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Challenging behaviour FeatureSpace’s ARIC Engine is revolutionising the way that banking businesses combat fraud and security threats. Luke Reynolds, the company's Fraud Director, talks through its capabilities FeatureSpace is the world’s leading producer of adaptive behaviour analytics, with ARIC, its fraud-fighting engine, helping to keep organisations safe in 180 countries across the globe. By profiling customers using the mass of unstructured data that banks receive daily, ARIC identifies anomalies more efficiently than previous technology, while the engine’s self-learning capability, means new fraud attacks are combatted by a constant upload of new information surrounding the threats. FeatureSpace’s main focus when engineering ARIC was the vital importance of understanding the consumer and identifying unusual behaviour patterns upstream before a transaction takes place. From how they log in, to what they do on their screen, ARIC uses these many pathways of information to build up a profile – and with customer-not-present fraud forecast to cost retailers and financial institutions $7billion by 2020 in the US alone, knowing who your customer is has never been more important.

Data overload Due to the vast technological advances that the western world has acquired for convenience, large banking businesses find it difficult to develop an individual profile of the thousands of consumers that utilise their many products. Having multiple devices and using them all in different ways to process transactions, means that organisations end up with a huge wealth of data, but much it is not well-defined or well-structured.


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The questions that are being thwarted by this influx of unstructured data are vital ones: How do you know your customer? How do you build a profile? How do you understand what’s normal behaviour for a customer when potentially you never see them? FeatureSpace’s response to these questions is to use data collected prior to any monetary transaction to build up a detailed picture of the customer, so when he or she logs into their mobile app, for instance, the way that they type in their passcode, followed by the way that they navigate through their screens, creates a footprint that allows ARIC to determine if the person accessing the account is genuine. Technology that preceded ARIC used expensive means of understanding normal behaviour for the consumer, based on multiple layers of defender technology to build a rich behavioural profile score. ARIC gathers information from many channels but flows it directly into one engine in order to produce a non-monetary consumer file long before a transaction has even taken place.

Social engineering The most challenging fraud to detect and combat is customers under duress being forced to use their banking technology to transfer funds to their attacker. Otherwise known as social engineering it’s a difficult case to solve, because how do you know it’s fraud if the person has logged in, using the details as they would normally do? Thanks to ARIC’s profiling system, FeatureSpace is able to identify nuanced screen behaviour, such as logging in slower or navigating the screen with a different Summer 2016

Profile for Fintech Finance

Fintech Finance Magazine Summer 2016  

Fintech Finance Magazine Summer 2016