You've really got to think about the hearts and minds of the people that you've implemented that technology with, and we didn't do enough with the business. So we've gone back to basics. I talk about this data culture, but it's, it's wider than that. So technology is coming at us thick and fast.

I mentioned the fact that we need this to be through the whole organization and you can't have our leaders. feeling a bit nervous about talking about it. And I can talk about this from the heart because I'm new to data and tech. I'm a corporate banker through and through. I don't really know this world.

So when I joined the team, I sort of said, okay, talk to me in plain language. Talk to me in language that I understand. Talk to me in what problem are we solving with this technology or with this data that we're, we're wanting to do this with, with this data. And by doing that, It's meant that we then play that back to the business.

So we are all talking with a common language. We also arranged for our senior leaders to go off site, in a safe environment, ask any stupid questions, there were no stupid questions, so they could learn. And we just talked about Gen AI, we talked about AR, we talked about all the things that James was going to mention in a moment around data and the importance of data management.

And they got it. And we had a few light bulb moments. And what that's meant, Suki, is that they take that out to the organization, they take that out to their teams, and they bring to life what we're doing in the background. And that's the magic. 

Speaker: Suki Dhuphar 

Timestamp: 0:08:58

That is magic because I mean, making decisions when you're informed, it's much, much easier when you're, you know the debates are going on about Gen AI and everything else and they will continue to go on but making an informed decision allows you to at least make a a good decision right off the back of it.

So it's brilliant that the way you've walked through taking the organization on that journey it's been amazing. Hopefully people have learned from this as well as you've been talking about it. Moving over to Jane. Thanks. As we get sort of deeper into sort of that data side of things. I mean, I've, you know, recently a couple of quotes have really resonated with me.

From CEOs of Snowflake Frank Stute, Slootman. You know, data is, is a central part of making it. Getting data right. We'll make sure that you you're using AI correctly as well. You know same similar sort of sentiment from the Microsoft CEO such in the data. Data is really, really important to making sure that you can then use it for AI applications, Analytics, operational work, better customer journeys and also internal decision making. So as the head of data management sort of corporate banking, you know, what, how are you sort of leveraging data? How are you, what techniques are used, especially in the new modern world, right? That we're working in. What's the process you're going through, and how are you educating people?

Speaker: James Pitchforth

Timestamp: 00:10:16

That's great, and that's a fantastic question to be asked, to be honest, Suki. Before I go into the detail and give my interpretation of it and how I relate to the quote as well, I think I'd just like to... Spend a few moments reflecting on what Claire said because the data culture and the data awareness piece is fundamental to any data strategy.

You have to have everybody behind it so that everybody understands what you're trying to achieve and understand why data is so important to the end solution or the end goal. If I then look at the kind of context around those quotes that you said, a lot of those people have been talking about data, and then they talk about what data does.

The fundamental here is to remember that the start point is data. The data has to be good, and we all know in this world of data people that AI and machine learning is predicated on good data. If the data doesn't do what it needs to do, or isn't what it needs to be, then the outcome that everybody wants to happen Won't be achieved as maybe as well as it could be.

So we have to completely think about that. And in doing that, we need to then understand what we mean by data management. So data management then needs to enable smarter solutions, or smarter solutions need to be part of data management. So that takes me into then, so what is data management? So in the new world that we live in at the moment, our problems as data people are that there is just a lot of data.

Data is part of our lives. It grows with us. It breathes with us. It does everything with us. And our problem as data people is how do we control that? How do we use that? How do we maximize that? How do we take that with us and enable it to do what we  want it to do moving forward and create those smarter solutions to deliver great outcomes?

What we then need to think about is also, some of us in the room will work for large organizations, others might not. But those of us who work with big organizations or organizations that have been around a long time, we have that data concept of huge amounts of data. But that huge amounts of data is also part of a massive technology estate.

So the data that we want might be all over the place. It could be anywhere. And as data people, we need to be able to control that, govern it, make it usable, understand it, define it. And that is the new concept of data management. So data management has been around a long time. So it's not a new concept, it's been with us for a long, long time.

