Poonawalla Fincorp Limited has announced the implementation of advanced AIpowered debt management platform to transform its debt management processes, redefining the collections journey in the lending sector. This aims to enhance efficiency across processes, strategic designs, and governance framework.
Central to this transformation is an advanced engine that autonomously analyzes data from customer interactions, including digital communications, tele-calling, and field operations.
It offers a multi-layered, multi-channel intervention mechanism that enhances efficiency, reducing 4-5 days of manual effort typically needed for managing collection communications. The platform will enable PFL to leverage 100 plus micro-strategies that are aligned with customer profiles, preferred communication channels, and optimal engagement timings.
Implementation of a human less, automated channel allocation process has reduced the time from 3-4 days to under 3 hours, enabling faster customer engagement post-delinquency, across tele-calling and field channels.
Mr. Arvind Kapil, Managing Director & CEO of Poonawalla Fincorp, said, “Our adoption of AI in debt management is not just about automation—it’s about smarter, data-driven decisions that improve outcomes. By combining predictive insights with governance controls, we are redefining collection strategies to be more effective, adaptive, and responsive to customer engagement."
Usage of the platform is augmented with predictive models driven by AI and machine learning, empowering the team with smarter decision-making capabilities. It delivers 2-3X sharper risk assessment compared to the traditional models.
The company is also using GenAI-enabled automated call audit mechanism to monitor collection agents’ interactions, ensuring compliance with governance standards and enhancing accountability. This integration into the collection technology stack reflects PFL’s commitment to robust governance standards.
Over the last six months, the synchronization of technology with collection goals has supported PFL in improving efficiency.
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