5 Ways Generative AI Is Revolutionizing The Payments Industry

According to a recent Visa Consulting and Analytics (VCA) report, the impact of generative AI on the payments industry will significantly help businesses secure more customers, drive stronger engagement, and automate invoicing for streamlined transactions.

As the industry continues its emergence, businesses have been keen to implement generative AI as a driver of digital transformation.

The payments industry is no different, and as the post-pandemic recovery has seen a widespread transition towards a cashless society, the arrival of the age of GenAI appears to be timely for providers and clients alike.

Industry leaders are bullish on the future of generative AI in payments. “Generative AI has the potential to revolutionize how we think about payments automation, fraud detection, and customer experience,” says Erin McCune, a payments expert at Bain & Company.

“We’re already seeing leading firms leverage these technologies to drive tangible business impact, and I expect the pace of innovation to only accelerate in the years ahead.”

Plus, industry analysts project that adopting generative AI in payments could deliver $200-$340 billion in annual value for financial institutions.

A recent survey found that 85% of banking IT executives already have a clear strategy for incorporating AI into new product development. These data points underscore the significant commercial opportunity of generative AI for payment providers who can effectively harness this emerging technology.

How can the generative AI boom help revolutionize the future of business payments?

Let’s take a deeper look at an industry that’s ripe for innovation from the latest iteration of artificial intelligence:

1. Payment automation

Generative AI has the ability to view and interpret invoices in a way that can extract relevant payment information to mitigate the risk of payment delays or human error stemming from manual data entry.

In addition, machine learning algorithms can identify and correct errors in payment data, helping to ensure seamless and swift transactions across parties.

The ability of algorithms to actively automate the invoicing process can be a crucial efficiency tool for countless industries and international supply chains which could throw up challenges in interpreting invoices over language barriers.

Paymo has taken a major step in streamlining the payment process for its users with the launch of PM Payments. This integrated platform allows Paymo customers to get paid online directly from the invoices they send, with a single click of a “Pay Now” button. Clients can conveniently pay via credit card or ACH, and the payment is instantly reflected in the invoice, with the business owner notified.

Automated payments eliminate the need to wait for checks in the mail and empower clients to pay anytime, anywhere, using their preferred method. Through a native payment gateway implemented in the project management and invoicing software, the payment process is automated, and data entry errors are minimized. PM Payments is currently available to US customers with competitive, straightforward pricing based on card type.

2. Optimizing personalization

The advantage of generative AI is its ability to analyze and interpret masses of structured and unstructured data to leverage previously impossible solutions to provide for payment providers.

For instance, personalized payment experiences can involve using a customer’s payment history to suggest the most relevant methods for completing a transaction or providing status updates on recent purchases.

As digital transformation continues to improve the payments landscape, we’re seeing a more comprehensive range of options available to users, including peer-to-peer (P2P) payments, buy-now-pay-later (BNPL), biometric payments, cryptocurrency, central bank digital currencies (CBDCs), and a variety of open banking solutions.

Another kind of personalization concerns customer support. Payment processor Form3 has integrated generative AI chatbots to provide personalized customer support and guide users through complex transactions.

Offering personalized recommendations for completing transactions can help provide users and businesses with the most efficient and cost-effective solution for making payments.

3. Automating invoicing

Generative AI is also transforming payment invoicing for both businesses and their consumers. With the ability to intelligently extract details like invoice numbers and supplier names in just a few seconds, AI bots can leverage natural language processing and automatically create invoice layouts at high speed.

This reduces the chances of human error and ensures that the payment process between business and client is of the uppermost accuracy.

Most modern-day invoicing software allows businesses and consumers to complete transactions in one click.

While the action of invoicing itself is extremely quick, AI-powered invoicing software automatically collects data from each transaction for detailed reporting and export features that help you update your bookkeeping electronically. Here’s a detailed list of the best 20 invoicing software for your business.

Also, robust invoicing software like Paymo will generate invoices based on outstanding time entries, tasks, or expenses:

4. Next-generation fraud detection

Generative AI’s seamless ability to analyze big data and use it to make intelligent recommendations and automated decisions makes it an excellent option for combatting fraudulent activity within the payments industry.

