With the rapid development of AI, fraudsters are becoming increasingly organised and sophisticated. Instead of lone actors, we’re seeing well-coordinated criminal teams that are more focused and skilled at identifying vulnerabilities than ever before.
Yet, data shows that 39% of businesses took no action following their most disruptive breach in the previous 12 months, giving cybercriminals the opportunity to continue cashing in and turning fraud into cybercrime.
The power of AI
One of the most powerful tools that fraudsters have started implementing into their arsenal is AI bots. These bots enable new types of fraud and present significant challenges for businesses. In 2022 alone, £177.6 million was lost to impersonation scams in the UK, and as AI-powered deepfakes and voice cloning improve, the risk of fraud will only continue to grow.
To protect themselves, businesses must stay informed about the latest fraud tactics. They need to understand how criminals are using AI-powered bots to launch and scale attacks, how deepfakes and synthetic identities are evolving, and most importantly, how to defend against these threats.
Historically, scammers and fraudsters were limited in their resources. They often operated alone, relying on their ability to trick people. Once blocked, they would usually give up and move on. However, this has now changed, and fraudsters are forming organised teams and using AI to enhance their deceptive tactics.
For online businesses, generative AI makes it harder to differentiate between genuine users and fraudsters. One common tactic involves using AI-powered phishing templates to gain access to account information and credit card details. These AI-driven “chatbots” mimic real businesses by copying their speech and text patterns. Deepfake technology further complicates matters by creating highly convincing AI-generated likenesses of real people.
The era of deepfakes
Deepfakes are making fraud increasingly complex. The technology enables attackers to impersonate victims to make high-value purchases by creating synthetic identities and mimicking voices. In this way, deepfakes can trick customer service into approving transactions. Fraudsters can even manipulate videos with lip-syncing techniques that are hard to detect.
Businesses are only just starting to realise what a major problem deepfakes will become for them. In the future, AI-powered bots could make calls without human involvement if we don’t take action now. This poses a significant risk to both businesses and consumers. To combat these sophisticated attacks, businesses need to implement high-performance machine learning models into their technology. To effectively fight deepfakes, we must understand the tools and techniques being used and implement AI-powered tools that match the speed and scale of criminal activities.
Fraud resilience
Risk intelligence teams play a crucial role in safeguarding businesses against AI-driven fraud. By analysing various fraud types and collaborating with data scientists, they can feed information into models and cross-reference it with past consumer behaviours. This allows them to continuously adapt their defences as fraudsters evolve their tactics.
To build resilience against AI fraud, companies must work closely with intelligence teams to identify anomalies and incorporate them into feedback loops. This enables systems to learn faster and detect fraudsters more efficiently. By analysing data, such as IP addresses and device information, risk intelligence teams can identify users who repeatedly engage in fraudulent activity using multiple fake accounts, and take steps to block them.
While AI chatbots pose new challenges, the good news is that solutions are also evolving. Prioritising a strong fraud prevention strategy is essential. This might involve partnering with a fraud prevention provider, forming a data intelligence team, or creating a comprehensive fraud prevention framework.
By combining in-house capabilities with strategic industry partnerships, businesses can focus on customer loyalty, retention, and profitability.
- Cybersecurity