But data management in this L, where we've got huge, inordinate amounts of data that has been driven through a technology revolution, a data explosion, if you like. needs data management to work smarter. So I suppose when we think about it like that, what do we do? What, what capabilities do we have in the modern world to enable us to control and manage that data?

Maybe as modern data management. Or what does modern data management look like? And in doing that, what we can look at is, is some of the new capabilities that are out there in the world. And we can start to understand that, that, that problem, that, that concept, which is how do we harness that asset to drive smarter solutions, smarter behaviors.

And what we really need to do then is look at the foundations. So the core foundations of data management, I personally don't believe have changed. We need to look at the requirements. We then need to look at the definition of that data and the data point itself, understand where it comes from, and then understand where it needs to go, the lineage, the traceability and lineage of that data.

Once we understand that, we've got the core foundations. Equally, then we can start to look at how we match that data. So I've talked about data being all over the [00:14:00] place. How do you then connect that data? So it's all over the place in these great big technologies, these great big organizations. How do we understand where it is?

So as part of our requirement, we need to capture it and control it. We can use matching as a way of doing that. In the past, we've done it through logic. But why not look to more smarter, intelligent solutions to help us do it better. That then takes me into a concept called clustering. So if you've matched the data, how do you then maintain the data?

How do you make sure that you can not have to continue that matching process all over the time? So what you can do is you can cluster it. You can create a unique identifier, a unique key. Which if we think about, you know, master data management that is the whole concept of master data management. So again, this isn't a new thing, but let's use the new capabilities to be able to enable us to do that smarter.

Once we've got to that point, I believe that there is a way there that we can look at that stack, we understand it. We bring it under governance, we control it, we make sure we've got all the right things in place and we've tested it. Then you can start to enhance it so you can start to bring in more data, actually increase that big data stack with all that rich data that we're gathering every day.

And once we've done that personally, I think that's a point where you say, okay, as a company, are we ready? Or as an organization, are we ready to turn on things like artificial intelligence, machine learning? and other data science techniques. So, in summary, I suppose, in order to answer the question, for me, it's all about foundations.

If your foundations are strong, your building will get bigger, and it will get bigger and, and bigger through smarter solutions to create better outcomes. The things to be, to consider when you're going through that is very much what Claire's already referenced. So it's making the, making sure that the organization is data ready.

Are we ready to go on that journey? Is everybody lined up? Are the stakeholders, whether they're the senior stakeholders or stakeholders at all grades, ready to go on that journey with you? And then also do it in a responsible way. So you need to make sure that your methodology is explained, documented, is part of procedures, part of processes, and is done in a considered risk framework.

And for me, That is how you, how you take modern data management forward. 

Speaker: Suki Dhuphar  

Timestamp: 00:16:28

That's Excellent, James, and hopefully very insightful. I saw a lot of nodding heads, so you definitely were insightful. 

Speaker: Claire May 

Timestamp: 00:16:34

If I just, I was just going to add, just on the buy in piece that James just referenced there, if you think about any, any data management or program that you want to do, change program, you're going to need some money, and then you're going to need to implement it.

If you don't have that buy in, which is why those foundations are so important, You won't get the money in the first place, but then if you do manage to get the money, you've then got to implement it. You've, you've, you've got to just get that, get that right. It's, it's fundamental.

Speaker: Suki Dhuphar 

Timestamp: 00:17:01

No, absolutely. And then I can imagine that, you know, the problem just grows bigger and bigger if you're looking at it from a global perspective. So absolutely getting those foundations right off. It's such a critical piece.

And I know the journey that I've had with both of you. That's certainly been our talking point from day one, which is let's get the foundations right and the rest will follow as we sort of grow on that. Yeah, yeah. And, and talking about that journey on, one of the things that I've always respected about, and especially working, you've just mentioned it earlier on the fact that you've come from corporate banking into data, it's a brilliant view, a brilliant way of thinking of something.

