Battle against AI-generated fraud will continue to intensify

• Fraudsters have been quick to harness the potential of generative AI to perpetrate various fraudulent activities.
• Businesses have no choice but to adopt AI tools, to give themselves a chance to forecast and anticipate the next moves of these fraudsters.

In today’s digital age, the landscape of fraud is evolving at an alarming pace. Victim profiles, which used to skew heavily toward the elderly and infirm, now include younger, fully functioning adults. 

In 2022, 20-59-year-olds reported 63 per cent of all fraud in the United States. Industries being targeted by fraudsters are evolving as well, and now include those in crypto and gaming.

In the past, most adults were able to see through scams and avoid them. However, the introduction of generative AI has been a game changer, transforming ordinary schemes into highly sophisticated efforts. 

Generative AI, a subset of artificial intelligence (AI), is making waves in the world of cybercrime. It is a technology that can generate content that is virtually indistinguishable from human-created content. 

Whether it’s producing convincing text, images, or audio, generative AI leverages deep learning and neural networks to create highly realistic and persuasive output at scale. 

Shady third-world country call centres have been replaced by autonomous AI tools. This capability has become a powerful tool in the hands of fraudsters.

Fraudsters have been quick to harness the potential of generative AI to perpetrate various fraudulent activities. They are scaling their efforts through automation, as they conduct conversational fraud using AI-powered bots, mimicking human interactions in channels like email, text messages, and even platforms like WhatsApp. 

These bots engage unsuspecting individuals, leading them to divulge sensitive information or engage in financial transactions that benefit the criminals. 

Furthermore, generative AI technology is used to produce deep fake voice recordings, making fraudulent phone calls even more convincing.

One area that is particularly concerning is the way generative AI is used to steal credit card information. By using AI-generated phishing websites, emails, and text messages, criminals can deceive individuals into revealing their credit card details. 

They can even use voice calls with Deep Fake technology to trick unsuspecting victims. The realism of these scams has made it increasingly challenging for users to differentiate between genuine and fraudulent communications.

Businesses’ responsibility to prevent fraud

As the battle against AI-generated fraud intensifies, businesses find themselves on the front lines of defence. 

They are, after all, the ones approving transactions that use stolen payment devices. They are also the party that will be hit with chargebacks and potential penalties, giving them a strong financial incentive to prevent fraud. 

Even when customers are to blame for their credit cards being stolen, they still will blame businesses for accepting payment. 

A recent survey found that 24 per cent of customers believe that the business where the fraudulent transaction took place is responsible.

Those customers are much less likely to do business in the future with a company that they believe mishandled their information. Businesses that are unable to detect fraud will see their customers make their purchases at the competitor down the road. 

The consequences of not detecting fraud are severe. The combination of customer churn paired with chargebacks and penalties makes for an ugly hit to the bottom line. 

Businesses could opt for a risk-averse payment denial approach. 

Historically, however, that approach means declining up to 20 per cent or more of legitimate transactions. Once again, this approach will have a significant impact on profitability.

Combatting AI-generated fraud

To combat the rising tide of AI-generated fraud, businesses and financial institutions are increasingly turning to AI themselves. 

These AI-powered fraud prevention solutions can process vast amounts of data in real time, identifying patterns and behavioural anomalies that may indicate fraudulent activities. Machine learning algorithms can continuously adapt to evolving threats, proving invaluable in the ongoing battle against fraud.

AI technology is crucial for swiftly and accurately identifying fraudulent transactions and preventing financial losses. 

By more precisely distinguishing between legitimate and fraudulent activities, these tools also help reduce false positives, ensuring that legitimate customer transactions are not mistakenly flagged as fraudulent. 

Those unwilling to adopt AI to prevent fraud will find it difficult to remain competitive in their field. 

An urgent need that demands attention now

The urgency of addressing the growing challenge of generative AI fraud cannot be overstated. Generative AI is in its infancy. 

Every single day, it continues to evolve, learn, and transform itself. Fraudsters themselves are learning daily how to better utilise generative AI effectively and scaling up their activities even more. 

As time goes on, the technological advances and improvements in fraudster skill sets will pose a potent challenge that must be overcome. 

Businesses must recognise their responsibility to protect their customers and themselves from the evolving threat landscape. They have no choice but to adopt AI tools, to give themselves a chance to forecast and anticipate the next moves of these fraudsters. 

Failing to do so can have dire consequences for digital goods sellers and their customers alike. Businesses must take immediate action to combat fraud and safeguard the trust of their customers.

• Alex Zeltcer, CEO and Co-Founder at nSure.ai, an Israel-based company combating online chargebacks and securing high-risk transactions from fraudulent activities.

Related Posts:

• Why we should not slow or abort the AI development process
• Generative AI to become a game-changer in financial services