Cashfree Payments, a fintech company, is introducing artificial intelligence (AI) agents to merchants for the automation of payment processes. This arises as these companies increasingly adopt agentic use-cases in India to create revenue sources beyond payment processing.

Merchants can utilize the AI agent named Relay for various purposes, including retrying unsuccessful payments, checking in on abandoned carts, verifying cash-on-delivery orders prior to shipment, handling failed subscriptions, and managing disputes, among other tasks.

The company aims to achieve ₹20,000 crore in lost gross merchandise value (GMV) by employing agents capable of encouraging customers who may abandon their transactions. This can be achieved by starting a voice or text-based conversation, or transforming them by providing discounts.

"Currently, businesses employ a growth team that contacts customers to find out why they left items in their cart or if they encountered problems during checkout. These groups might offer a discount to a customer. "An AI agent would now drive these functions," stated Mayank Juneja, director of engineering at Cashfree Payments.

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A small to medium-sized business (SMB) might invest approximately 60 hours weekly on payment-related operations. Cashfree asserts that it can reduce this duration to 45 minutes with its representative.

The agent operates on the infrastructure of the Bengaluru-based firm. "External AI providers do not receive merchant transaction data," it stated.

Aside from e-commerce, Juneja mentioned that the agent could also be utilized for scenarios like loan recovery.

This may involve reaching out to customers via phone, reviewing e-payment agreements, and deciding the optimal moment to reconnect with a customer.

The introduction of the agentic service creates a new source of income for fintechs such as Cashfree, which function on slim payment processing margins in the competitive payments sector.

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Cashfree mentioned that although the service is free initially, it intends to implement a performance-based pricing model later on.

Cofounder Reeju Datta mentioned that factors like the count of e-commerce carts converted through the agent and successfully resolved disputes would act as pricing metrics as adoption increases.

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This month, the fintech company Razorpay launched an AI model named Vulcan, trained on four billion transactions, to enhance payment success rates and identify fraud. It asserts that it has learned from 3 trillion data points, enabling the model to comprehend almost 3,000 signals from every transaction.