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Episode 31

How to get value out of PETs in banking

Hosted by
Alexandra Ebert
Our guest is Ville Sointu, Head of Emerging Technologies at Nordea, the largest bank in the Nordics. His job is to look at technological opportunities and threats. Ville is passionate about connecting new technologies to business utility and making an impact on people's lives through those technologies. His work in banking is incredibly important, since banks are deliberately designed to be risk-averse and conservative. The very nature of the banking industry makes finding new, better ways of doing things a difficult feat. The advantage neobanks have over incumbent institutions is immense but unlikely to last forever. Their brand new, shiny architectures are bound to become legacy at some point, and so they will be facing the same challenges traditional banks face today. Listen to the episode to learn:
  • what innovation strategies work in banking
  • why it's impossible to compare banks and financial institutions due to different regulatory landscapes
  • what's leapfrogging 
  • why do different markets see different products and services succeed
  • how and when to adopt emerging technologies in banking
  • why do banks need more engineers who can explain technologies
  • why silos are not bugs but features in banking
  • how siloes can be broken down using PETs like synthetic data
  • why do banks need to pay attention to the long term gains with PETs and not only to immediate results
If you would like to learn more about privacy enhancing technologies in banking, download the Mobey Forum's report on Digital banking blindspots. If you would like to find out more about using synthetic data in banking, read the overview on synthetic data use cases in banking


Alexandra Ebert: Hello and welcome to the 31st episode of the Data Democratization Podcast. I'm Alexandra Ebert, your host and MOSTLY AI’s chief trust officer. Today, we will cover the topic of emerging technologies in financial services, and how banks can really get value out of new technologies and operationalize them.

My guest is Ville Sointu from Nordea Bank, a European financial services group based in Helsinki, Finland, on the forefront of digital banking and innovation. Ville leads the emerging technologies teams that Nordea, and he's an internationally known expert of financial technology and a true FinTech enthusiast. He's also the co-chair of Mobey Forum's AI and Data Privacy Expert Group.

[00:01:00] Today, we covered emerging technologies. When is the right time for banks to look what is out there on the technology forefront, and how to adopt [00:01:10] it and make sure that you improve the value for your customers? We also took a look around financial services on the globe and covered the question of is there something [00:01:20] incumbent in Europe and Western parts of the world have to be afraid of when we look into China and Africa, for example? Of course, we also touched upon synthetic data.

[00:01:30] I'm sure there are plenty of things that you will take away from this episode. Let's dive right in.

Alexandra: [00:01:40] Welcome, Ville. It's great to have you on the show today. Before we dive into all the exciting topics that we've lined up, could you briefly introduce [00:01:50] yourself to our listeners, and also maybe briefly share what makes you so passionate about the FinTech world and the work that you do?

Ville: Yes, obviously. First of all, [00:02:00] thanks for having me. It's really great to be on the podcast as a guest. I think it's one of my first in this space. As you mentioned, [00:02:10] my name is Ville Sointu. I am the head of emerging technologies for Nordea bank. Nordea bank, for those who might not know, is the largest financial institution in the [00:02:20] Nordic countries where we operate both in the personal banking and corporate banking space as a major player. [00:02:30] My role as head of emerging technologies in Nordea is what I call technology-driven business innovation or business development.

[00:02:40] The other way I describe it, I always joke that it's the stuff that nobody else is doing in the bank, but just somebody has to cover it [00:02:50] because we need to. This puts me in a space where I look at the opportunities given by technologies in the next two to five years, either as an [00:03:00] opportunity or as a threat to the bank, of course, and we need to understand, analyze, and utilize these new technologies as we move forward. The other side of your question, which was how did I end up in this space, and how did I end up being so passionate about FinTech on financial technology in general, it's a great question.

[00:03:20] Maybe I need to caveat my answer a little bit by saying that, first of all, I'm an engineer. I come from a technology background. I do not have any formal banking [00:03:30] training in my history. It's always been about technology. Through that kind of working with telecoms in my early career, I fairly quickly landed in the financial services or financial technology space. I worked for a number of startup companies on the technology side and consultancies, of course. [00:03:50] Then wanted to get experience from a very broad perspective. I was always driven by utilizing new technologies, understanding how [00:04:00] we can use things like mobile phones.

Back when I started 20 years ago, the mobile internet was not an obvious thing as it stands today, for example. [00:04:10] I wanted to understand what do these things mean in context of financial services, and how can these things make the services better essentially [00:04:20] for the users of the services? I've been always interested in connecting technology with business to utility and doing it from the angle of new technologies. [00:04:30] I think this has been a common theme throughout my career. In addition to that, I always wanted to understand the whole landscape every way you can [00:04:40] use different services.

