Does Generative AI Make Current Biometric Security for Payments Obsolete?

For the last few years, biometric security has been touted as the future of payments. Traditionally, biometric technologies like face recognition are safer than the user name/password system. However, there have been concerns. For example, in his book “A Hacker’s Mind“, the renowned security technologist Bruce Schneier highlights the risks of biometrics data. He talks about how the “relative immutability” of biometrics like fingerprints and retinal scans only makes them safe when protected.

Talking about risks, Bruce points out the ease of “creating a new password” whenever it is revealed or stolen. This is not the case for biometrics. For instance, in the event of a “stolen” thumbprint impression, individuals cannot generate a new thumbprint.

If not biometrics, what is the way forward for the payments industry? As it stands, generative AI technologies look promising for transforming payment security in the future. 

 

Is Biometrics Security Becoming Obsolete in the Payments Industry?

In recent times, voice-based biometrics, along with one-time passwords (OTPs), successfully authenticate customers in the banking and payments industry. For instance, voice biometrics security has been used in account openings, payment transactions, and KYC (Know Your Customer) procedures. Notably, biometric technology is easy to implement from a technical standpoint and could accelerate customer verification. 

However, over the past decade, biometrics security is also facing challenges as a secure form of user authentication. John Ainsworth of CUSO points out that the mechanism of the “one-time password technology has remained stagnant and unchanged for the past two decades.”

In recent years, hackers have unleashed OTP bots to break into the most secure payment systems and compromise security measures. Threat actors used these advanced bots to obtain 2FA codes from susceptible victims.

Similarly, bad actors are also finding opportunities at exploiting voice-based biometrics systems. One such threat is the use of synthetic voice attacks by hackers. AI-generated synthetic voices sound extremely similar to real voice – and are easy to generate with only a minute of voice data. Hackers can use these deepfakes to manipulate and modify a host of online videos, recordings, and images.

 

Can Generative AI Transform Payments?

Some of the popular examples of technology-driven payment systems include cryptocurrencies, embedded finance, and the metaverse. The widespread acceptance of technologies like AI and ML in the payments sector has delivered business value in the form of faster & safer transactions as well as enhanced user experience.

In particular, AI technology has been instrumental in the payments industry for:

• Forecasting fraudulent transactions
• Reducing the rate of false positives
• Minimizing operational costs
• Assessing financial risks accurately

The emergence of generative AI tools promises to elevate this technology to the next level. In particular, the emergence of synthetic data is an exciting use case of generative AI for identifying any person. While traditional biometrics security remains limited to the physical and behavioral traits of any person, synthetic data can prove viable to train generative AI models for accurate identification.

Let’s look at some of the key business areas in payments where generative AI technology can make an impact:

1. Fraud Prevention

Payment processing companies can leverage generative AI capabilities to prevent (or reduce) fraud. For instance, generative AI models can improve the effectiveness of voice-based biometric systems. By analyzing a larger base of voice data, they can accurately improve the identification of voice patterns. Similarly, when powered by generative AI, biometrics systems can monitor and analyze human behavior and how people interact with devices.

2. Retail Payments

According to Mastercard research, 61% of consumers are more likely to use digital payments when provided with personalized product recommendations.

By integrating tools like ChatGPT into payments, retailers can simplify and accelerate how shoppers compare and buy online products. Based on the user’s prompts, ChatGPT-esque tools can recommend the right products and expedite online product searches. Besides saving valuable time, this technology can improve the overall user experience.

 

So, Can Generative AI Make Current Biometric Security Obsolete?

Is generative AI technology mature enough to replace the biometrics system in the payment industry? In practice, this technology is still in its infancy stage and requires continuous improvement. For instance, generative AI must address issues related to data accuracy, data security, and infrastructure before gaining mainstream acceptance.

Among the possible use cases, tools like ChatGPT can serve as a “virtual assistant” to process user payments. Driven by predefined rules of consent, generative AI models can further streamline the payment process by:

• Enabling voice-activated and contactless payments
• Securing payment transactions by detecting any anomalies or signs of fraudulent activities
• Building the user’s trust in digital payment systems

Additionally, generative AI can accurately authenticate user identities on voice-activated payment processing systems using real-time fraud detection mechanisms. For instance, it can power behavioral biometrics to analyze how individuals interact using their devices. This includes behaviors like:

• The angle at which they are holding the device
• The amount of pressure they are applying on the screen
• Other factors including typing rhythm, screen swipes, and directional motions

Going forward, generative AI technology can enhance the customer experience and drive enterprise-wide cost control. Despite the immense potential of this technology, the payments industry will continue to have a “human in the loop.” For example, the human element is needed as the control mechanism for data security and privacy issues.

As more AI systems ensure payments, it’s vitally important for the payments industry to protect sensitive customer information. According to some cybersecurity professionals, the security of generative AI tools is much below that of most enterprise applications.

 

The Future

To summarize, the AI-led technological advancements can play a transformational role in the payment industry. Compared to traditional biometrics, generative AI can prove better at preventing financial fraud and improving customer experience. Organizations can embrace generative AI technology to handle the growing volume and complexity of online fraud.

However, it would be prudent to say that it’s still too early to predict if generative AI will make biometrics absolutely obsolete. In fact, generative AI can complement biometrics security with capabilities like behavioral analysis, which can further enhance the authentication process.

Over the last 12 years, Verinite has been developing customized payment solutions for a host of banking and payment processing companies. We are partnering with both new and established players in the payments industry and helping them innovate in a fast-changing world. Interested in exploring our range of modernized payment solutions? Get in touch with us today!