EN | Learning Financial Technology (in an ever-changing landscape) | MERGE Madrid 2025

Okay. So, we want to start. We are here um my name is Andre Alonso. I'm here with Andrew and we want to present a new a new masters at IU University on financial technology. So, basically what we aim to do here is it's to convey the message um that you know financial technology is an ever changing landscape.

We've both been working in the two big dimensions of uh financial technology. I'm more working on machine learning and AI and Andrew it's an expert on blockchain and uh digital regulation. So what we have been working on with IE university is to really develop something completely new brand new to focus on a long-term course on how to learn financial technology from the ground base. Um that's why we see financial technology like a two-dimension um let's say landscape or field of research or academic field where basically we aim to focus our effort on explaining that fintech is basically about two big technologies AI and machine learning generative AI natural language processing how to master this new technology together with as we are here blockchain uh crypto and and defy smart contracts. So what we want to differentiate ourselves is you know together with the backbone of IU University to work from a very technological uh background on what are the basics for studying financial technology that this is not something that can be done in a very fast course one month or uh six months course on any of the particular topics but we need to go back and to go to the um you know to the roots of what is AI what is machine learning why in finance we are using this has uh this to do with econometrics with the statistics you know what are the problems regarding responsible use of AI sustainability same with blockchain and will focus more on blockchain and and uh digital regulation before going into you know the very fancy things of setting up a new startup or a new fintech that we will touch upon that but we want to differentiate ourselves saying that we know the basics and the academic we have the academic background to really build something from a scratch that will take a year long to really try to master what we understand it's financial technology.

As of today, you know what what is financial technology? Most staff would you know associate financial technology with one particular dimension of financial technology. Some of us like blockchain some of us like you know basically building up something from scratch and a startup in finance related things. Some of us go more into other dimensions of technology like AI in the very general terms that I will touch upon this refers to natural language processing uh refers to how banks are using nowadays generative AI but also how to deploy this in real practice. Um so basically we we want to see how to connect two worlds.

First like you know general finance like banking or financial institutions how are using AI like seriously using AI. So we are looking for profiles like people wanting to delve deeper into uh that science computer science profiles that really have a good understanding or of what are you know the statistics behind these new technologies. what are the um you know the the the academic background to really understand the complexities of going into uh computer science subjects but also people who are more into finance and they want to go back to understanding you know I already know how finance work how new marketing infrastructures work but I don't have the understanding of how to program in Python I don't know you know what's h behind the roots of blockchain I want to program in blockchain and they want to spend one year long going back to these roots and this is exactly what we are going to do. So we start inside IE in the science and technology school. So this is not the business school.

This is science and technology because this is what is going to be the backbone of our professors and what of our faculty. We are looking for people who are willing to spend some time with you know first term same subject as in computer science and then going into the third second and third term trying to specialize themselves either more into the technological driven the technological dimension of AI and banking or blockchain fintex and this new industry and why AI is used in banking there are several use cases you know I don't want people to just to stop in the surface you know we can go into why really banks are using this and from our experience we are seeing AI using very different uh use cases. We have some examples like credit risk and credit scoring. There are so many fintexs that basically are devoting their efforts to try to rely on new machine learning models on new generative AI technologies to really understand how they can you know gain new access to trade uh or they really can manage um in a newly fashion financial risk. So we want to understand from people um in banking how they are using AI for example in in all the domains of financial risk.

This means um using traditional machine learning. This is uh going into interpretability techniques like game theory subly values. This means understanding all the very basics of statistical inference and the roots of supervised and unsupervised machine learning. So again think about one term that is going to be spent all all the first term of the master degree on computer science ads. If you are more into trading or asset management, it's true that we have you know all these high frequency trading that is also some kind of the profiles we're going to cover uh with some of the faculty specializing you know in latency and how to use uh machine learning and AI and generative AI for trading for causal difference for example and factor investing.

So again it's not that we are going to be a trader or we want only to get traders inside the master degree but you are going to be able at the end of the master degree to understand how traders want uh deal what's the technology behind them. So then you will be able to specialize more in the infrastructure and really be like the technologies behind these kind of new trends in trading or you can be more like a strategist and work with a more finance intuition of um why these new technologies can prop up uh new uh strategies in trading. But it's more we don't want to go only into the wave or the fancy things of setting up new things risky things. We also both of us come with a background from the public sector. So we want to put a lot of effort on supervised supervision and regulation.

So a lot has to uh will be said about supervision and regulation of financial markets of new players, new products um and all the technology how the technology is going to help also the auditors and the risk experts about how to supervise new fintex or how to use new technologies to improve their work. As of today with a financial risk that we are supervising um when we talk about AI it's true to say that we live in the area of Texas data a lot of you know the usefulness of AI in banking is because we are getting into an area area where you know say big data and the vast amount of data that we have is true but what is usually said is more than 80% of the new data that we have is text. So we have to be super expert now how to retrieve data from text and this is the big thing that we are now able to do with large language models and natural language processing and generative AI and we want to understand how to combine you know Texas data within the traditional econometrics and statistical techniques. you know how we can run some empirical analysis with traditional uh numerical values, categorical values but together with extracting information from uh text just to put you as an example how ESG and sustainability has really gained traction in banking is because banks have been able to extract all the information from PDFs from texts. You know this is one of the very first example of how to combine new technologies for traditional and new banking innovation.