I've been working in Southeast Asia. I spent a significant amount of time working in Africa and South America in emerging economies and mobile money solutions. [00:04:50] The reason why I needed, I wanted these experiences is that you need to understand different ways of [00:05:00] really utilizing new, in this case, mobile technologies to access financial services. What does that mean from a society perspective, from the day-to-day lives [00:05:10] of people?

Seeing this impact, especially in the emerging economies, that these services have is a very powerful thing. It's also a big part of my motivation. In [00:05:20] addition to being a little bit nerdy with new technologies, it's also seeing the impact of things on the ground? The combination of these, I guess, combines [00:05:30] into that somebody might call as a bit of a passion towards FinTech in seeing the way it can change the world.

Alexandra: It definitely sounds like you're [00:05:40] passionate about it. After what you just shared, I can fully understand why that's the case, particularly seeing all the differences how financial services developed in other parts of the world compared to us here in Europe. [00:05:50] One thing that would be of interest to me, particularly to emerging technologies, we all know emerging technologies come with opportunities, and as you just [00:06:00] pointed out, of course, sometimes all the risks are involved. How do financial service providers approach emerging technologies and also innovation differently [00:06:10] compared to other sectors that are not as heavily regulated?

Ville: That's a great question because it's very, very different in a regulated industry [00:06:20] working with innovation in general and emerging tech. By definition, banks are, of course, very risk-averse. This is not [00:06:30] a bug in the system, so to say. It is actually a feature. It's built-in by design that the banks, they avoid change as much as [00:06:40] possible. They are very risk-aware and always they are very careful in how they proceed with new things. [00:06:50] This is for a good reason. The change always means risk of something going wrong.

If something goes wrong in a bank, the repercussions [00:07:00] of that are perhaps more significant than in any other segment, at least in segments where human lives are not directly impacted, [00:07:10] or in terms of being safe, at least. The duty to keep people's money safe is a very important one. [00:07:20] If trust evaporates, it evaporates very quickly. That's why this trust always is at the core of all these risk procedures and change aversion [00:07:30] of banks.

Again, it's a design feature, not a bug. Coming into this equation with new innovation, new [00:07:40] technologies, how can we actually enhance these new, mostly unproven ways of doing things with new type of technology, [00:07:50] by definition is a complicated thing to address by regulated institutions. Then it becomes a question, how do you combine the change, the need [00:08:00] to find better ways of doing things using new technologies into this risk-averse environment? We've seen different approaches in doing this.

[00:08:10] We know that many banks have their "innovation departments". Effectively, they get a space and they get some really [00:08:20] smart people into a room and they start "innovating" in that room. Then they do something, and that rarely actually connects to the day-to-day business [00:08:30] of the bank because it's so isolated. This was the trend in the early 2000s [00:08:40] up to 2010. We saw a lot of these activities. They failed to, again, materialized into any real impact, at least visible impact [00:08:50] to the bank's day-to-day business.

What at least we have been doing where I work in Nordea is that we've realized [00:09:00] that you need to embed innovation and emerging technologies utilization into the actual businesses and customers facing services [00:09:10] that we use every day. You need to find a model where it benefits to experiment in a safe way in a way where the [00:09:20] actual business stakeholders are involved from day one and understanding what are the opportunities in utilizing this new thing, and turning that into [00:09:30] a very concrete value proposition almost from day one.

Alexandra: That's a very good point that you're [00:09:40] mentioning. I definitely want to get back on how to escape the POC trap and make sure that emerging technologies have a business impact. One thing you mentioned, I found quite interesting [00:09:50] describing the risk-averseness of banks not as a bug in the system, but actually, a feature which, of course, totally makes sense because it's an important responsibility [00:10:00] to keep people's money safe.

I was just wondering how do you see this play out when we think of all the new banks entering the fields or increasingly also [00:10:10] tech companies, large ones like Apple but also in China, for example, with WePay and so on and so forth, all these quite fast-moving not necessarily [00:10:20] risk-averse organizations entering the financial services industry. How do more traditional banks which have a long history of preserving and [00:10:30] upholding trust cope with that? How do they find the right balance of speed and risk averseness?

Ville: That's a great observation. [00:10:40] I'll try to answer it in the best way I can. First of all, if we look at what we call the challenger bank space which you mentioned [00:10:50] because all the entities you just mentioned are a bit nuanced in the way they actually position themselves compared to legacy banks [00:11:00] like Nordea or incumbent banks, I should say. First of all, the challenger bank question is an interesting one. This is what we're observing or monitoring [00:11:10] quite closely as well.

