Fintech firm Cashfree Payments is rolling out artificial intelligence (AI) agents to merchants to automate payment operations, as reported by Business Standard. The AI agent, called Relay, can be deployed by merchants for use cases such as retrying failed payments, following up on abandoned carts, confirming cash-on-delivery orders before dispatch, managing failed subscriptions and filing disputes. According to Mayank Juneja, director of engineering at Cashfree Payments, the company is targeting ₹20,000 crore in lost gross merchandise value (GMV) through agents that can nudge customers who are likely to abandon a transaction by initiating voice- or text-based interaction, or convert them by offering discounts.
A small and medium business (SMB) could spend around 60 hours a week on operations related to payments, as reported by Business Standard. Cashfree claims to cut this time to 45 minutes with its agent. The agent runs on the Bengaluru-based company's infrastructure, with merchant transaction data not sent to external AI providers, according to the company's statement. Beyond e-commerce, Juneja indicated the agent could also be deployed for loan recovery use cases, including following up with customers over calls, examining e-payment mandates, and determining the right time to contact a customer again.
The launch of the agentic service opens up a new revenue line for fintechs like Cashfree that operate on thin payment-processing margins in the competitive payments industry, according to Business Standard. Cashfree said while the service is free at launch, it plans to introduce outcome-based pricing in the future. Co-founder Reeju Datta explained that outcome-based pricing would mean that metrics such as the number of e-commerce carts converted using the agent and disputes successfully resolved would serve as pricing parameters as adoption grows.
This development follows Razorpay's recent launch of AI model Vulcan, which was trained across four billion transactions to improve payment success rates and detect fraud, as reported by Business Standard. Razorpay claims to have been trained across 3 trillion data points, with the model able to understand nearly 3,000 signals from each transaction. What differentiates this model is that instead of specialized models each for routing, risk, fraud and checkout, a single model understands all data points at one point.