So sustainable finance is very quantitative when you go into banking. Why? Because you need data scientists, you need computer scientists, you need people who are really good in these new technologies to really extract information that is strictly only in texts and this is happening in many other fields. So what we really want to put here is some good use cases, some good subjects that people will be able to deal with these technologies and at the very end of the course be able to apply them in different application domains. Um customer service and all the um let's say expertise using language to interact with the clients.

It's you know a master or a first go in uh in banking nowadays. So everybody is building something on chat bots and the like and again and again we will talk about responsible use of AI explainable AI interpretability and regulation because we don't want to serve a new wave. We want to be solvent and robust and spend our time both with the ground basics of technology and also with the new digital regulation that is coming up that is super fast moving together with the same that is happening in the ecosystem. So we have new pieces of regulation every month and this is going to be one of the big challenges of the master how to keep up with this new regulation that is happening

now on blockchain.

Great thank you Andreas and just check you can all hear me okay. Yeah, great. Um, yeah, exactly. So, moving on from AI to blockchain, we do these things alphabetically. So, you know, at some point we'll end at the end of the, uh, end of the alphabet.

Um, obviously blockchain, um, I think you know, you all here, you must all very well know exactly the benefits, the potential benefits of blockchain for financial services. I think why we find it an interesting um topic and really core plank of the masters in financial technology as a whole is what blockchain can do for uh financial markets and changing business models across financial markets. AI as an just explained you know very much provides new tools new ability to extract data and make the most of this data whether sell as a product or to make your own um your own services more efficient. Blockchain I think has a real ability to fundamentally alter the business models of finance as we understand it. If we think back to sort of traditional fintech if you can call it that from the financial crisis 2008 2012 uh before blockchain a lot of that was about unbundling uh unbundling traditional financial institutions and actors be it banks payment systems payment services payment is obviously one of the large areas where it started well blockchain allows that as a new technology but in an even more efficient manner.

So what we're seeing is the technology existing which then allows companies to change their business model uh and thus out compete either existing players or provide new services new opportunities for inclusion for more efficient or cheaper financial services for better crossber operability um and also for potentially more sustainable uh and certainly more durable financial services. So I think when thinking about blockchain in financial innovation and financial technology as a whole there are two things here. one is what the technology allows as a shift in infrastructure as a shift in technology for existing financial firms for fintech firms and for startups obviously challenges um and then also what people tend to think about when they instantly talk about crypto or blockchain is there a new asset class whether that's a cryptocurrency whether that's a stable coin whether that's a CBDC or a tokenized uh real world asset RWA so we got these two different areas uh coming into financial markets financial services from one single technology DT And within that of course you know DT is maybe distributed ledger technology is maybe one form one overall arching technology but there are different forms of blockchains there's permission there's permissionless public private and each one of these has a different implication each form of blockchain has a different implication for what services you can offer on what basis to what clients or to what users um for for different areas you know not all blockchain is financial but most of it that we see today is and so really what we want to do in this course is bring in this idea that the technology is great on its own but on its own that's not the whole story is linking that to financial markets and saying okay what does the new technology allow in a financial market as I say part efficiency part new products but it's also new business models and I think that's where the interesting thing really comes in so here are just some you know very well-known use cases obviously stable coins why are they I mean I think everyone here is probably going to talk about stable coins at some point why are they so interesting well because they allow the merging of the crypto or blockchain based financial system new emerging financial system with the traditional one through on ramping fear on offramping fear. So that's what creates the link. I mean that's why it's a foundational technology for the sector tokenize real assets in a sense similar obviously they're taking real world assets and putting it onto the chain.

But then what does that mean? How would you structure that? This is the kind of thing which a lot of people and here again you know a lot of these um exhibitors here will talk about the value you can extract from tokenizing real world assets the benefits of making things more fractional or efficient or more inclusive. But actually what does it mean and how do you structure this new technology? You know we've had securitization for a long time.

We've had special purpose vehicles, SUVs for a long time. What does tokenizing that mean? What does that imply both for the customer but also for the firm? Where does value sit? How does value move?

And how does that change because of the technology? Um, and related to both of these is then DeFi and smart contracts which are, you know, relatively similar. What does it mean when you take out the intermediary? Like I I would argue that the history of financial services is a history of intermediation. And now suddenly we've got a technology which can allow pretty much anyone in the world even unsophisticated you know nonprofessionals to conduct very sophisticated financial transactions on a peer-to-peer basis.

Now that has huge benefits. Again it's more efficient. You get settlement finality. You get atomic settlement. You can get um a complete reduction of yeah complete reduction of counterparty risk by making sure that it happen by making sure the transaction happens on both sides at the same time.