It's an understanding that what is the actual benefit of having a modern, fresh, build from the ground up, modern IT [00:11:20] architecture capabilities to do quick development as needed? Having a very strong engineering from day one. Understanding that [00:11:30] the development of new features and the operations are tightly connected, businesses are very close to development teams. Having a modern organization [00:11:40] with modern technology behind it, and using that to develop new services. What is the upside of [00:11:50] the benefit or the efficiency gain that you get out of that?

Looking at the speed of development of these new players, it's of course [00:12:00] extremely impressive. Remains to be seen how efficient they are in sustaining that, of course. [00:12:10] You have to remember that the incumbent banks have been around for a very long time, many of us more than 100 years. It's [00:12:20] not only a combination of a lot of technologies, is also a combination of a lot of organizations, banks. Most of the banks that we operate today are [00:12:30] a combination of many institutions from the past due to mergers and acquisitions.

We have a combination of a lot of legacy in terms of organizational [00:12:40] governance hierarchy and technology. It's fairly easy to see that maybe this similar trend will continue for the challenger banks as well. [00:12:50] Asking this question in 20 years when they are in the middle of transformation into the new technology is a good question. Is it sustainable [00:13:00] and how good are they in actually executing this organizational efficiency in the long term?

Alexandra: That's a good point that you're mentioning here because I think there's this famous quote, I don't [00:13:10] know who exactly said it, but basically looking at the Fortune 100 companies from-- I'm not well prepared with this quote, but a few decades ago, and the Fortune 100 [00:13:20] companies or Fortune 500 companies that we have nowadays, that many of them are not the same anymore.

I was wondering what I think that potentially in the financial services industry, [00:13:30] those stayed rather consistent on the top compared to the big tech companies we knew from the 1950s or something like that, 1960s, 1970s, which are now [00:13:40] not as relevant anymore because banking is just a different business. Looking also at the challenger banks with a long-term lens I think is a quite interesting [00:13:50] perspective.

Ville: Yes. One great example of this actually is at PayPal, which for a long time was considered by the banks to be the [00:14:00] new kid on the block. The fast mover is now legacy, [chuckles] or they are considered incumbent compared to many of these challengers. [00:14:10] That's the way things move forward. Everybody becomes the last generation at some point in time. The sustainability [00:14:20] of your business is interesting. I'd like to point out one more point on this question, which is that it's important when we do these comparisons, that we look at things [00:14:30] on a level playing field.

When we compare banks to other entities working in the similar space, you need to [00:14:40] understand that banks can't be completely compared to other banks because regulation and the supervision of these entities is different. It is not [00:14:50] a good practice, for example, to compare regulated institutions or differently regulated institutions, at least, between each other.

That's why entities, like different virtual currency providers that are regulated or unregulated in a completely different way as banks, [00:15:10] it doesn't make any sense. Luckily, we're seeing a lot of good emerging regulation coming in the European Union as well. That should create a more [00:15:20] level playing field in this space. Just a side note that the level playing field regulation is important thing to consider when making comparisons between players.

Alexandra: Definitely. [00:15:30] One other thing that comes to my mind in that context is since you also mentioned emerging markets where banking and financial services doesn't look back on hundreds years' history and [00:15:40] legacy banks or even branches of banks being available. Basically, everything happening via mobile from the start. [00:15:50] How do you see that play out on the long run?

How do you see that play out? Will they at one point in time be at a size where they will be in a good position to enter also Western markets [00:16:10] and US markets and so on and so forth, or do you think that those will grow big but just stay in the regions that they emerged from?

Ville: [00:16:20] What we're seeing in many of the cases is in many industries is leapfrogging. [00:16:30] What we've seen in places where there's less of infrastructure for banks, for example, with low amount of branch offices, [00:16:40] and yet it's a large country where players like mobile operators might have a lot of branches or agents around the country.

[00:16:50] Then they have found a way with these mobile money solutions, especially in Africa, to basically offer financial services through these [00:17:00] mobile phone operator networks and agents and use them like a micro branch in a way where you can do cash in, cash out, [00:17:10] effectively creating this digital financial services space where it didn't use to exist. That means that they completely skipped [00:17:20] the time when they were using e-banking or a computer or a laptop to access your financial services. They even skipped the space where you [00:17:30] needed to go to a branch office and do your customer processes or any of that.

