Ravelin is an award-winning fraud detection and prevention platform for online merchants and the payments industry. Ravelin uses a combination of machine learning, graph networks and human insights to detect fraud before the sale happens, saving merchants millions in chargebacks, lost customers and reputational damage.

Worked as part of a research team on a two-year study focusing on understanding the impact of serious organised crime in local communities. Working closely alongside the police and partners such as the National Fraud Intelligence Bureau, we developed innovative methods to uncover the presence of a variety of different types of organised crime, including fraud and organised theft networks. Findings from this research have been published in 'Policing: a Journal of Policy and Practice', and 'Trends in Organised Crime'. The final report and a number of summary briefings are also available on the Police Foundation website.

A NIAT qualified Intelligence Analyst with over 5 years experience in crime and intelligence analysis within a law enforcement environment, specialising in serious and organised crime and network analysis. My role with Kent Police involved the analysis of a diverse array of data sets in order to produce a range of National Intelligence Model (NIM) compliant analytical products including: Tactical & Strategic Assessments, Problem & Subject Profiles, Geographic Analysis, Network Analysis, Telephone Analysis and Risk Assessments. My research and analysis has advised a range of customers on current patterns and trends, performance issues, upcoming risks and threats, and the most efficient use of limited resources in order to achieve maximum impact. I have also supported a number of high profile police operations in an analytical capacity, including the London riots and the dismantling of a number of serious organised crime groups.