AI in Digital Payments

The future of commerce is being shaped by Artificial Intelligence, which is no longer just an emerging technology but a key tool for business optimization and growth. In the dynamic world of payments, AI is redefining how transactions are managed, fraud is combated, and lost revenue is recovered. This shift not only impacts operational efficiency but also offers a crucial competitive advantage.

AI analyzes hundreds of variables in real time to make smarter decisions at every stage of the payment lifecycle, from checkout to dispute management. This enables businesses to face growing challenges such as the pressure for profitable growth, constantly changing customer expectations, and rising transactional costs.

The New Paradigm of Transactions

The pressure for profitability and the rise of fraud threats have made AI an indispensable tool for the payments sector. A recent study, based on a Stripe survey of more than 2,000 global business leaders, revealed that 43% already use AI solutions in their payments, and another 32% plan to do so in the next two years. The main application of AI in this field is fraud detection, used by 47% of the surveyed companies.

This growth in adoption isn't just due to cost reduction, but to the expectation that AI will generate a strategic advantage for the business. For example, 78% of respondents believe AI will create more personalized customer experiences, while 76% are confident it will significantly increase profitability and reduce fraud.

This paradigm shift also brings new challenges. Traditional payment systems, designed for human interactions, must now adapt to AI agents that will act on behalf of companies and customers to make purchases and manage services. This future of "agent-based commerce" requires rethinking payment infrastructure and fraud prevention systems to distinguish between legitimate AI activity and automated attacks.

Profitability on the Horizon

The strategic application of AI in payments can generate a considerable financial impact. For example, checkout optimization, which personalizes the payment experience, can lead to an average 12% increase in revenue and a 7.4% increase in conversion rates by dynamically displaying relevant payment methods.

Furthermore, using AI to prevent and manage fraud has proven to be highly effective. By applying security measures selectively, businesses can reduce fraud by up to 32% on average without negatively affecting conversion. AI-based fraud prevention technology can block card testing attacks, which have decreased by 80% in the last two years on one of the largest payment networks.

Finally, the recovery of legitimate revenue is another area of great impact. It's estimated that incorrectly declined transactions will reach $265 billion by 2027. With AI, companies can increase authorization rates by an average of 2.2% and recover up to 57% of failed recurring payments, minimizing customer churn.

Roadmap for Growth

To capitalize on the opportunities presented by AI in payments, companies should implement a multifaceted approach that spans several operational areas.

• Personalize the checkout: Analyze customer, device, and location data to show the most relevant payment methods and improve conversion. Displaying even a single irrelevant payment method can reduce conversion rates by up to 15%.

• Design for AI agents: Prepare payment infrastructure to be machine-readable, allowing AI agents to make secure purchases and automate financial tasks.

• Maximize authorizations: Use AI to identify legitimate transactions that might be declined and apply specific strategies for their approval, such as retrying payments at the optimal time.

• Prevent cart abandonment: Simplify authentication processes for low-risk customers, balancing security and user experience.

• Proactively manage disputes: Implement AI solutions that identify high-risk transactions and suggest proactive refunds before customers initiate a chargeback.

• Automate recovery: Use AI to automatically gather and present the necessary evidence to dispute chargebacks, saving operational time and recovering more revenue.

• Reduce fraud costs: Implement an AI-based fraud detection system that learns and adapts to new threats, such as card testing attacks, without affecting legitimate transactions.

• Optimize performance: Use AI-based alerts that detect anomalies in authorization rates with more than 90% accuracy, allowing for quick action before issues impact revenue.