I have been studying Artificial Intelligence (AI) for Capital Markets for ten months now and I am shocked everyday by the speed of evolution of this technology. When I started researching this last year I was looking for the Holy Grail trading tools and could not find them, hence I settled for other parts of the trade lifecycle where AI solutions already existed.
Yesterday, as I was preparing for a speech on AI at a conference, one of my colleagues in Tokyo forwarded me an Asian newswire mentioning that Nomura securities, after two years of research, would be launching an AI enabled HFT equity tool for its brokerage institutional clients in May – here it is: the Holy Grail exists, and not only at Nomura. Other brokers have been shyly speaking about their customizable smart brokerage, e.g. how to use technology so that tier5 clients feel they are being served like a tier1. Some IBs are working on that, they just don’t publicly talk about it.
Talking to Eurekahedge last week I realized that they are tracking 15 funds that use AI in their strategy, I would argue there are even more than that because none of those were based in Japan (or Korea where apparently Fintech is exploding as we speak).
All this to reiterate that AI is an exponential technology, ten months ago there were no HFT trading solutions using AI, and we thought they were a few years away but no, here they are NOW. And the same with sentiment analysis, ten months ago they were just a marketing tool, now they are working on millions of documents every day at GSAM. Did I forget to mention smart TCA that’s coming to an EMS near you soon?
Stay tuned for more in my upcoming buy side AI tools report.
Artificial Intelligence (AI) is the new buzzword to talk about on the street. Financial institutions need to embrace AI, as we have explained in our January report, or else they risk to lose competitiveness or be coded by the regulators more than they can do it themselves.
I am in NYC next week to share Celent’s view on AI for capital markets. A little preview for your here.
Today we are at a crossroad where data scientists have the computing power, the alternative mind-sets to search and the willingness to look for narrow AI solutions, not the wide AI brain that we should get to in 2030 according to experts. This enables vendors to come up with amazing solutions from Research Scaling with Natural Language Generation to Market Surveillance/Insider Trading with Machine Learning Natural Language Processing or even Virtual Traders via Deep Learning of technical analysis graphics traders look at to take decisions.
The amount of data available is another big driver for the rebirth of AI, and regulators are looking at ways of accessing that data and using it. This is borderline what my colleagues would call RegTech, and it’s coming.
Our Q2 agenda reflects our understanding that you want to know more about AI: we will share ideas on solutions for the buy side, for exchanges and for the sell side. But in the meantime I hope to bring back some cool ideas from the big apple, hopefully also from the secretive quants working in the dark Silicon Alleys.
Most of the vendors I have profiled are specialists’ boutiques, but the cost of such research is however so enormous that generalists are trying to productize their fundamental research for various sectors, from health to homeland security, including financial services in partnership with financial institutions.
This morning I woke up to great news that Microsoft is at the forefront of Deep Learning on voice, imagine what this could bring to Anti-Money Laundering or Insider Trading products. The other news was that some top quants of Two Sigma just solved an MRI algo to predict heart disease, and I hope other great minds will, as most of them usually do, also give back to society by applying their amazing knowledge to such grand challenges.
- Scenario for the SD2C to keep a slot on the desktop is a combination of extremely modernized chinese walled and balance sheet optimized platform that aggregates, routes and matches as much investor flow as possible (some of it coming from MD2C RFQ platforms, some of it not) but also takes part in a Multidealer (not to client) consortium-like platform for their unmatched inventory and/or for the large size enquiries/indications of interest of their clients? It could be that some clients prefer to have 2-3 really good relationships with 2-3 dealers that have SD2C platforms that serve their particular needs (algos, primary issues, inventory, etc), and use their desktop space for these 2-3 venues rather than having to link up to the many MD2C platforms.
- Scenario for the MD2C to keep their currently extremely robust slot in the desktop of investors, before all investors get extremely robust OMS and EMS technology to buypass the MD2C (not soon!) or go for the SD2C-only route, could be to enable wholesale, institutional and retail flows to interact. In CDS indices (which are liquid) we have seen how Tradeweb has gained more than the majority of market share by doing that (and not only): enabling investors to stream wholesale liquidity. Could it be done in corporate bonds? There is currently no interdealerbroker (IDB) e-trading taking place in corporate bonds but could a MD2C platform add that IDB2C functionality? You can read more about IDB2C in The Blurring of the IDB Vs. D2C Models in Fixed Income and FX report. The alternative would be for the MD2C to offer the credit OMS/EMS technology to investors, and some are already working on this.