Industry experts tell us how businesses can leverage AI and Machine Learning to detect and prevent fraudulent activities more effectively.
W ith financial crime becoming increasingly sophisticated, businesses are under growing pressure to stay one step ahead of fraudsters. Traditional fraud detection methods often struggle to keep pace with the speed and scale of modern threats, especially as attacks become more automated and targeted.
Enter AI and Machine Learning( ML) technologies that are transforming how organisations detect and respond to fraud. By analysing vast datasets in real time, spotting subtle patterns and anomalies, and continuously learning from new threats, AI and ML are enabling faster, more accurate fraud prevention strategies. But how can businesses make the most of these tools, and what challenges must they overcome to implement them effectively?
In this feature, industry experts share their insights on the potential of AI and ML to revolutionise fraud detection and explain how organisations can harness these innovations to protect their operations, reputations and customers in an increasingly complex digital environment.
Mike Britton, CIO, Abnormal Security
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Modern attackers are increasingly weaponising AI to launch more sophisticated social engineering attacks at scale, and they appear to be thriving, with 98 % of security leaders reporting AI-driven attacks on their organisations.
With tools like Generative AI, even inexperienced and petty cybercriminals can now create highly targeted and convincing phishing and business email compromise( BEC) campaigns, eliminating the typos and grammatical errors that often help end-users identify traditional attacks.
Mike Britton, CIO, Abnormal Security
As AI becomes an increasingly valuable asset within an attacker’ s arsenal, it must also be used
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