PayU is strengthening its focus on integrating Generative AI (GenAI) to revolutionize customer interactions, merchant support, and employee productivity in 2025. With India poised for a GenAI-driven digital transformation that could add up to $1.5 trillion to the national GDP by 2030, PayU is committed to leveraging AI responsibly. The company prioritizes regulatory compliance and security while enhancing customer experience through AI-powered innovations.
Key GenAI Initiatives at PayU
- Faster Merchant Onboarding:
PayU is using GenAI to optimize its merchant onboarding process by identifying discrepancies in submitted data and analyzing online footprints. These AI-driven insights, combined with risk monitoring, have led to an 80% reduction in fraud and chargeback losses. Additionally, PayU now onboards top-tier merchants within 2-3 days. - AI-Driven Support Automation:
GenAI models assist in classifying email tickets, extracting crucial information, and providing structured responses, enabling PayU to instantly resolve 30-40% of merchant queries. - Streamlined Ticket Management:
To improve efficiency, PayU employs GenAI to filter out spam and duplicate support tickets, saving customer care teams up to 7% of their time. The company aims to automate 60-70% of support responses, ensuring faster and more effective query resolution. - Enhancing Workforce Productivity with AI:
PayU is equipping its employees with advanced GenAI tools to drive efficiency and innovation. The company has introduced Toqan, an internal AI platform developed in collaboration with Prosus, which automates repetitive tasks and enhances decision-making. Employees in PayU’s credit division now have secure access to top AI models from OpenAI, Meta, and Anthropic within a robust compliance framework. Additionally, PayU Finance employees can query backend databases without prior SQL knowledge, streamlining internal processes.
Future AI Expansion and Commitment to Compliance
As a regulated entity, we take pride in seamlessly implementing GenAI-driven initiatives while ensuring full compliance with regulatory standards,” said Koushik Kadidal, Chief Data Officer & Head of Insights Business at PayU. “Looking ahead, we aim to reduce manual workloads for developers by 20-30% through LLMs, targeting 65% accuracy and cutting Level 1 code review time in half. Additionally, our goal is to automate 60-70% of support responses to enhance efficiency. We remain committed to the responsible deployment of GenAI, keeping compliance at the core of our operations across all PayU businesses.
