By Ben Wong
Did you know that last year, it was reported that scams in Asia resulted in an estimated US$688 billion over a period of 12 months? In Singapore alone, businesses faced losses of around S$6.6 million (USD$5 million) due to fraudulent attempts, while over half of businesses in Hong Kong and Malaysia experienced cyber-attacks or data leaks.
The year also saw scam syndicates evolve their tactics, targetting offline retailers with card-not-present fraud, proving that fraud attempts are no longer primarily online.
Fraud is becoming increasingly insidious, and the growing sophistication and frequency of such activities are impacting consumers and businesses – not just financially, but also psychologically. The looming threat of scams can cause the consumers of today to feel more unsafe than ever when shopping. For businesses, which depend heavily on consumer trust, this creates significant operational risks, threatening customer trust, loyalty, and reputation.
While many are doing what they can to protect themselves from scams, it’s hard to keep up with the increasingly advanced tactics being used. This calls for businesses to strengthen their risk management capabilities, not just to protect their bottom line but to also demonstrate their commitment to consumer safety and enhance their credibility.
Bad actors are scaling their operations
Just as AI and technology have improved processes, they have also enabled bad actors to scale their operations, automating and launching attacks more easily and rapidly across multiple touchpoints. Fraudsters are increasingly leveraging tactics like deepfake impersonation and automated social engineering to extort money or steal personal information, making such attacks more prevalent across the globe.
In the region, phishing scams are on the rise, targeting individuals to reveal sensitive information like passwords and credit card details. This not only results in financial losses but also exposes consumers to the risk of identity theft, and misuse of their personal data.
These phishing attempts have also resulted in fraudsters going further to engage in acts like card testing, where credit card details obtained, tested and active cards are sold for a high price on the dark web. Stolen card details are also being used to create synthetic identities to deceive retailers of inventory and money. These virtual identities that combine both made-up and legitimate personal information are harder to detect and prevent, causing a threat to businesses.
Refund fraud is becoming increasingly common too, where fraudsters earn by requesting for business refunds after familiarising themselves with a business’ policies.
Static, rule-based detection systems are no longer sufficient
As new payment methods emerge, risk management has become an essential line of defence for businesses—not just to protect consumer trust but also to safeguard their revenue and uphold accountability in an evolving landscape. Static, rule-based detection systems are no longer a fit for an environment where fraudsters continually refine their tactics in real-time.
To stay ahead, businesses must adopt a dynamic, hybrid approach to risk management — one that leverages automated risk assessment and machine learning to recognise patterns and adapt fluidly to emerging threats to safeguard payments and customer data in real-time. One way would be to integrate a robust, multi-layered digital infrastructure with the following considerations in place.
- Prevention: A business’ tech stack must be capable of anticipating fraudulent activity before it occurs through analysing past transactional data and identifying potential risks.
- Detection: Real-time pattern and anomaly monitoring that signal potential fraud should be a standard part of daily operations, ensuring suspicious transactions are flagged promptly.
- Response: Rapid action is crucial – real-time detection must be paired with swift responses to protect compromised customer information and minimise the impact of fraud attempts.
AI: A powerful ally against fraud
The potential of smart risk management solutions is immense, allowing businesses to enhance security without disrupting payments. Whether through dynamic authentication checks (Dynamic 3D Secure), network tokenisation, or even A/B risk experiments, these automated solutions strengthen risk management while maintaining a smooth payment experience.
With vast amounts of payments data at their disposal, businesses should view data coupled with AI and machine learning as a strategic tool to enhance security, optimise operations, and drive smarter decision making. This is especially critical for businesses handling large transactional volumes, as robust fraud prevention detects hidden threats within the payments infrastructure and helps businesses respond in real-time—or even preemptively—before attacks occur.
At Adyen, we’ve seen that leveraging AI and machine learning can reduce manual risk rules by 86% on average, and help to reduce false positives as well as prevent chargebacks before they occur. .
That’s why we continuously look to build integrated solutions that provide businesses the ability to strike a balance between fighting fraud, optimising costs, and maximising revenue. As fraud attempts grow in sophistication, businesses must embrace a proactive, integrated approach to security. It’s no longer just about staying one step ahead —inaction risks not only financial loss but also irreparable reputational damage. With AI advancing at an unprecedented pace, integrating it offers numerous advantages—from outsmarting fraudsters and gaining a competitive edge to doing right by the consumer — enabling businesses to uphold their integrity in an increasingly digital world.
Ben Wong is General Manager, Southeast Asia and Hong Kong, Adyen