Case Study: Trustev
Complete end-to-end design, development, testing and maintenance of an AI-backed fraud detection system.
- Proof of Concept
- Machine Learning
Pat Phelan and Chris Kennedy, two Irish based serial entrepreneurs came together with the shared vision of reducing e-fraud, enabling safer transactions and getting more people through the online sales pipeline. Trustev started in 2013, with Chris & Pat who had the vision for a product that could radically reduce e-fraud rates while maintaining a strong user experience – something that very few businesses were able to successfully execute.
Pat and the team had a clear vision of how they wanted to achieve this. The technology is the vehicle upon which their vision could be executed upon. Trustev took on investors who shared this vision with the team, with the pressure of taking investors came clear targets. Investors wanted to see results, and fast! They would need to hire a team to build out this product to ensure that the agreed milestones could be met. Hiring in-house staff can take 2-3 months and even longer for onboarding experienced team members. Being situated in Cork, Ireland Trustev were competing for top talent with companies such as Apple, Dell and EMC – it was clear from the outset that attracting the necessary level of talent in Cork was going to be an uphill battle.
Pat searched for technology partners who could quickly assemble a team to get the Trustev MVP developed in a short time-span. They were looking for very specialized professionals with particular expertise in developing advanced machine learning algorithms. Not alone did they require just any machine learning experts they required ones they would be aligned in terms of vision and mission. At the time, the Razor group were a well-established brand in Ireland having completed high profile software projects for RTE (Ireland’s national television and Radio broadcaster) and Meteor (Ireland’s largest telecommunications company), when the introduction to Vuk Mirkovic, CEO of the Razor group was made. It was clear from the outset that Razor would become a significant part of the Trustev journey.
Within 2 weeks of meeting, the Belgrade based development team were up and running. The goal was clear – to decrease losses from online fraud on eCommerce stores by over 50%, how to get there was in the capable hands of the Razor development team.
The Technology Stack Used
A combination of web and mobile programming technologies were used to develop this solution for Trustev, as well as tools for machine learning and data science.
An automated fraud detection system based on a machine learning algorithm. This out-of-the-box solution assesses over 1,000 parameters to assess the customer’s digital footprint and determine if they are a valid, genuine user looking to make a purchase. The end-to-end solution can be integrated with all major eCommerce stores.
A clean, seamless interface with a robust, scalable backend and a fully documented open API.
Our solution has reduced losses due to online fraud by over 60%, saving millions of Euro for eCommerce merchants all across the globe.
Parameters used to assess digital footprint
Reduction in losses from online fraud
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