Editor’s Note: This week, our founder spotlight is about Yves Guillaume A. Messy: Political Science student, self-taught programming genius, and founder of the insurance startup QGS Technologies. Buckle up for a long conversation with Yves Guillaume about his background, his company, entrepreneurship, and some interesting reads and personalities to look up to.
Dobson Chronicles (D.C.): Can you tell us a little bit about who you are and what your background is?
Yves Guillaume A. Messy (Y.M.): My name is Yves Guillaume Messy. I was born in Sub-Saharan Africa, and moved to Canada as a political refugee. I went to high school here, in Ottawa and in the Greater Toronto Area, before studying Political Science at the University of Toronto. I originally intended to study engineering prior to moving to Canada, which may explain how technical or mathematical my view of political science and international relations eventually unfolded. The rise of Big Data and Artificial Intelligence provided me with a unique opportunity to deploy machine learning and quantum computing -driven models of how international politics work and apply this view to financial markets. So in this way, I’m an accidental scientist, and still a definite foreign policy nerd.
D.C.: And what is it that drove you towards Political Science?
Y.M.: I had an early interest in global affairs, to the point where I still have this vivid memory of me at 10 years old watching the news, looking at Koffi Annan at the UN with intense interest. Since then I studied, volunteered, got involved in, or otherwise explored various ways to personally make an impact on some of the pressing global issues we face today, from access to finance among what Paul Collier refers to as “the bottom billion”, to human security issues, to issues of war and peace. Having this engineering disposition and this focus on the study of war and peace and global affairs, it seemed like a natural progression that I would take political science models that we traditionally were taught, and pretty much insert them into Big Data and Artificial Intelligence-related analytics, which is what brings me here today!
D.C.: You say you have an engineering disposition, but how did you concretely come to master the actual skills behind programming and that exposure to innovative technologies that you leverage in your startup?
Y.M.: Of course you can take coding classes in university, but I was lucky enough to to be really into video games when I was 10 or 11, so I have a little bit of a history playing with MS-DOS and Windows 95 from the command line, sometimes take video games apart or get free ones. And even though I took 6 or 7 years off of that to study political science intensely, with logic and math at the core of my approach, I had an easier time than most in relearning the main languages a few years later. It was easier for me to learn the basics of C++, Python, and Java, computational logic and basic data structures and algorithms, thanks to my earlier educational background. At the end of the day, to me, social sciences and computer science are both about logic and probability theory. That link what allows me to navigate both spaces from an interdisciplinary perspective.
D.C.: You learned programming on your own, so would ”student during the day – programmer at night” describe accurately your experience?
Y.M.: Exactly. Being a student at the University of Toronto was an immense privilege since the school has the third largest library system in the world. I had access to the best academic and hands-on resources available on C++, Java and Python, and then looked around for additional textbooks on data structures online. The issue for me was to find out what was the best language available out there to translate political systemic behavior into logic language. And I guess that quest led me from political science to logic, to stats, to mathematical logic, all the way to AI research and programming. Again, there are resources online available for simple translations, textbooks to help you implement programs, but at the core of it, it’s all logic and statistics.
D.C.: And so those long nights of studying led to the birth of QGS Technologies, the startup you founded. Can you tell us about what it is and what it does?
Y.M.: Yes, by the time we’re done with QGS Technologies, we want the political environment of an investment destination to be no more important than its temperature, when making the decision whether or not to invest. We recognize that political uncertainty overall will increase to highest levels seen pre-World War II, so our mission to reduce, or even eliminate political uncertainty’s ability to expensively prevent investment decisions from being made. QGS Technologies and our software, was a hobby research project initially, but two major political surprises Donald Trump’s election and the Brexit vote, combined with the hysteria that followed from both, motivated us to put a working solution out there as soon as possible. The timing worked out.
D.C.: About your company now, what is the key value that you are trying to create for investors?