Now they have access to financial services using their mobile phones. That's [00:17:40] probably the way they will prefer to do that as long as it makes financial and overall sense for them to do so. This type of leapfrogging is, of course, an [00:17:50] interesting phenomenon which we're seeing in a lot of places. The other parallel that I want to draw here is that your question about do local [00:18:00] solutions become global solutions. This has been seen in so many different places in history.

One of the examples that [00:18:10] I always like to bring up from my telecoms background is that I remember back in early 2000s when European economies, in the technology space, [00:18:20] we were trying to figure out how do we do wireless application protocol-based solutions for customers. That's the infamous WAP, the black and white basic [00:18:30] form of internet that we had in the early 2000s in the very basic back then, mostly Nokia phones. At the same time, looking into [00:18:40] Japan, they already had color displays, they had practically internet everywhere. It was called i-mode back then.

The i-mode, [00:18:50] it was like a miracle for us in Europe, trying to understand how is it possible that this is so advanced? [00:19:00] Then the question, of course, was why isn't i-mode available everywhere? Why don't they come to Europe? In fact, they did. They did try to launch in several other [00:19:10] countries outside of Japan, but none of them really succeeded. It was a very closed ecosystem, ultimately. Even though they were able to create some [00:19:20] services, people didn't really see the benefit of using an i-mode service in favor of just having an open internet access [00:19:30] from your computer and they ultimately failed.

Now the bridge to the question of financial services comes from now we're seeing a lot of success [00:19:40] in China, for example, with their tencent Alipay offering and great super apps for financial services in those regions. [00:19:50] The question becomes, why don't we see those in Western countries? It's still an open question, but I would almost [00:20:00] pose the same type of a challenge that I explained with i-mode, is that ultimately what people need? Are they really that good here outside of [00:20:10] China? Everybody can see the benefits of those entities operating in massive scale in China, but do those parameters [00:20:20] apply in Europe, for example? I'm not sure about that.

We've, for example, already moved past largely from QR-based payments [00:20:30] at the point of sale. We already have contactless NFC payments. Very convenient, very safe, and fast. I'm not sure people are convinced that it's better to use QR [00:20:40] codes for acceptance. Just a very narrow example of these habits that have already been formed that might not be compatible [00:20:50] with the Chinese approach. I think that it remains to be seen. I'm sure we will see these entities coming into Europe and other parts of the world [00:21:00] in the future. We'll see how it plays out.

Alexandra: Definitely will. Definitely a good point that contactless payments are much more convenient than having to scan a QR code. [00:21:10] One thing that I was wondering, since you mentioned that, of course, emerging technologies play an important role for incumbent banks. Even though they [00:21:20] might not be this okay, it's quintessential that you are always on top and are as fast as all of these challenger banks due to the scenario that you just laid [00:21:30] out.

What I was wondering, how to get this art of investigating emerging technologies, evaluating emerging technologies, and [00:21:40] incorporating those that are beneficial into your operations right from a timing perspective. Do you have some actionable advice for our listeners when would be[00:21:50] a good time to start looking at a new technology to make sure that you're not too late to hop on the train, to say so?

Ville: [00:22:00] I'm going to answer this from a banking perspective because that's where most of my experience is coming from. I've worked with [00:22:10] several, consider them new technologies in this space. I'm lucky enough to work for a bank that is actually investing in new technologies and is seen as a digital [00:22:20] leader in the banking space, at least, especially here in the Nordics.

The one common thing that I can say based on-- [00:22:30] I'm going to give you a practical example here. I used to work a lot with blockchain technologies. We were running a center of excellence for blockchain. We still do,[00:22:40] and I'm still leading it. Back then, we were looking at a specific technology, in this case, blockchain and distributed ledger technology. How do we scale this [00:22:50] technology to make any business sense or create new customer value for our customers?

The quick revelation [00:23:00] that we had after a lot of experimentation was that ultimately, it doesn't matter at all what is the technology behind [00:23:10] these solutions that we bring to our customers. It needs to be invisible. Here's the advice [00:23:20] that I derived out of this is that as a technologist, as somebody who worked with technology to have a business innovation or you're trying to move forward new technologies, you need to [00:23:30] remember it's never about the technology, it's always about the result, what it actually looks like to the customer.

Even though you might find [00:23:40] some superior technology to do everything smarter, faster, better, that can never be the justification to do something just because it [00:23:50] happens to use a specific technology or the current latest type acronym. You need to focus on the end result and the end value. Then you mix and match [00:24:00] the right technologies to achieve that goal. Here's where you need to use the technical expertise. Again, the technology can never be the [00:24:10] means to an end is the number one lesson that many are still learning in this innovation space.

