Predictive Risk Management

Our algorithmic book management system ensures that you make most revenue from your portfolio as possible by using artifical intelligence to group exposure within your portfolio

Automatic Toxic Flow Detection

The future is here now. We offer the most sophisticated toxic flow detection system on the market. Lightening fast toxic detection which can dramatically boost revenues.

Automatic A / B book classification

Our statistical decompilation technology© allows firms to protect themselves from algorithmic traders

Seemless Integration

We integrate with popular trading platforms like MT4 & MT5 as well as liquidity bridges

Use Artifical Intelligence
to significantly optimize your hedging strategy

In most cases we can improve firm PnL by 20%, and we can prove this.

Risk book optimization

Optimise risk groupings and improve effectiveness of risk isolation strategies

Real time Portfolio Level analysis

Our user interface displays real time portfolio level analysis as well as historical results


Backtesting Services

We can show you exactly how much you can save using this system. We can demonstrate backwards and forwards tests of our algorithms on your real-time dataset

Easily integrates with your existing process

We have built in several analysis features to allow the system to run along-side human risk managers or alternatively it can be set to run automatically.

Our Team

Our team has expirence in AI, Risk Management, Quantitative Modelling, Regulation & Trading

Dan Moczulski

Commercial Director

Ashley Aberneithy


Dr Fraser Mackenzie

Research Director

Kevin Taylor


Ben Swann



Published Journals

Our products have been forged out of partnerships with some of the world’s leading universities and world renowned academic risk research centres. All our products are based on evidence driven research and implementation.

Coming soon


Information about our research, upcoming releases and company information is posted on our blog. A more informal way to communicate with the industry

Coming soon

Phd Candidates

Want to do your Phd with us? We have strong university links with whom we partner with

Academic Partnerships

Our strategic academic partners allow us to create challenging research training experiences, within the context of a mutually beneficial research collaboration between the Universities, and

Managing uncertainty through quantitative analysis

The aims of the project are to: (i) develop and employ advanced statistical, econometric and machine learning techniques to better understand the trading behaviour of individuals in speculative financial markets, (ii) develop means by which trading and market conditions data can be combined to produce real-time predictions of directions and volumes of trading activity in a given market. The project will be undertaken with the support of

Contact Us

Lets sit down and have a chat

Irongate House
22-30 Dukes Place, London
United Kingdom

P: +44 (0)203 544 5062

© 2017