As part of their special 2024 issue, Il Bollettino, an Italian Economic Journal, interviewed our CEO & Co-Founder Tommaso Migliore. He shared his perspectives on the continuous growth of AI in 2024, with a particular focus on its profound impact on the world of investments.
"I believe there is a great opportunity," says Tommaso Migliore, CEO and co-founder of MDOTM Ltd, a Fintech company developing AI-based investment solutions for banks, insurance, asset, and wealth managers. "Humans and machines are indispensable because we have great minds graduating from our universities every year who can undoubtedly harness this value. Innovation starts with people, who, in turn, start with incentives. Big companies, Big Tech, have very broad objectives. Often innovation is challenging to grow internally. Hence, their approach is to invest externally and acquire smaller competitors."
Why and how is AI used in the financial space?
"If we think about it, every complex ecosystem requires complex technology to understand and explain the relationship between the millions of elements that make it up, just as in financial markets. We often tend to think very linearly: there's a problem, here's the solution. It's not always like that. When dealing with complexity – non-linear relationships between risk, returns, and correlations – that's where artificial intelligence adds value. That's why it's being talked about now and why it's discussed in finance, perhaps one of the most complex environments. Moreover, generative AI has certainly brought technology closer to everyone. ChatGPT has had more than a technological impact; it's been informative. Why? Because what a neural network used to do, consumed with numbers and equations, has suddenly become tangible, with text, images, and videos that I can understand much more easily. That's why it has become one of the most interesting topics at the moment."
In practice, there is an evolution of both interest and awareness as well as technology. Which one is moving faster?
"Here, I am reminded of what Bill Gates said about tending to overestimate the impact of new technologies in the short term and underestimate it in the medium term. That's what's happening now. At this moment, many people wonder if AI will take away our jobs, but I think it will be like when the internet spread. Back then, the initial concern was about jobs. No one would have estimated how truly disruptive it would be, how many new opportunities it would create, and the focus was mainly on the most immediate use cases. Can we shop online? Then all stores will close. Stores are still there, but the world has completely changed. I believe that with AI, we will witness a very similar phenomenon: evolution rather than revolution."
What are the use cases of AI?
"There are many, but I would divide them into three main aspects. First, a marketing and positioning aspect, then one related to customer interaction, and finally, one related to information and its processing. From a marketing perspective, not only in finance but also in e-commerce, content-producing sites, etc., AI brings a greater ability to understand preferences, creating a personalized, tailor-made experience. In finance, this is seen primarily with more targeted offers. Then there is better use of customer information. What does that mean? It means that once I understand better what I want, I can also work better with data to offer something truly personalized. This is all finance because it's about understanding the customer comprehensively. Finally, there is the computational aspect applied to the world of investments, converting that need into a portfolio, wealth management, a truly tailor-made investment solution."
What are the use cases of AI in the financial sector?
"In this case, where great value is seen is in everything related to aspects of asset allocation, both tactical and strategic, through the construction of personalized portfolios on a large scale. We already live in a hyper-personalized world. If I open Netflix, I see a different page from everyone else, but it's still Netflix. This makes our expectations move in this direction too. But in finance, this kind of attitude doesn't exist to the same extent. Especially regarding wealth management, it's common, for example, to resort to approaches revolving around model portfolios. Why? Because personalizing on a large scale in a non-linear environment is not simple at all. Here, AI changes things."
Wouldn't such operations be executable by a human professional?
"Firstly, it's essential to understand that AI is a model. Theoretically, everything could be done manually, even building a machine if desired. But it would take too much time. Artificial intelligence, compared to classical modeling, can solve problems that are non-linear and would require many, thousands of different equations. So, in practice, it wouldn't be achievable. I'll give a concrete example: if an investment company has two clients with diametrically opposed positions, how can the same investment idea be implemented on these two portfolios? Only through hyper-personalized allocation that considers all investment constraints and preferences, using a more elastic, dynamic, and sophisticated mathematics than traditional methods."
In the AI industry, dominated by big names like Google or Microsoft, do you think there is room for smaller operators?
"Just think about this: OpenAI developed ChatGPT, not Google or Microsoft. It's true that Microsoft invested, but only later. We've all tried Alexa, Siri, or Google Assistant, and they're not even close to ChatGPT. Why didn't they do it themselves? Creating innovation in a large organization, even if well-capitalized, is always difficult. This is because innovation starts with people. The powerhouses exist in an organization, but they are scattered. In a scaleup, you put these brains very close together with a clear, aligned goal. Enormous resources are not always needed to do great things. Maybe you need them to scale it later. But you don't need them to create the initial innovation. In short, there is space. And let's always remember all the times when we thought the situation would never change, and then suddenly it did. Think about Nokia: in 2007, Forbes wrote on the cover, 'Can anyone catch the cell phone king?' In the same year, the iPhone was launched, and shortly after, Nokia practically disappeared. In contrast, the same Big Tech like Google or Meta did not exist thirty years ago."
So, your sector, which would seem to be capital-intensive, is actually labor-intensive, or rather, people-intensive?
"The variable to consider is always the life stage. Usually, software is a sector that is a bit less capital-intensive than manufacturing. Of course, being well-capitalized from the start is an advantage, but it's not the only key. Where funding is needed, especially, is for scaling. Once you have the solution, have shown everyone how it's done, you have to be quick not to lose the advantage you've built."
What are the opportunities not yet fully exploited in the AI landscape?
"The growth potential of AI is enormous in the coming years. This is because, from the perspective of technological talent, we produce great minds. Consequently, we have people capable of developing these types of technologies. The area that, in my opinion, will be of greater interest is hyper-personalization of decisions, especially those related to finance. Providing technology capable of assisting, like a co-pilot, decision-makers in investment choices and in building personalized portfolios on a large scale."
Regarding finance specifically, do you think this is an important innovation to survive even today?
"It's a priority. Innovation, especially when it's so disruptive, cannot be seen as an option but a real necessity. Action needs to be taken, experiments need to be conducted. In this, American culture teaches us: Silicon Valley companies have a real obsession with change and new technologies. They always want to make sure they don't miss a big trend and an opportunity to increase the efficiency and productivity of processes. Even being passive or too cautious about innovation can turn into a risk."
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