Y.M.: Prior to starting QGS Technologies, my core business experience lied in private equity and venture capital; as an advisor, analyst, and limited partner, looking at risky emerging and frontier market investment destinations like Niger, Senegal, and Brazil as investment destinations. These often present a dilemma for institutional investors, not much data to gauge the risk and the evidence on the ground is often anecdotal at best, and often comes with a lot of moral hazard and reliability issues. To me, having that uncertainty reduced to a number at all times, to contribute to market participants’ risk management and investment decision-making models is key. This is effectively what we do for investors, we make this previously unavailable talk to our clients in real-time, in a way they and their models can understand, this saves them time and money, it augments their decision-making abilities.
D.C.: So you provide them with this number, and then based on their appetite for risk, investors will adjust their decisions accordingly.
YM: Exactly. We are working to provide one of the fastest real-time scores of any financial investment’s political risk outlook. For example, the typical private equity deal takes 6 months of due diligence, after which, investors decide whether or not to invest in a deal meeting. They then get stuck in politically risky investment destinations for five to seven years based on some of the most casually political considerations seen in finance today. We want to give investors that political agility, model it, and insert it into their workflow and board meetings, thanks to artificial intelligence’s recent progresses. That is fairly new stuff. Now, investors will be able to see the evolutions of the political situation in real-time and have a ‘liquid’ outlook of their investments’ political context. To us, this is key to increasing ease of access to finance worldwide.
D.C.: And so without trying to steal your secret ingredients, what are some of the technologies you leverage to achieve those goals?
Y.M.: We leverage open data and purchase others. We also use natural language processing, sound, video, and some other techniques such as traditional machine learning, some unconventional artificial intelligence techniques, and some really interesting big data visualization techniques that enable us to make sense of the huge amounts of data at once, because it can be overwhelming.
D.C.: During your last presentation at the McGill Dobson Centre for Entrepreneurship, you mentioned that you are also using virtual reality to streamline the due diligence process. Are you using proprietary equipment?
Y.M.: We prefer to be hardware agnostic, to focus on building a virtual reality platform for government relations and asset management exchanges, powered by blockchain technology. Blockchain technology will be key to this platform, to allow for cheaper verifiability (and therefore trust) between investment decision makers and the stakeholders they deal with for advice as they consider international investment. So for example, if you’re in New York, and you want to invest in a Brazilian opportunity, but you don’t have time to tour to the facilities and check on recent changes in the local political and regulatory environment, we hope to make it possible for you in days, not half-years. We have, however, looked seriously at custom hardware in Shenzen, China, specifically, but this is very much exploratory at the moment.
D.C.: How did you jump from having the concept and doing your research as a hobby to realizing your ideas into a business?
Y.M.: It was a bit of an accident, to be honest. I was at a conference in London around this date last year, where I heard a prominent banker speak about the implications of the Trump election on world markets, and how bankers couldn’t have seen it coming. He was explaining how events such as Brexit or the Trump election are not foreseeable, and I was sitting there in a room full of some of the smartest people in the world of finance, realizing that there were a few simple data points that could really help them see the big picture better. As a political commentator on these issues, I’ve had a track record of forecasting political surprises rather consistently, since the rise of emerging markets back in 2010. It occurred to me that, if I can manage to formally model some of my intuition forecasting dozens of earlier similar political surprises, these financial market participants’s work would become a whole lot easier, with respect to political risk. From then on, I started working with investment managers directly, to get a clearer picture of what’s being done poorly today. Engaging directly and validating some of my assumptions also showed me how and why some of the lesser quality political forecasts get made today. We are leveraging these lessons today, as part of our product design process.
D.C.: So it’s been about a year since that breakthrough moment. Where is QGS now? Are you already in operation?
Y.M.: We pitched the idea at a competition called Startup Bootcamp Insurtech in London, which was one of the first insurance technology competitions worldwide. At the time, we went from concept to proof of concept, which is what got us into the competition, and on to the final round but didn’t end up making the final cut because we lacked the capacity to service more than a few people at a time. So I went back to Canada to focus on scalability, quality assurance, and product validation. Based on these efforts, we were able to fine-tune our proposition, making it available became able to prototype users via APIs, robot-advisors (conversational computing interfaces) and some basics of our virtual reality solution. We are about to get into the go-to-market phase to make an alpha version of our software available to a wider audience.
D.C.: This is very exciting! So what is your vision for QGS in the future?
