Malaysia is in a cybersecurity emergency, as evidenced by official statements. According to Securities Commission Malaysia (SC) executive chairman Datuk Seri Dr Awang Adek Hussin, the number of fraud cases in Malaysia has skyrocketed since 2020. Furthermore, Surfshark released a report cementing Malaysia’s eighth position as the country with the most data breach cases as of 2023. 

From such evidence, we can see the landscape of cybersecurity threats evolving in sophistication. In return, this urgency calls for more proactive fraud detection involving artificial intelligence (AI) to stop criminal activity from occurring in the first place. How does it work?

Harnessing AI in Cybersecurity and Fraud Detection

The Power of AI in Fraud Detection

AI is a highly dynamic and adaptive defence mechanism because it can learn from historical data fed by users. This fraud detection technology will skim through numerous data to discover repeated patterns, enabling it to detect various types of the most common frauds. 

These examples include but are not limited to credit card data theft, the creation of sockpuppet accounts for malicious purposes, taking over legitimate user accounts, and credential stuffing with multiple repeated login attempts. To prevent such frauds, AI will detect user IPs, numerous login failures, unauthorised purchases, and any other signs pointing to cybercrime acts.

Benefits of AI in Fraud Detection

Manually responding to cybercrime threats–especially when automatic bots are involved–is an arduous task that costs money and time. At the same time, every second counts in cybercrime prevention to avoid any losses. 

However, AI can benefit any business’ fraud detection process by detecting and responding to real-time incoming threats. Furthermore, they can continuously improve their detection and preventative systems by sifting through numerous data at a rapid speed (machine learning), which helps them keep evolving against more sophisticated modus operandi. 

As a result, this will significantly reduce reactive efforts and strengthen cybersecurity to gain consumers’ trust.

Real-World Use Cases

Many companies have used AI for their fraud detection processes, with two of the most notable ones including Rakuten and BlaBlaCar. 

Rakuten is one of France’s biggest e-commerce providers, seeing a lot of traffic daily. However, some bots would flood the server among genuine users to shut down the website’s operations. While Rakuten used to employ many human resources to prevent attacks, now they have switched to AI for real-time threat protection and freeing up both their server load and their workers’ time. 

Next, BlaBlaCar–an online carpooling system widely used in France–also employs AI to safeguard their user’s data without compromising their experience by masking their personal information such as their name, address, payment methods, and recent trips. Their artificial intelligence system still works well because it detects the most common fraud patterns without relying on personally identifiable data.

Risks and Challenges

While AI has proven highly beneficial for fraud detection, it still has risks. One of the most potentially dangerous ones is malicious actors’ attempt to circumvent the AI’s detection technology. Instead of using automated bots that the AI may catch, they will resort to non-automated threats, such as social engineering, to gain real users’ trust.

Aside from the threat potential, sometimes AI may generate a false positive report flagging genuine users as fraudsters. Therefore, companies must monitor the AI system to ensure it is working as intended.

The rise of digital application uses among business owners and individual consumers will entice more malicious criminals to harvest such priceless data for their gains. However, AI can detect and prevent criminal patterns immediately, especially against a more sophisticated method. Additionally, while AI has a high upfront cost, its long-term benefits can help companies save money and resources for cybersecurity safeguarding, giving them more time to innovate. Thus, AI is a highly indispensable technology for fraud detection.