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AI Use Cases in the Payments Industry

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The payments industry has used AI for quite some time. Fraud scoring and analyzing individual payment spending patterns have been part of issuer risk analysis for decades. FICO has been using machine learning to create credit scores since the 1980s and is one of the most recognizable payments companies steeped in AI.

In several global regions, McDonald’s uses Mastercard’s Dynamic Yield solution to increase average order value through AI that optimizes personalized food recommendations in digital menus.

Visa has a network of services called VisaNet + AI, offering solutions such as the ability to closely mirror approval decisions made by issuers during outages.

While generative AI has been available for years and has been in use, it is not widely adopted within many payments companies, except in fraud management. AI is often not embraced at nearly the same level in other departments.

The next few years will likely involve a concerted effort by payments companies to develop strategies for implementing AI. Most have just started their journey. Overall, the payments industry is experimenting with two types of AI technologies; machine leaning and natural language processing.

TSG mainly expects future AI use in the payments space to be improvements in the ways AI is used in payments today, such as:

  • Improved fraud detection
  • Improved predictive analytics on consumer behavior
  • Improved customer engagement with generative AI for audience-specific communication

We are now at a point when gathering and storing vast amounts of transactional and behavioral information on individuals is commonplace. As society continues to digitize, more types of information will be harvested, such as data stored from smartphones and cameras. As more information is gathered, AI’s usefulness strengthens.

AI can streamline personal experiences and back-office processes. Below are a few examples.

Select Payments Company Applications


AI can assist sales staff by identifying patterns in lead activity and creating tailored sales content. 

Merchant & SaaS Platform Onboarding 

In cases where onboarding processes are long, AI can decrease onboarding and API integration friction by verifying data automatically and completing risk assessments, cutting down manual review time. 

Buy Now, Pay Later 

Some buy now, pay later companies use algorithms for quick credit checks instead of hard inquiries on credit reports. 

Attrition Prediction

Using patterns and attributes, payments companies could use AI to predict which merchants are likely to attrit.

Select Merchant Applications


AI will help detect fraud and improve geofence marketing as consumers enter proximity to physical store locations. 

Value Added Services 

AI can speed up ancillary merchant activities like generating menus or writing blog posts. Adding AI in other payment-adjacent tools can enhance loyalty. 

Conversational Commerce & Chatbots 

Retailers can leverage messaging apps and digital assistants to provide smoother checkout. For example, consumers can order items with voice commands. AI-powered chatbots can enhance customer service, automate processes, and expand retailers’ abilities to sell intelligently. The online checkout process and any service questions can be answered by bots with more and more precision as time goes on. 

B2B Invoicing 

AI can aid reconciliation by automatically matching incoming payments with outstanding invoices without requiring a person to review them manually. 

Next steps for your company

In summary, AI is revolutionizing digital payments by making them more efficient, secure, and personalized.

If you’d like to talk with our subject matter experts on how AI can be used in your payments company, reach out to schedule a quick introduction call