Just like so many industries are veering towards using cutting-edge technology like AI to improve their processes, so too is fraud detection. In order for humans to detect fraud, there is an overwhelming quantity of traffic and data to sift through, which can be difficult to monitor.
Artificial intelligence and machine learning are becoming increasingly important in the fight against fraud. Why? Simply because they can process incoming data and block new threats in a matter of milliseconds. This article explores some of the ways in which AI is being used to detect and prevent fraud, as well as some of the potential pitfalls of relying too heavily on automated systems.
How does AI work when it comes to fraud detection?
Using a group of algorithms that monitor incoming data in real-time, AI can detect and fraud threats before they arise. Unlike standard fraud software, AI learns with historical data and can uncover fraud patterns, as well as the rate of likelihood of fraud – and at incredibly fast speeds. It will then flag transactions for further investigation.
What are the common types of fraud that AI can detect?
● Transaction fraud
The eCommerce industry especially is facing many challenges with card fraud. With AI, you can discover which items are the most targeted by scammers, what kind of shipping information is most at-risk, and which card payments should be blocked.
● Fake account creation
Social media is full of bots, trolls, and fake accounts. These fake account creations give scammers the ability to spread malware, ruin your analytics, and destroy your reputation by distributing false product reviews. AI can track many variables to block all bots while still letting through genuine users.
● Multi-Accounting
AI can be used to analyse data points that call out suspicious user behaviour, like poker bots, cheating players, and even affiliates that bring in low-quality traffic to your site.
● Email phishing
A popular and fast way to steal confidential information, scammers put out convincing messages in the hopes that the sender will click on it. AI can work through banning IP addresses and domains from suspicious networks. Furthermore, authentication protection includes email verification.
A cautionary tale
With all the good that AI can do in identifying threats, it can still be manipulated. AI systems are built on the rules used to train it, so making any small and subtle changes can gradually steer AI in the wrong direction. Furthermore, hackers are also getting craftier – they can reverse engineer these AI systems to expose vulnerabilities and gain access to sensitive data. In fact, modifying any input data can lead to system malfunctions.
Worst of all, perhaps, is that cybercriminals can use AI to scale their social engineering attacks. For example, AI can be used to create deep fake content, share on social media, and attract users to click phishing links. The end result? An individual’s security is compromised.
Lastly, sometimes good old-fashioned manual reviews are just preferable: false positives can and do happen. AI still lacks human psychology, which should be applied when you’re trying to get to the bottom of understanding why a user’s action is particularly suspicious.
Get in touch with FraudWatch for effective fraud prevention
Using artificial intelligence to detect fraud has helped many businesses avoid financial ruin or reputation damage, proving that it’s a significant tool with plenty of potential. FraudWatch specialises in protecting businesses across Australia against all types of online cybersecurity threats. Work with us to ensure your organisation is protected from phishing attacks, fake mobile apps, dark web prevention, cyber threats, and social media impersonation.
Talk to our analysts today to find the best approach to protecting your organisation with our premium cybersecurity services.