Meet the Researcher Series - Dr. Darren Shannon

What are your research interests?

Speaking more broadly, my post-PhD work involves going back to the human element of financial market behaviours, whether that be trading or interacting on a more global marketplace. I use a blend of conventional statistical techniques and advanced AI techniques like machine learning and deep learning models to isolate behaviours and make predictions – whichever suits best for the complexity and nature of the task.

But because of the diversity of subjects I was exposed to and the tasks I had to complete throughout my educational journey, I don't think my research interests can be nailed down to a single topic. I highly value interdisciplinary research and cross-disciplinary insights, where established knowledge and theories in one subject are repurposed to create a breakthrough in another. I've always been curious about that. Even when I was getting the grips with how humans behave in financial markets – which was why I wanted to learn so much about quantitative finance models in the first place – I learned many of the pioneering insights came from other fields of study. For example, the ubiquitous Black-Scholes equation came from insights on heat diffusion. Many of the early prominent quantitative financiers and financial modellers came from theoretical physics. 

Much of my earlier work, from my PhD, was actually on investigating emerging risks related to vehicles. I looked at creating an economic damage calculator from motor vehicle collisions, and I looked at how the risk landscape may change over time as more technologically capable vehicles make up a larger part of the traffic mix. So I was looking at the insurance perspective and the road safety perspective over time. We should expect our roads to get safer over time through the introduction of these more advanced safety-aware vehicles, that can make decisions on your behalf in safety-critical moments, but we had few studies being done at the time that actually gathered the evidence together to paint a realistic picture. All of this research drew on insights from different disciplines, so my PhD was pretty interdisciplinary.

What research projects have you been involved in?

We just completed one research project and we're starting another about illicit activities in the crypto space. Our role in the project just completed - which was on the use of crypto to fund terrorism financing through money laundering, and form prevention solutions - was to act as educators for law enforcement agencies around Europe. To teach them about how crypto works from the basics, connect them to other law enforcement agencies, allow them to discuss and share their background knowledge on forensic crime investigations, teach them about this new area that they may or may not have been exposed to, so they can apply their best practices built up through years of experience to this emerging risk domain.

And we're beginning a new project where we're more so focused on illicit activities related to scams. Our role again is to act as educators, while increasing our own level of understanding in terms of how malicious actors may behave in this ecosystem by tracking wallet transactions, forming networks, analysing who might be trading with who and when, and picking up on suspicious trading patterns, for example. We are more interested this time in knowing about the risk behaviours of those involved in the crypto ecosystem. Looking at how people behave and trade with each other. 

We are doing this for two reasons. One, to know how to better protect vulnerable people using crypto (for example, younger people trying it out for the first time), and two, to know more about the risk behaviours of those involved in this space. Anecdotal evidence would suggest that those involved in crypto have a higher tendency for risk, but there is a large silent majority whose views we are not really capturing. This might be, for example, younger people just curious to know about how finance works, how trading works, and how investment works. And there are multiple elements that we should be aware of. As Business School educators, it is great to see curiosity about how financial markets work in practice that you can access through your phones. But, on the flip side, it opens the scope for these people to be vulnerable to being exploited by more experienced malicious actors. So we're looking at how people behave in these markets, and we’re also looking at the mechanisms by which vulnerabilities can be exploited.

How does your research influence your teaching?

Cryptocurrencies are just an example of an emerging asset class within finance, and I like to place the emphasis on the word emerging there. Because really what I'm interested in is new developments in finance. Given my quantitative background and the research topics I am currently pursuing, a lot of this would involve the use of the advanced AI techniques I mentioned before. 

So how might these research interests and research activities feed into my teaching? I keep up to date with the latest developments in the financial domain, in sustainability, in corporate finance, in credit risk, and I also keep up-to-date with the latest use of AI models in finance. 

So I impart that to my learners. I bring that knowledge to them. I set them tasks so that they remain at the forefront of the use of AI in finance, getting hands-on experience with these models with bespoke, fresh and messy data so that they are ready-made to generate cutting-edge insights the second they step into practice. That is my goal every year. Bring practice to them.