Archive for March, 2017

Data Innovation Summit 23 March 2016

Last week we were proud to be a sponsor of the Data Innovation Summit in Stockholm and partake in the energy and enthusiasm of over 700 delegates/presenters/exhibitors sharing ideas, technologies, challenges and solutions within Big Data, Data Science and Analytics. Our ‘technology in practice session’ focussed on turning ad-hoc analyses into strategic models by industrialising your analytics (‘From 7 days to 7 seconds’).

We are entering the era of big data, sophisticated algorithms and rapidly emerging technology. Financial and analytical modelling is moving to the heart of how businesses are being managed and assessed. However these models are not being built in platforms that are fit for purpose. The result is that Boards, regulators and management are being asked to rely heavily on models that are slow, that are fragile, and that are opaque.

In our session, we showed how a-business can industrialise and automate their ad-hoc and tactical financial, analytical and statistical models. This will embed these models into a streamlined, controlled environment which is tightly integrated into the company’s enterprise systems on the incoming and outgoing data interfaces. We gave some examples of how this has been done in practice, and discussed the benefits that this gives an organisation.

We think it is crucial that organisations begin to integrate their ad-hoc analytical models into a modern, enterprise modelling framework to create reliable, transparent, collaborative and streamlined modelling processes. This means that the analytics processes will become faster, less resource intensive, less fragile and far more likely to be trusted and relied on by Boards for their strategic decision making.

Welcome Panos!

We are delighted to welcome Panos Theodoratos to our team!


Panos has joined the London office as a Senior Analyst. He is originally from Greece where he completed his Bachelor’s degree in Statistics and Actuarial Science. After completing his BSc, he moved to London where he did postgraduate studies in Finance and Econometrics. Panos previously worked as a statistician for a medical research organisation for more than two years where he implemented statistical and actuarial models with medical data. He then moved to the analytics team of Experian London where he contributed in business solving problems with econometrics, statistics and machine learning algorithms. He has experience in using different statistical tools such R, E-views, SAS and SPSS and a strong interest in predictive analytics.

Fun Fact: Panos shares his birthday with Carmen who is also in the London office. Some call this the Birthday Problem. In probability theory, the birthday problem or birthday paradox concerns the probability that, in a set of n randomly chosen people, at least 2 will have the same birthday. In the London office we have 10 people and 2 pairs who share the same birthday!