But it also creates new risks which are well operational. What if you don't know how to do it? Um, it's also what if you make a mistake and you send something to the wrong person. You know, you get these these really quite important frictions that exist in the traditional financial system to row back problems or mistakes or slow things down. So, you can do AML, anti-moneyaundering and and financial crime checks that can be harder on blockchain when things are so instant.

So, there's a benefit. There's also some some challenges here as well. So that's why as part of this as a third leg for the course we're adding in policy or the public context if you want to phrase it that way very much as a core third pillar you got the technology of course that's foundational to financial innovation you need the technology you then need the understanding of financial markets and how they're changing because of the technology you also need to understand the policy context now partly that's a simple compliance question how do you comply how do you make sure you comply how do you conduct your anti-moneyaundering checks but it's actually much much more than that what does the policy framework allow you to do you Banks are the most or traditional banking is the most uh classic example of this. A bank is defined in law. But what happens if something comes along which can do everything a bank can do but in a different way.

Now originally people said well then become a bank. Then people said well hang on maybe this is more like e-oney under the sort of e- money directive of the European system. Now we're looking at stable coins. Maybe we're separating out deposit taking or the storage of value from credit creation and the loaning out of value. So how does the regulatory framework allow that?

Should it allow that? What are the risks? And so it's always come back to this first principle of what is the role of policy? What's the public sector's role in these markets? How do you then design the rights uh regulation or policy framework to achieve the outcomes the public sector decides it wants?

And then as an industry or as a founder, as a technologist, how do you interact with this? How do you how do you know what's happening? How do you make sure that you're complying? How do you make sure you're making the most of the opportunities that regulatory change allows? Now I think PST2 the payment service from about 10 years ago but less in the EU I would argue created the modern payments fintech landscape in the EU.

I think that's why it's much more dynamic than the US. So there are opportunities coming from regulatory change as well. It's not just a question of adding on compliance burdens things like that. So as a whole you know regulation policy it provides the framework of stability so investors and companies know what the landscape will look like in five years time. They can make projections they can grow they can develop these new services.

It provides rules of the road so finan existing financial institutions that want to use use the new technology know how they can work together with these things. So it provides that certainty and I think a big theme of a lot of people here now is this mainstreaming of financial technology financial innovation into existing market system. Of course there's questions of consumer protection uh and financial stability which are fundamental to everything. Um and then there's this this this other idea of what do we do with um with uh with existing uh public infrastructure. So central bank accounts or or um payment systems like RTGS, target two and things.

How can we use these to support financial innovation and what does financial innovation imply for these things? So as I say the c the course as a whole has three pillars technology, financial markets and policy or the public context. So moving on um in our last five minutes to talk about the masters itself. Do you want to take over or?

Yes. the the program format it's one full year full-time and basically we are looking for these kind of people who are into data science who are into the statistics or computer science I have the curiosity in finance or the other way around people who have the curiosity into computer finance into computer science but didn't have time or didn't have the background enough to spend some time coding but they want to go back um into this uh roots of how how to deal with h this field of expertise and they have the knowledge of finance Um basically this means that it's an interdicciplinary curriculum because we are going to touch upon AI and we're going to touch things that are purely on financial markets and the history of financial markets and why we are coming today and we are seeing here today Alastia or blockchains for instant payments and we will touch also the traditional technologies RTI and uh all the like for you to know what why we are here where we need to innovate um and once we spend between term one and term two with all the qualifications on the technology and the technological part. You will be able to specialize in different things as we said before where we see the expertise to uh demand from this expertise today both in innovation units in banking where you have people devoting their work into you know scaling uh payments and market infrastructures creating new products creating new markets uh also AI those kind of profiles who are more into data science and computer science and they want to really apply this strictly to finance related domains Um and then we will do this by integrating the faculty of IE uh so full-time professors together with people uh from the industry uh master classes and the entrepreneurial mindset of IE with the data tons tech ventures and also with the idea of potentially being able to you know learn how to create a fintech from scratch. Either you want to go into the general industry or you want to create something by yourself you will be able to do it both things. Yeah.

So I mean just to conclude I mean as uh as we've been saying like the the aim here is to create students who or to help students develop across what we see as the three core platforms for a successful career in finance today. Um you know I think most people growing up certainly myself these things didn't exist. The technology didn't exist and the need for these programs didn't exist. Well now it does and you can and our contention is that you can only have a successful career in finance if you understand how innovation works in finance. And that means understanding the technology not as a sort of add-on or something to talk about, but actually understanding what the coding looks like, what the programming looks like, how to do that yourself.

Then of course you need to understand what's happening in financial markets. How are they developing? And part of that is the regulatory framework, the policy framework, what's allowed, what will be allowed. So by teaching the students these three things, we think we're setting them up for a career in entrepreneurship, in fintech sales, or even in an existing financial institution to be able to make the most of the new technology.

Okay, that's all from our side. Thank you very much. with that. Thank you very much.