Alexandra: That's true. I'm fully [00:24:20] with you that it should never be about the tech alone. That just having faster, shiny, nice tech is not a justification unless you're a tech nerd and love to have new stuff and [00:24:30] play around with it, but of course, not in the business context. One thing I'm challenging, though, is that fully with you when it's a customer-facing application that you want to see value for the customer and that the [00:24:40] customer doesn't really care about what's under the hood.

In general, when it comes to merging technologies, many of them are not necessarily something that you would [00:24:50] describe as customer-facing. Just thinking of synthetic data, for example, where it really helps organizations to become more agile and faster in accessing the data and innovating with [00:25:00] it, which of course subsequently results in hopefully better features, better services, better products at a faster pace.

In general, it's something that [00:25:10] also has a huge impact on operational efficiency because you don't have to go through these cumbersome weeks or month-long processes of accessing data, preparing data, and hoping that you get something that's [00:25:20] anonymized in a way that you can still use it for something. Would you say that even though it's not only about tech, it has to be tied to a business outcome, or is it [00:25:30] always and ever on what plays out or what comes out for the customer at the end?

Ville: First of all, it's [00:25:40] always about the end result to the customer. Then the question is how many steps you need to take in order to get there. For example, on the point you made about [00:25:50] synthetic data, by the way, which is an interesting topic that we should drive a little bit deeper into as well if we have time today. These are so-called enabler [00:26:00] components in what can be categorized as infrastructure improvement to drive a result, maybe on a broader [00:26:10] perspective than just a single service, for example.

If you have more high-quality data that you can use [00:26:20] through methods like creating synthetic data that make your AI better, ultimately, that will then result in better, smarter, more predictive [00:26:30] services for your customers. Do the customers know that there's synthetic data behind it? No, they don't. They should see [00:26:40] the value of the service and how it's making their lives better. I think the answer to your challenge is that [00:26:51] we are both right in this regard. We're just talking about different phases of the development here.

Maybe the real question here is [00:27:00] that how do we identify these opportunities where we get exponential returns in working on enabler components that can be utilized in multiple [00:27:10] cases as a piece of core infrastructure? There are many technologies that go into this category. Blockchain, again, I already mentioned, we got efficiencies in terms of creating [00:27:20] collaborative infrastructure.

Then we have privacy-enhancing technologies that, first of all, make compliance cheaper and more efficient, but also [00:27:30] allows the organizations and the AI and the algorithms to learn better from larger data sets. Again, these are things that are completely invisible to the customer [00:27:40] unless, of course, you look at it through the lens of, "Now I have a smarter investment portfolio. I don't know exactly why, but I do." [chuckles] That's [00:27:50] the end result of this successful infrastructure place.

Alexandra: You got me convinced. Since you're mentioning that it's just the lens that you take on [00:28:00] how many steps are in between the end result of making your customers more happy and offering a better service, how good would you say are banks when it comes to evaluating a new technology, [00:28:10] particularly if there are more steps until you see the end result for the customer?

Because what I see play out when I look into synthetic data that those organizations that have a concrete [00:28:20] business need, for example, they can't access the data they need to improve credit scoring model or something like that, then synthetic data is [00:28:30] brought to the organization and they can just access this data quickly. See that the model performance improves significantly, and see the value that they derive for them from that, they are happy with synthetic [00:28:40] data.

One thing that I think oftentimes is a little bit underappreciated is the general change that you introduce, particularly when you start [00:28:50] using synthetic data because besides the actual business case. Organizations that really manage to open up data access with synthetic data [00:29:00] democratize access so that it's easier for different smart people within an organization to see granular behavioral customer data in a privacy-safe form, [00:29:10] which can spark so many other ideas, project services and great ideas that weren't possible before.

This is of course a little bit more difficult to [00:29:20] access because how to compare to the environment that you had before where data was locked up and it was hard to innovate, and now you have this [00:29:30] open data culture democratized access and so many new things that could derive from that. Of course, it's a little bit harder to calculate and see on the bottom line [00:29:40] directly. What's your perspective on that? Is this something that some banks are good at? How could they get better at seeing this overall change introduce to the organization with emerging technologies? [00:29:50] What's your take on that?

Ville: That's a really interesting angle. I think I can give maybe some context to this because I've been working [00:30:00] in this environment for a while. These are more or less personal reflections based on the things that I've seen so far. [00:30:10] We have to remember who works in banks. The traditional split in a bank is that you have the "business people" who are [00:30:20] trained bankers. They have, basically, academic background is only from business or economics, and they're great at what they do. Then there's the IT department, [00:30:30] effectively people with technology backgrounds moving into banking space.