With every card transaction generating dozens of data points, artificial intelligence can actively analyse the data against its machine learning algorithms to make accurate, real-time decisions to either approve, deny, or quarantine payments. By integrating tools for transaction monitoring, businesses can enhance their ability to detect anomalies and suspicious activity, allowing for more proactive fraud prevention.

As the age of open finance continues to grow, it’s difficult to anticipate the fraudulent activity that will take place in the future and its level of voracity. Fortunately, advanced generative AI fraud detection systems can actively monitor and assess prospective instances of suspicious activity to make autonomous judgments on whether criminal activity is taking place.

Several companies have already begun implementing generative AI in their payment operations. For example, Visa has leveraged generative AI models to enhance its fraud detection capabilities, enabling the system to rapidly analyze large volumes of transaction data and identify suspicious patterns in real time.

Visa launched in May 2024 Visa Account Attack Intelligence (VAAI) Score that identifies the likelihood of enumeration attacks in card-not-present transactions, which amount to $1.1 billion in fraud losses.

5. Perpetual compliance

Regulatory compliance is an important aspect of the payments industry, and firms must ensure that they’re fully on board with Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations to avoid costly difficulties later on.

Fortunately, machine learning and generative AI have helped to lead companies through complex regulatory structures in a way that can ensure that compliance is adhered to at all times, even as rules change and the regulatory climate becomes more stringent.

Through live monitoring of domestic and international regulatory changes while adhering to GDPR principles for customer data, generative AI and machine learning can automate the compliance process to ensure that businesses don’t have to continually spend resources on checking rule modifications on the fly.

Source: Unsplash

Challenges and limitations

While the potential of generative AI in payments is significant, there are concerns about data privacy, algorithmic bias, and the potential for misuse of synthetic content created by generative models, concerns that need to be carefully managed:

• Data privacy and security concerns

The use of generative AI in payments raises critical concerns about data privacy and security. Generative models are trained on vast datasets that may contain sensitive customer information, payment details, and other confidential data. Ensuring the proper management, protection, and consent around this data is paramount, as any breaches or misuse could lead to serious privacy violations, identity theft, and reputational damage for payment firms. Robust data governance frameworks and compliance with evolving regulations like GDPR will be essential.

• Algorithmic bias

Like other AI systems, generative AI models used in payments can potentially exhibit algorithmic biases based on the data they are trained on. This could lead to unfair or discriminatory outcomes in areas like credit decisions, fraud detection, and personalized recommendations. Payments companies must carefully audit their generative AI systems to identify and mitigate such biases, ensuring fair and equitable access to their services.

• Potential for misuse of synthetic content

The ability of generative AI to create highly realistic text, images, audio, and video raises concerns about the potential for bad actors to misuse this technology. Synthetic content could be leveraged for fraud, phishing, identity theft, and other malicious activities undermining trust in digital payments. Robust authentication methods, content validation, and user education will be critical to combat these emerging threats.

• Regulatory compliance challenges

As the use of generative AI in payments expands, firms must ensure their systems comply with evolving regulatory frameworks around the responsible development and deployment of these technologies. This includes adhering to guidelines around transparency, explainability, and human oversight of AI-powered decision-making. Navigating this complex and shifting regulatory landscape will be a key hurdle for payments providers.

Payments firms will also need to ensure their generative AI systems comply with evolving regulatory frameworks around the use of AI technologies. Overcoming these hurdles will be crucial as the industry adopts these transformative capabilities.

Driving a sustainable future

Generative AI is actively shaping the future of the payments landscape. Its utility will transform how customers pay for goods and services and can revolutionize how customers and enterprises manage transactions.

Eventually, the age of GenAI will fundamentally provide innovation for businesses and help secure payments with unprecedented efficiency.

For brands and payment providers alike, embracing the innovations offered by generative AI will form a major stepping stone towards digital transformation for transactions. This, in turn, ensures efficiency and safety as the possibilities throughout open finance grow.