Y.M.: The way I see QGS going, I would like to see most international financial centers, from Tokyo to London to Paris or New York using Geoff, our AI, comfortably, as a risk-management colleague in a way. We want to make sure that we become a tool of reference when it comes to political risk in international investment management going forward. Hopefully, by next year, most financial centers will have some kind of QGS software available.
In terms of our business model, right now our beachhead strategy is to provide data on a Software as a Service basis. From there, we plan to add robo-advisors and virtual reality goodies to an eventual beta launch.
D.C.: Who are you currently working with on QGS Technologies?
Y.M.: QGS Technologies is a distributed team, which means that we are not bound by geography, but we have a core team of eight and a peripheral team made of crowdsourced efforts. Some of the core team members are people I was already with during the London startup competition, and some aren’t. Typically, I’ve learned that there are different teams to meet different needs at different stages of startup growth. We’ve been interviewing rigorously people from around the world, and our team now counts people from France, Brazil, the UK, Greece, Canada, and China. What matters is their ability to be comfortable in a virtual space and distributed teams, and their willingness to tackle complex problems at the intersection of political science and programming.
D.C.: Thank you for answering questions about your company. The McGill Dobson Centre for Entrepreneurship seeks to inspire entrepreneurs in the McGill community, so now has come the time for a little inspiration! I’ll start with a basic question: what is your definition of an entrepreneur?
Y.M.: To me, an entrepreneur is a problem solver who’s comfortable looking outside of the box, possibly with a sense of urgency. Entrepreneurship seemed a natural thing to me because I come from a family with a long tradition and experience in entrepreneurship, going back to 1935. I’m still learning to think in other ways!
D.C.: Would you define yourself as a risk-taker?
Y.M: Yes, in a way. One thing I’ve seen is that the more success I meet going forward, the better I get at taking calculated risks. Most people see a lot of risk in some things, but they simultaneously fail to see the risk in others “safe” options. The world of business, society overall actually, is being disrupted left and right, every day, in ways no one is able to foresee. You could say that given the future of work brought about by AI and other exponential technologies, doing nothing, not daring a little, is the riskiest move of all.
D.C.: What would be your biggest advice for our community?
Y.M.: The biggest advice I can give is to really get out of your bubble, of your comfort zone. We’ve never lived in such a time when established models of functioning are changing so fast and fundamentally. You need to always keep an eye on adjacent innovation hubs. Hang out in other faculties’ buildings, talk to people. Going forward, people who will thrive the most are those who are able to be post-disciplinary. One thing I’ve seen is that the ability to see across disciplinary boundaries enables you to see change sooner than colleagues who are stuck in silos.
D.C.: Can you tell us about the people that you admire and inspire you?
Y.M.: Oh dear, that’s a tricky one! First off, obviously Muhammad Yunus, who is a great inspiration. I’ve been lucky enough to meet him on a few occasions at the University of Toronto during my school time. As someone with a passion for access to finance, human security and international development questions, I was very curious the first I came across Banker to the Poor, one of his books about social entrepreneurship. The fact that he was able to use business methods to bring human security, dignity, and innovation at the grassroots SME level to most of the developing countries today is amazing.
Another one would be Ray Dalio, head of Bridgewater Associates, a US hedge fund. He has a very systematic, logical, and empirical way of looking at real world situations, in his case in Finance. But more than that, he is disciplined and rigorously focused on real-time learning from both mistake and successes while in business. That principled approach to change is inspiring.
And finally, Christine Lagarde. She is legendary, both as a policy-maker and as a trustee of financial stability, international cross-cultural consensus, and empathetic leadership whilst at the helm of International Monetary Fund. She did this right through, and past, more than a decade-long financial recession. She’s an inspiration on all accounts.
D.C.: Finally, do you have some great reads or resources that you would like to share with us?
Y.M.: I would suggest a book called the Mathematical Corporation by Angela Zutavern and Josh Sullivan, and The Seventh Sense, by Joshua Cooper Ramo. These books will tell you everything you need to know to start thinking about disruption today.
D.C.: What are preferred sources for keeping up with international news and political issues?
D.C.: Thank you for your time, I really appreciate you taking the time for this interview. Best of luck to you with QGS Technologies and we hope to see you again soon at McGill!
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