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Yes Bank and Open Financial launch AI platform to predict EMI payment failures

Yes Bank and Open Financial Technologies have launched a new AI-powered platform designed to predict failed EMI payments before they occur.

Yes Bank and Open Financial Technologies have launched a new AI-powered platform designed to predict failed EMI payments before they occur. The platform enables customers to proactively shift their payment date, account, or method through authorised interventions, aiming to reduce defaults and improve collections efficiency, according to bfsi.economictimes.indiatimes.com.

The platform uses advanced machine learning algorithms to analyse payment patterns and identify customers at risk of missing EMI payments. By predicting payment failures in advance, the system allows banks to engage with customers early and offer flexible options to avoid defaults. Yes Bank and Open Financial Technologies collaborated to develop this solution, which integrates seamlessly with existing banking infrastructure, the report said.

This development reflects a growing trend in the Indian banking sector to leverage AI for credit risk management and collections. Similar AI applications are gaining traction as banks seek to optimise recovery processes and enhance customer experience. The platform joins other AI initiatives in financial services, such as PhonePe’s AI strategy to serve a billion Indians, highlighting the sector’s increasing adoption of artificial intelligence technologies, as noted by economictimes.indiatimes.com.

Yes Bank and Open Financial Technologies officially launched the platform this month, with plans to expand its deployment across multiple loan portfolios. The initiative represents a concrete step toward reducing non-performing assets by using predictive analytics, a key priority for Indian banks in 2026, according to bfsi.economictimes.indiatimes.com.

Editorial standards. Reported and edited at Startupniti's news desk from the sources listed in the right rail. Every fact traces to a citation. If something looks wrong, write to corrections.
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