You're just not just a data person because you're bringing that business view. That ‘What do my customers want’, that data for kind of view into, into play? And I know we share a common ethos of making sure that we have loyalty within our customers and give them the best possible experience that we can.

So what are you doing about that in particular? And I know we've had a long conversation about some of the techniques, but what are you actually doing about that to make your customers become even more loyal? 

Speaker: Claire May 

Timestamp: 00:19:01

Yeah, I mean, it's fundamental. It's why we're here. If our customers aren't happy and they're not continuing to bank with us, We don't have a job, we don't have a purpose.

So everything we do is around. Can we make this even better for our clients and our customers? And if you think about yourself as a consumer and how things have changed, we just, we expect that if we give our data, it will be used to give value back to us. I don't expect to give my data and then be asked for it again.

And for them to not know of what and do something with it. So that is now basic. That's ticket to the game stuff. That's not me doing anything special. And actually, if I don't do it, that's to the detriment of my clients. So that's number one. You've got to make sure that your basics are good, solid. And we sound boring, don't we?

We're talking about foundations again. Your basics are good. So that's all about your data quality and then how your data flows through and how you're using it. So we want our relationship teams. to be out adding value because we know that's where our customers want us. So everything we do is about how do we get more time for that face to face, virtual or real face to face?

How do we get more time for that interaction? Because we know from the feedback that that's, that's what they're looking for. They're looking for that guidance as they grow into another international country, or they take the first steps with an acquisition with a business. That's, that's our core. So. How can we use the data to help our relationship teams either from a back office point of view to process everything efficiently and beautifully or from a front office point of view to give them just the most amazing information to have brilliant conversations.

And if you do that, we will be wowing our clients every day. You know, that's the ethos. Then if you think about colleagues, how can we make their life amazing? And again, it can be through data. You can remove risks. You can increase in efficiencies, you know, all of those things and actually if you've got great engagement and colleague satisfaction Undoubtedly that's going to lead to smiling faces enjoying themselves and having a great time at work will translate into my clients love dealing with me Last week just a final point.

I think last week I was at a conference And I heard someone talk about, I've been talking lots about data driven, being data driven as an organization, you know, data first, what's the evidence, use it to our value. And someone turned that on their head a little bit and said, you know, we won't think of ourselves as being data driven, we'll think of ourselves as being data grounded.

And I just love it, and I've used it. I've talked to the team about it since I came back, that, that's it, that's the way we're moving because all of us will accept and just will be part of our lives. Gen AI will be part of our lives. Data's already here, in our phones, everywhere. And that's where we've got to sort of move that culture to, in my opinion.

Speaker: Suki Dhuphar 

Timestamp: 00:22:04

No, no, that's absolutely true. And more and more, especially like we're looking at the clients or customers of our clients they're smarter. They're looking at data. You know, they're looking at how much did I spend? What did I spend? Yeah. Where can I spend my next pound? My next dollar? We want to make more money, right?

Especially corporate banking. So, I love the idea that you've come from it, from a corporate bank. How do you see what you are doing impacting that customer experience and loyalty as well? 

Speaker: James Pitchforth 

Timestamp: 00:22:38

Again, that's it. That's the core of what we do. So if we think about it, my role in this is literally I'm client facing, if you like, I sit in a line one function. So essentially everything that I do is tailored against the client.

So for me, everything I've just talked about is about the client. So it's about how do you deliver better solutions for that client? How do you nurture that client? How do you provide more insight for that client? How do you create intelligence for that client? How can we work better as a bank for that client?

So for me, data is the engine. It's the thing that we need to nurture, develop, create. But it's all about the client for the good of the client. And that gives you a real purpose and an ability to create better solutions. Oh, that's brilliant. 

Speaker: Suki Dhuphar

Timestamp: 00:23:23

And I know, obviously, you don't want to share the information of our workshop, but that's exactly the way I've seen you think.

You know, it's a client in the middle, what can we do for the client? What data do we require to be able to build this kind of holistic experience? for the client. So that brings back to brings it back to the loyalty, the great customer experience, the what the customer is looking for. So, you know, it's brilliant to hear that.

