One of the joys of Level39 is the calm. It’s a dojo of fintech. Another delight is the extraordinary spectrum of companies here. It’s almost as if they’ve been curated on the basis of some elegant juxtaposition. Let us harmonise. In one afternoon, I meet three, the first, The Thalesians, is a Quant Finance Think Tank, exploring how ancient Greek philosophy can be used as part of a series of ideas and principals to develop trading software. The second company, Creditz, creates blockchain infrastructure. The CEO used to be a pro poker player, before that, he worked for a hedge fund. With my afternoon topped off with a gentleman who was in the Army, serving in Iraq and Afghanistan, being awarded the US Bronze Star, before developing Voyage Control, “like air traffic control, but for logistics companies’.
They seem to have only one thing in common, as far as I can tell. All of them are a heck of a lot smarter than me.
What is it? The Thalesians?
“We’re a quant finance think tank. We originally started a quant finance discussion group, we still run events, in Europe, Zurich, London, New York.”
What’s ‘Quant Finance’? (for those who might not know;)
“It’s the practice of building quantative models to understand financial markets, and therefor how to trade them more effectively. In the summer of 2013 I resigned from a full time job at Nomura, the Japanese bank, to work on Thalesians full time and do research on systematic trading and to develop a relevant source software library, called Py Thalesians. And I also wrote the book, Trading Thalesians. Available from Amazon, Waterstones, and all good bookshops.”
I ask Saeed how he’s funded, (by his own trades), and we talk about trading, and currency strategy. “A lot of what you try to do when you model markets, it’s what you think will happen, and how you think the market will trade as a whole. One might have the right view on a potential outcome, but if you’re the only one with that ‘right view’, it may not be the right trade. It’s often about market narrative.”
I try to understand. “Is the intention to create software that can more accurately predict trading patterns?” I’m close ish. “The software tests hypothesis, it enables the user to explore an idea, then model and see the probable outcomes. The main user benefit is opening up innovative and alternative ways of looking at markets, deeper understanding. The big data route, text analysis of news, this is not as prevalent as it could be.”
I nod sagely and try steering the conversation onto safer ground. Esoteric Artificial Intelligence.
“If software can predict trading patterns better than humans, will it ultimately become an Ai challenge, rather than a human one? Will an ‘Ai race’ occur, with multiple super computers trading against each other, not even predicting the human trading patterns, instead, trying to predict each others? Like Supercomputers try to play chess against each other…”
Saeed reminds me we are talking about the real world of finance. “Any statistical tool … one needs to know the why an outcome occurred. It can’t just be a ‘black box’ giving an answer. One has to be able to understand why the outcome was predicted, or why it failed to manifest, when trading money, one must always be cognisant of the downsides, how much can be lost.”
I hadn’t thought of that. And now it’s time to move on to my next interview, where I’m going to ask how blockchain works. So help me god. The ancient Greek ones and the new.
The problem: Road Freight, it’s frequently very inefficient and fragmented, very manual in its organisation. As an example, 30% of trucks on the road at any one time are empty. In the US empty trucks travel 20 billion miles a year. The cost in fuel, man-hours, air pollution, congestion, vehicle wear, road wear, it’s a really inefficient industry. And as cities become more densely populated, the challenges, the problems, they increase.
We have an enterprise SaaS platform, currently very focused on helping busy logistics hubs, providing something like an air traffic control systems for trucks. Currently logistic hubs are all about queuing, there’s disconnect between stages, arrival, unloading, forklifts, they’re usually very reactive, planned by fax (!) or email. Just not organised. Many industries have radically transformed themselves with tech, but not logistics.
They have tight margins, they don’t have much for R&D, so they become increasingly more inefficient, and they can’t pay big wages for tech solutions.
It’s an ‘old school sector, mechanical, like construction, lacks automation, huge amount of waste. Often the people making the decisions don’t appreciate the costs of not changing. They accept the situation as normal and acceptable. Not much audit and so forth
So how does it work, Voyage Control?
It’s scheduling software. It applies speed, efficiency, streamlining the logistics processes, improving compliance, security, providing better management reporting and auditing.
Simultaneously reducing air pollution, traffic congestion, and improving the asset realisation for the company.
We have team here and in NY, we have about 20 major enterprises, eg, Olympia London, Earls Court, they experience the result being better for visitors, exhibitors, and organisers.
2014 was about working with 3 big hubs and making sure the platform operated well, now it’s about scaling up.
Tell me how you got into this:
When I worked in intelligence community, a lot of Intel collection was done in a siloed way, inefficient, and I became very involved in how to create a common operating picture for a battle field environment. Ultimately it’s about efficient decision making. Logistics was a complete cluster, so there was a massive opportunity to fix that.
Does the MOD have this? No.
The public sector could definitely benefit, from the MOD to the NHS, but getting it in there is way difficult, public sector procurement is a very long game.
Tell me about the award, Cognicity Challenge…
Yes, Canary Wharf Group’s Cognicity Challenge, we won the transport category. £50,000 plus acceleration.