Still, over all of these years of digital development, [00:30:40] there's very little in between. There are these people who understand the opportunities by technology and have enough [00:30:50] business understanding that it will be possible to bridge these gaps. There's a banker whispers [chuckles] in a way where [00:31:00] you explain the value of a new technology to these stakeholders on the business side of the bank who have never spent a significant [00:31:10] amount of time trying to understand how technology works.

This role is increasingly important. [00:31:20] Maybe this is a call to action also for some of the listeners here is that I think the banks need more engineers. [chuckles] [00:31:30] We need more people who understand technology, not only from the IT perspective sitting in the engine room, so to say, but people who are able to explain technology [00:31:40] better and the value.

Alexandra: Yes, to translate between the different departments that's so much needed. If you have some secrets where to find those engineers [00:31:50] because what I know is that everybody is searching for them, but definitely a call to action I can sign up for.

Ville: Exactly. These horizontal [00:32:00] capabilities are not in a large scale recognized at banks at the moment, even though I can say that at least from my subjective [00:32:10] perspective, there has been huge steps forward lately inside the organizations that I'm familiar with [00:32:20] in terms of understanding that we do have group-level horizontal capabilities. That we must have a cohesive technology and business strategy, that we invest in to get these exponential [00:32:30] benefits to all of the business units.

Because that's another symptom that we see largely due to this division between business and technology, is that a lot of the [00:32:40] innovation in technology in utilizing new technology is done in silos. You might have even different units [00:32:50] in the same bank working with a similar technology completely unaware of each other. Then they find each other when the vendor, [00:33:00] for example, happens to mention that, "Hey, did you know that we have this other project going on inside your bank?" They're like, "Oh, okay, wow. Oh, this was a synergy opportunity missed here."

[00:33:10] This siloed organizational structure is one of these features that is also built into banks by design, [00:33:20] so it's not a bug in the organization. It is the way the customer information is also protected, but also the responsibilities [00:33:30] are clearly separated in order to comply with a lot of the risk management regulation and rules that we have in place. [00:33:40] To a certain extent, saying let's break down the silos is not the clear answer to these issues. We need to find a way to do that in a [00:33:50] compliant and a privacy-preserving way, which by the way links into this broader discussion about privacy-enhancing technologies as well.

Alexandra: Absolutely. I think this now should be [00:34:00] the prompt for us to move into privacy-enhancing technologies with our conversation because I am with you that personal sensitive financial information [00:34:10] shouldn't be floating around the bank unrestricted and unprotected. In general, I think that the silos seem to be quite a hurdle [00:34:20] for incumbent banks to overcome when it comes to this adopting new services and getting rid of certain inefficiencies, like looking into the same technology at the same [00:34:30] time and so on and so forth.

From my perspective, at least from our conversations, it's more about getting this balance right of keeping that in the silo [00:34:40] which needs to be protected, but finding ways, like privacy-enhancing technologies, to more collaboratively work and innovate for the sake of improving the experience for your customer. [00:34:50] Maybe to come to privacy-enhancing technologies as a primer for our listeners, some of you might remember that we had Amir Tabakovic on the show last year in summer [00:35:00] where we already covered the privacy-enhancing technologies report from Mobey Forum's AI and Data Privacy Expert Group, which Amir is a co-chair and Ville today [00:35:10] is the second co-chair.

I think the report was titled the Digital of Banking Blindspot. Now I think in 2022 new reports were published, and [00:35:20] there's also some other publications coming up. As a quick primer to dive into privacy-enhancing technologies, Ville, can you share a little bit about the reports that are currently [00:35:30] being written up at Mobey Forum and why they're relevant for our listeners?

Ville: Yes, of course. By the way, cheers and greetings to Amir.

Alexandra: Always.

Ville: It's been great [00:35:40] working with you on this paper. For the listeners who haven't looked at this report, I'm sure there's going to be links in the show notes.

Alexandra: Absolutely.

Ville: We always wanted to do a series of papers when we started talking about what we call emerging privacy-enhancing [00:36:00] technologies. The first report which you discussed with Amir was basically a way for us to explain what is the problem that we're trying to solve, [00:36:10] why are these things considered important, and how is this different from the things that already exist?

