UNFRAUD

Project "UNFRAUD" data sheet

The following table provides information about the project.

 Partnership

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Map

 Project objective

'The impact of cybercrime is a growing concern in a society that increasingly interacts online. In the EU the cost of cybercrime has reached €871 billion a year and fraudulent card transactions amounted to €1.27 billion. The high number of online frauds coupled with the low level of cybersecurity deters businesses, and in particular SMEs who may not be able to afford comprehensive anti-fraud services, from fully exploiting the potential of e-commerce. UNFRAUD is a software product that prevents potential online fraud scenarios by analysing previous and current fraudulent invents through deep learning artificial intelligence to tackle the new challenges that fraudsters devise. UNFRAUD’s algorithms are similar to one’s used by Google for self driving cars and facial recognition (i.e. deep AI that recognizes human errors, behaviours and surroundings) and through this deep learning it is able to detect 'fraudulent' behaviour. This makes UNFRAUD much more reliable as well as greatly reducing the cost of anti-fraud services, allowing companies to operate and grow safely. During the Phase 1 feasibility study the project will focus on identifying and securing the key partners required for commercialisation, establishing a sound business model and commercialization strategy, and planning a pilot test with a bank, big e-commerce, enterprise, telecommunication company and public administration in order to fully demonstrate and assess the products capabilities.'