The Revenue Impact of Generative AI in Payments and Banking

The payments landscape has always been a critical area for merchants looking to drive revenue growth and expand into new markets. Historically, payment systems were functional but lacked the agility and customization required to meet diverse customer needs. For merchants, this often meant leaving potential revenue untapped due to friction in the payment process—be it slow transaction times, limited payment options, or lack of personalization.

However, with the introduction of generative AI, businesses have found new ways to make payment experiences simpler, more efficient, and highly tailored to individual customer preferences. This transformation isn’t just about convenience; it’s about creating an ecosystem where every transaction strengthens customer loyalty, enhances satisfaction, and drives revenue growth.

Simplifying Payments to Unlock Revenue Potential

Take the example of a small merchant expanding into international markets. Traditionally, this would involve integrating cumbersome systems to handle multi-currency payments, complying with local regulations, and offering region-specific payment options. Each of these requirements adds layers of complexity, often slowing down the expansion process.

With generative AI, this scenario changes dramatically. AI-powered systems analyze customer preferences in different regions, identifying which payment methods—such as digital wallets, Buy Now Pay Later (BNPL) options, or instant transfers—are most popular. By proactively tailoring the payment experience to these insights, merchants can eliminate barriers to transaction completion.

For instance, imagine a merchant in Asia entering the European market. Generative AI can predict which local payment methods customers prefer and automate the integration of these options into the merchant’s platform. The result? Faster adoption by local customers, increased transaction volumes, and additional revenue streams that might have been inaccessible with a generic payment setup.

This streamlined payment process not only reduces friction but also fosters customer loyalty. When consumers find it easy to make payments in the way they prefer, they are far more likely to return for repeat purchases. This loyalty translates into increased lifetime value for each customer and a stronger foundation for the merchant to expand further.

Customer Loyalty as a Revenue Driver

Customer loyalty has always been the cornerstone of sustainable business growth. But earning loyalty in today’s competitive market is no easy task. Customers expect fast, secure, and personalized experiences at every touchpoint, and payment systems are no exception.

Generative AI enables merchants to meet these expectations by offering payment experiences that are not only quick and safe but also tailored to individual preferences. For example, AI can track a customer’s preferred payment method—say, a particular digital wallet—and prioritize displaying that option during checkout. This level of personalization makes the payment process feel effortless, reinforcing the customer’s trust in the merchant.

Moreover, generative AI can identify patterns in customer behavior to proactively address potential pain points. Suppose a recurring customer’s transaction is declined due to insufficient funds. Generative AI could immediately recommend alternative payment options, such as splitting the payment across multiple methods or offering a short-term credit line. These small but impactful interventions can turn a potentially negative experience into a positive one, further strengthening loyalty.

For merchants, the financial impact of this loyalty is significant. Loyal customers not only make repeat purchases but are also more likely to recommend the merchant to others. The revenue generated from these repeat and referral customers often far outweighs the cost of acquiring new ones.

Generative AI in Banking: Transforming Efficiency and Decision-Making

The payments sector is not the only beneficiary of generative AI. Banks are also leveraging this technology to revolutionize their core operations, from data management to product development and decision-making. Companies like Temenos and Quantexa are at the forefront of this transformation.

Temenos: Responsible Generative AI for Core Banking

Temenos recently launched its first responsible generative AI solutions as part of its Gen AI-infused banking platform. The goal? To help banks transform how they interact with their data, ultimately improving efficiency, operations, and product management.

For example, a bank using Temenos’ generative AI might analyze customer transaction data to identify opportunities for cross-selling financial products. Suppose a customer consistently pays off their credit card balance in full each month while also saving a significant portion of their income. The AI could recommend a high-yield savings account or a low-risk investment product tailored to the customer’s profile.

This level of data-driven personalization not only enhances the customer’s financial journey but also drives revenue for the bank by increasing product adoption rates. Additionally, automating these insights reduces the workload for human teams, allowing them to focus on high-value activities like relationship management and strategic planning.

Quantexa: Augmenting Decision-Making with Gen AI

Quantexa has introduced its generative AI suite, Q Assist, which is already being used by major financial institutions like HSBC and BNY Mellon. Q Assist is designed to augment decision-making across front-line workers and information teams.

Consider a scenario where a compliance officer at a bank is reviewing a flagged transaction for potential fraud. Traditionally, this process might involve manually cross-referencing the transaction with historical data and third-party sources—a time-consuming and error-prone task.

With Q Assist, generative AI automates much of this work. It can analyze the transaction in the context of the customer’s historical behavior, compare it to industry benchmarks, and provide a summary of findings to the compliance officer. This not only speeds up the investigation but also ensures a higher level of accuracy.

The implications for the bank are profound. Faster decision-making means fewer delays in transaction approvals, which improves customer satisfaction. At the same time, the automation of routine tasks allows compliance teams to focus on complex cases, increasing overall efficiency.

The Combined Impact of Generative AI on Financial Services

When applied strategically, generative AI creates a ripple effect across the financial ecosystem. Merchants benefit from increased revenues and customer loyalty by offering frictionless, personalized payment experiences. Banks gain efficiency and revenue growth by using AI to optimize operations, improve product offerings, and make data-driven decisions.

By simplifying payment systems, fostering customer trust, and enabling smarter decision-making, generative AI ensures that financial institutions and merchants alike can navigate the complexities of today’s markets while positioning themselves for future growth. Explore how Gen AI is impacting financial services.

The introduction of solutions like Temenos’ responsible generative AI platform and Quantexa’s Q Assist suite exemplifies how this technology is already reshaping the industry. As adoption continues to grow, the financial services sector will increasingly rely on generative AI to drive innovation, efficiency, and long-term success.

The Revenue Impact of Generative AI in Payments and Banking

The Revenue Impact of Generative AI in Payments and Banking

Simplifying Payments to Unlock Revenue Potential

Customer Loyalty as a Revenue Driver

Generative AI in Banking: Transforming Efficiency and Decision-Making

Temenos: Responsible Generative AI for Core Banking

Quantexa: Augmenting Decision-Making with Gen AI

The Combined Impact of Generative AI on Financial Services

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