And of course, it's going to be data, data grounded data. You’re data grounded from now on. Right. No, we're coming up to time, but I'm sure we've got 10 minutes, but I'd love to, I'd love for both of you individually to sort of  impart some advice to our sort of audience here just around, you know, how What they've got to look forward to as you're going through.

So, you know, you've given some great sort of tidbits about sort of seeing data grounded, looking at foundational. You said it's boring, but it's the absolute right thing for us to do, which is start from the bottom and work up. But looking forward, what what are the bits of advice, you know, guidance you can give the audience.

Speaker: Claire May

Timestamp: 00:24:23

audience here?

Okay. Yeah. So I'll start with, I guess, reflections and tips for me. So there are three main things and I've mentioned them already, but, getting the data culture right. So, if you've got a lot of data people talking data at your business, I hate to break it to you, but they're not interested in the technical terms.

I wasn't interested, and James, James and I have had a lot of laughs where I've literally had to say to him, stop, talk to me in English, so that I understand it, and then I can talk to the business about it, and. I can't stress that enough. I know I'm [00:25:00] really risking things here because I'm talking to probably lots of data people that love data and I love data too, but get your culture.

Think about your language. Don't make it too technical. And then the other thing that's close to my heart is think pain points first technology second. So constantly challenge yourselves to think what's the problem I'm solving? What's this going to make better for my customer? What's going to make better for my client and my, sorry, my colleague.

And I don't think you can go far wrong with that in terms of what I'm excited about. And genuinely, I must say that word a lot. I mean, people do laugh at me cause I've just become such a different person. I genuinely feel like we're on the cusp of something because we spent the time creating the foundations.

I hope to be back next year talking about actually some of this stuff coming to fruition that we're on the cusp of doing. I'm particularly excited by some of the conversations we are now having at all levels and the senior leaders really understanding that they're going to have to make some decisions pretty quickly, but that we've given them the skills and the knowledge to be able to do that.

So yeah, I'm, I'm excited about this next year. 

Speaker: Suki Dhuphar 


Excellent. We'll definitely have you back next year on this one. And what about for yourself, James? 

Speaker: James Pitchforth 

Timestamp: 00:26:18]

I suppose we've talked a lot about foundations and we've talked a lot about, you know, good basics. But I think for me, I genuinely feel excited about data and the future of data moving forward.

We've gone through the technology phase, we've gone through the digital phase. Digital consumes an awful lot of data and we're in a space now where we've got the technology to create more data. The power now, or the next stage of this for me, and the reason why I get very excited about working in data is It's, it's, it's all about the extent of our innovation to take this forward.

So I suppose the only advice I would give you is don't, don't feel boxed. Be innovative, be creative, go for those smarter solutions. And, and for me, it's all about that client. So every time I think about the data that sits around a client, how can I create more insight, more intelligence, more experience for that client?

And, and for me, that is why I work in data.


Speaker: Suki Dhuphar

Timestamp: 00:27:14

Excellent. Thank you, James. And just to wrap it up. I mean, it, as I said, it's been a pleasure having you on stage with me. Great conversation. I know we can carry this conversation on for, for ages. But the one thing I will sort of lead with from a software vendor point of view, one of the, one of the great things we're working with both Claire and James, it's a collaboration.

You've got ideas, share ideas, work together, you know, feedback, take it in, take the feedback. If you, if you need to improve, So I think whenever, whether you're working for a big organization or a small organization, whether you're working for a vendor or on the other side don't, you know, don't feel ashamed or small to ask questions and collaborate.

Always collaborate. I think it's the only way we're going to improve. And it's the way we, as people working for different organizations, are improving as well. So thank you for being here. Any questions, please come down to our booth. Happy to answer them. But thank you for being here and thank you very much again to Claire and James for the session.

Speaker: James Pitchforth 

Timestamp: 00:28:10

Thank you. Thank you. Thank you.