Monday, April 15, 2024
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    AI: the key weapon in battling payment fraud

    AI is driving business growth, but it is also driving fraud. And what is the best way to beat AI fraud? Using AI, of course. Paul Skeldon takes a look at how Evina is making that happen

    In 2022, a staggering €8.44trn vanished through cybercrime. This alarming figure is anticipated to escalate as cybercriminals turn to AI to help perpetrate ever more complex attacks – from a range of scams (see page 6) down to stealing directly from mobile users through manipulation or device takeover.

    So, how can the telemedia industry tackle this emerging threat as powerful AI tools become more accessible to cybercriminals? The answer lies in using AI to beat AI.

    From the beginning, Evina has heavily invested in its AI-driven threat detection capabilities, creating state-of-the-art cybersecurity solutions tailored to mobile payments – coupled with a human team of malware analysts for a winning solution. This core technology serves as a countermeasure to the AI-powered industrialisation of malware.

    AI fraud detection uses artificial intelligence – or a set of algorithms – to monitor data, looking out for fraud. AI’s ability to monitor vast amounts of data coming in and spot patterns and anomalies that would simply be beyond the abilities of any human to spot.

    The key to making AI fraud detection work lies in data. Evina’s AI-based fraud detection, for example, is rooted in three fundamental components.

    Firstly, it features an immense and high-quality data pool, made possible by its partnerships across 80+ countries, daily analysis of more than 30 million transactions, deep web criminal modus operandi collection and a global network of honeypots designed to attract and trap malware.

    Secondly, it uses a cutting-edge fingerprint matching and prediction system, using sophisticated machine learning methods. This  empowers Evina to not only apprehend previously identified malware, but also to halt live malware upon initial contact, recognising variations of existing threats or completely novel cyberattacks.

    Finally, it leverages a highly effective security and countermeasure system that safeguards Evina’s script from reverse-engineering attempts and adapts to threats employing advanced dynamic cryptography techniques and polymorphic codes.

    These innovations continuously strengthen its AI, allowing the technology to instantaneously protect users in Morocco when malware is detected in Thailand – a truly global solution to payments cybercrime.

    “These three core components of our technology drive our value proposition, achieving a remarkable detection rate of 99.98% and a minimal false positive rate of 0.06%,” says Evina. “This enables our customers to protect their growth while significantly reducing complaints.”

    www.evina.com

    The advantages of AI fraud detection

    Using AI to detect fraud is a clear winner for many reasons, including:

    Real-time detection: AI-powered fraud detection systems can monitor transactions and activities in real-time, enabling rapid detection and response to fraudulent behaviour. This allows for immediate action to be taken, minimising potential losses.

    Adaptive learning: AI models continuously learn and adapt based on new data and evolving fraud patterns. By leveraging machine learning techniques, they can improve their accuracy and detection capabilities over time, staying ahead of sophisticated fraud techniques.

    Scale and efficiency: AI can process and analyse large volumes of data much faster than human analysts. This scalability allows organisations to handle growing amounts of transactional data and identify potential fraud cases efficiently.

    Multi-dimensional analysis: AI algorithms can consider multiple variables and factors simultaneously to assess the likelihood of fraud. They can analyse various data points such as transaction history, user behaviour, geographical location and device information to generate a comprehensive fraud risk score.

    Adaptive fraud prevention: By continuously analysing and understanding patterns of fraudulent activity, AI can proactively identify potential risks and vulnerabilities, enabling organisations to implement preventive measures and strengthen their overall fraud prevention strategy.

    The human touch: It’s important to note that while AI offers significant advantages for fraud detection, it is most effective when combined with human expertise and oversight. Human analysts can interpret AI-generated insights, investigate suspicious cases, and make informed decisions based on the outcomes.

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