Machine learning proof of concept signed with multi-billion Euro asset manager

Insig AI plc (AIM:INSG), the data science and machine learning company providing solutions to the asset management industry, is pleased to announce that it has signed a proof of concept exercise with a European asset manager with assets under management (“AUM”) of several billion Euros.

In this initial proof-of-concept exercise on one of the client’s larger funds (valued in excess of €1 billion), Insig AI has been tasked to use its machine learning data and expertise to analyse and categorise the client’s portfolio. More specifically, the objective is to use a combination of linear and non-linear analysis methods to surface and understand relationships within the client’s investment datasets comprising approximately 2,000 companies. This will include:

• Identifying if there are relationships that are non-linear;
• Applying machine learning methods to categorical factors;
• Apply a factor screener to find best-performing stocks and portfolios; and
• Analyse twenty different factors, some binary, some continuous.

If this initial factor analysis and general proof-of concept is considered successful by the client, there are non-binding second and third phases of works, with the expectation that upon completion of phase two, the client would enter into a SaaS data framework licence with Insig.

Steve Cracknell, CEO of Insig AI commented: “I’m very pleased to have secured this initial contract. Whilst the initial contract value is small, it gives us the opportunity to apply our expertise to work with not only a prestigious client, but one at the cutting edge of using data analysis to further improve their investment performance. Furthermore, the potential follow-on work programmes become increasingly more involved with commensurate larger as well as recurring revenue opportunities.”

For further information, please visit www.insg.ai, or contact:

In the video below, CEO Steve Cracknell outlines the nature of the group’s business and its ongoing growth strategy