Roughly speaking, [00:36:20] having these access controls or limitations of use, which is the traditional way that data protection happens, [00:36:30] or you have a pseudonymization or anonymization of data for you to effectively disassociate the data source [00:36:40] or the subject from the data itself, and then that's the way you effectively try to protect data privacy. [00:36:50] We think that there's something in between these two worlds.

You can use what we call emerging privacy-enhancing technologies to find the balance between this [00:37:00] access control and traditional obfuscation-based mechanisms, where we could utilize data without compromising data privacy, [00:37:10] at least not to any significant degree, in order to effectively share data and do innovation based on [00:37:20] data with no risk of exposing customer data in places where it shouldn't be exposed.

[00:37:30] Again, the first paper was about having almost like this pixie book or headline level description of these are the technologies that we see [00:37:40] as the headline technologies in this space. By no means exhaustive, by the way, this space is [00:37:50] moving forward so fast that we already recognize that there are many new ones combinations of these technologies that are being utilized in the market. [00:38:00] We do list a number of these technologies in the first report and give a headline-level description.

The positioning of this paper was [00:38:10] an interesting discussion. We always recognize that there's plenty of big consultant house papers describing the high-level, [00:38:20] executive-level things on this previous enhancing technologies. Then on the other end of the spectrum, we have a lot of academic [00:38:30] research papers, hundreds of pages of technical analysis on the underlying technology, but there was very little in between.

We felt [00:38:40] that in between these two worlds of highly technical and highly business level, there is a space where most of the [00:38:50] people working day to day with these issues, actually, they understand the business part, but they might not be more technical enough to understand [00:39:00] these hundreds of pages of mathematical analysis on an encryption mechanism.

We wanted to cover this in-between part of this. [00:39:10] We wanted to start with this first paper, which describes the problem, what we're trying to do. Then moving on to what we're doing this year now is to [00:39:20] continue the series with deeper dives into specific technologies. We have done already papers on homomorphic encryption. I think [00:39:30] that we did the multi-party computation as well. Again, I'm not sure when this podcast comes out, but we're doing these mini papers now as a series of papers that deep dives into a specific technology.

Alexandra: I also know that the report on synthetic data came out already because I was asked and honored to contribute the expert introduction to the topic. I think this one was published already [00:40:00] in March or something like that, but definitely a resource that we will link to and that our listeners should check out because it's 100% right what you're saying.

There is a need for this in-between [00:40:10] to not only have this superficial headline newspaper articles information, which sometimes makes these different technologies or aspects together. [00:40:20] Also, of course, who has time and the technical capacity to read through hundreds of pages of papers in scientific analysis.

Ville: Yes. I would like to [00:40:30] remind that if you do pick up one of the mini-reports, then do remember to also check the first paper because sometimes we get feedback that this [00:40:40] was already too complicated. The reason is that it's a series of papers, so you should maybe read the first paper first and then take it as a series. Then later, you can [00:40:50] come back to a specific technology that you're interested in.

Alexandra: Absolutely.

Ville: Just to conclude, on this paper, we are concluding this series. Again, [00:41:00] now that I'm saying out loud, maybe it won't happen but at least our plan is to conclude the series to cover combinations of different technologies. Now that we [00:41:10] introduced specific technologies, we want to conclude the series by introducing the overall value of combining different technologies together, and how they complement [00:41:20] each other and create even more value. We're really looking forward to feedback on the papers. It's quite exciting stuff.

Alexandra: Absolutely. Also what you mentioned [00:41:30] with these hybrid use cases and how different emerging paths can be combined is such a fascinating topic. I just recently sat on a panel where we covered exactly that, emerging technologies [00:41:40] and how they can be combined. Fascinating stuff that you're working on there. Maybe one last thing to cover before we run out of time.

[00:41:50] You mentioned earlier that you found it as a success secret to really derive business value out of emerging technologies, that you think of how to integrate them [00:42:00] in operations right from the start, and how to get an impact out of them. Do you have some advice for our listeners, when they evaluate technologies like synthetic data, [00:42:10] homomorphic encryption, secure multi-party computation, and so on and so forth, how they can successfully navigate this journey from piloting to deploying [00:42:20] them in production and eventually ending up with deriving business impact from them?

Ville: I wish there was a silver bullet, but I can at least give [chuckles] [00:42:30] some notes that I've gathered along the way. You already mentioned focusing on the business value and seeing the outcome [00:42:40] already, or what it looks like even if you remove the whole technology from the explanation that you give to your boss and why it's important. You need to always be able to remove [00:42:50] the name of the technology and still explain why it's valuable.

