At its annual Visa Payments Forum in San Francisco, Visa introduced several new native payment technologies. These tools are meant to customize the user card experience while adding more convenience, payment options, and security. Listed below are five new card technologies announced by Visa.

• Visa Flexible Credential allows consumers to switch between accounts and payment methods. Consumers can choose debit, credit, “pay-in-four” with Buy Now Pay Later, or use rewards points. The product is available in Asia and will be launched in the US through Affirm.
• Tap to Everything — Visa is expanding the various ways consumers can tap to pay. These new methods include:
  • Tap to Pay: Any device can now be a POS device
  • Tap to Confirm: Easily authenticates identity when shopping online
  • Tap to Add Card: Enhances security when adding a card into a wallet or app
  • Tap to P2P (person-to-person): Allows money to be sent between family and friends
• Visa Payment Passkey Service — Built on the latest Fast Identity Online (FIDO) standards and uses biometrics to identify someone online. It replaces passwords while keeping online transactions secure.
• Pay by Bank — Focused on enhancing the account-to-account (A2A) payments experience. Consumers can transfer funds from one account to another, apply for a loan, or use a credit card for payments. The service is currently available across Europe. Visa does have plans to bring it to the U.S.
• Visa Protect for A2A Payments — Applies AI to Real-Time Payments (RTP) networks in an effort to reduce fraud uses real-time AI fraud detection.

Visa’s AI also plays a larger role in providing tokens between banks, merchants, and cardholders. Instead of handing over a lot of their data to merchants in an unstructured fashion, tokens allow consumers to provide specific information securely to merchants. Through this permission-based sharing, Visa builds a picture of the consumer that includes where they shop, their interests, and more. 

The merchant can then feed this information into their LLM model, creating a relevant consumer profile. The merchant can then present context-aware recommendations to the consumer.