Experian , a global data and technology company, has acquired NeuroID for its fraud detection capabilities in combating AI-enabled fraud. Details about the collaboration capabilities NeuroID's features upgrade Experian's fraud risk suite by offering additional insight into digital behavioural signals and analytics for both new and returning users across the customer journey.

This includes activities such as account creation, logins, and transactions. NeuroID's behavioural analytics solutions are currently accessible via CrossCore® on Experian's Ascend Technology Platform™ as an important tool for detecting fraud. Experian's identity verification and fraud prevention solutions assisted clients in circumventing around USD15 billion in fraud losses worldwide in 2023.

By incorporating NeuroID into Experian, clients can now rely on a single service provider to actively monitor and analyse a user's real-time digital behaviour, such as their form navigation and data input methods. The rise of generative AI-powered fraud has prompted companies in various sectors like financial services, healthcare, and ecommerce to explore other fraud detection technologies like behavioural analytics. By incorporating insights from behavioural analytics into their fraud prevention strategies, businesses can combat fraud in real-time, and safeguard against identity theft, account takeover, bot attacks, and fraud rings.

This also helps businesses to deliver a better customer experience. Experian officials have stated that the acquisition of NeuroID accentuates their commitment to providing accurate data, analytics, and insights to combat fraud. By collaborating with NeuroID, they aim to create solutions that not only identify risks but also help businesses to confidently navigate the online environment and trust their transactions.

NeuroID representatives declared that in this era of AI-powered fraud, companies face significant challenges in developing their fraud prevention strategies. Having NeuroID tools they obtain a fresh perspective on assessing user risk through behavioural interactions. Also, this approach equips them with an early defence mechanism to identify complex fraud schemes and bot intrusions.

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