That's number one thing, it's seeing the immediate value even from a narrow basis, [00:43:00] but then on the other side of that, the only way you will be successful with these technologies that are quite broad and are used almost on an infrastructure level, like the [00:43:10] privacy-enhancing technologies we just talked about. You also need to see the long game and you need to have both. You need to see the short, immediate value, but you also [00:43:20] need to see what is this going to mean in five years' time? How do we make sure that this is playing in concert with all the other things that we're doing at the [00:43:30] same time?

Are we heading into the same direction or are we just playing inside of one of these silos? One efficient way to kill any [00:43:40] project, at least in the medium to long term, is to make sure that it remains in a silo, it continues to deliver perhaps on that original [00:43:50] narrow value proposition, but never extends beyond that. You might be successful in the short term, but you will fail in the long term. Having an understanding [00:44:00] of the long term while delivering short term value sounds a fairly obvious statement, but many times when you're especially working in innovation [00:44:10] in the regulated environment, people tend to forget.

There's so many examples of bank innovation projects just doing something because it's the [00:44:20] shiny new thing, it's the new technology that everybody talks about. I guess saw the headlines and then they do it and they realize, "This actually didn't really change anything." [00:44:30] They perhaps are either too focused on the immediate return or too focused or just creating this long-term vision without being able to articulate the actual value in [00:44:40] the short term.

Alexandra: I can also imagine that this might be an additional challenge for the business side or maybe for those horizontal tech experts [00:44:50] that we talked about who would be in a position to communicate the business value to the business side in a way that's understandable for them because particularly this long term component [00:45:00] of setting your bank up to be successful not only now but also in the future is something I at least could imagine is maybe not always highest priority [00:45:10] for the business side, which needs to focus on making revenue goals and KPIs for this quarter, this fiscal year, and so on and so forth.

Would you say it's [00:45:20] an uphill battle for these horizontal translator roles to not only convince business side on which technology can have business value but also [00:45:30] consider the long-term impact and change that could be facilitated for them?

Ville: Yes. I always joke that I have the best job in the bank and I have [00:45:41] the worst job in the bank. The best job because I get to work with all the cool stuff, I get to play with all the nice, shiny toys that we talked about. The worst because also [00:45:50] I need to explain to everybody why this new thing is the important thing. You need to do a lot of work in order to articulate that [00:46:00] in a good way. I enjoy the work but it's also a tough environment, of course.

The way these banks [00:46:10] and typically any legacy organization or long-standing organization is built is that you have your KPIs, and you have your need to be [00:46:20] profitable, and you're looking at the next quarter and shareholder returns. Of course, as the old saying goes, you get what you measure. If you're only [00:46:30] measuring immediate returns on investment, you will never have any long-term technology strategy either.

I think this evolution is something that we're going [00:46:40] to see in these incumbent organizations, not only banks, all of them. Is that they also need to be able to [00:46:50] measure this sustainability efficiency, technology-driven innovation, and their efficiency gain out of those also in a little bit [00:47:00] of a longer perspective. Are you investing in things that might emerge in three to five years, or are you only investing things that get you something immediately? Because [00:47:10] that's a broader question of sustainability and building efficiency in an organization as well.

I think the very basic or very mundane answer [00:47:20] is that we need to build things that will measure KPIs based on these longer-term goals as well. I hope to see this type [00:47:30] of evolution in these organizations, of course, in the future.

Alexandra: I hope so too. Ville, it was a true pleasure having you on the show today. Thank you very much for [00:47:40] allowing us this peek behind closed doors of innovation at the incumbent banks. I definitely hope I can welcome you back on the Data Democratization Podcast at one point in time to [00:47:50] potentially cover hybrid applications of PETs and many of the other exciting topics that I'm sure you have an interesting perspective on. Thank you so much for taking the time today.

Ville: [00:48:00] Thank you for having me. It was a pleasure being here. I really look forward to continuing the discussion either offline or even here on the podcast in the future as well.

Alexandra: Wonderful. Perfect, [00:48:10] Ville. Oh, and since you mentioned the podcast, I nearly forgot Ville also has an awesome podcast, the FinTech Daydreaming Podcast, if I'm not mistaken, where he invites other FinTech enthusiasts and nerds, [00:48:20] as you said, to discuss the latest things in FinTech if I'm right. Definitely go check out that one as well. We will include it in our show notes.

Ville: We also do horrible banking jokes in the podcast, so I do recommend you taking a look.

Alexandra: Perfect. If FinTech didn't convince you, then going there for the bad jokes is [00:48:40] definitely something that you should consider doing. Thank you very much, Ville.

Ville: Thank you for having me.

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