Collections teams at banks and NBFCs push thousands of overdue accounts through calls, WhatsApp, and email every day, and most of that work still happens manually. A collector working a call list can't personalize outreach at scale, and templated messages can't tell a forgetful borrower apart from one who's stopped responding. So what does AI collections automation for NBFC and banking teams actually change about that math?

The core shift is moving from rule-based tools to Agentic Automation. Fixed triggers like "day five, send an SMS" can't adapt mid-conversation. Agentic Workflows read what a borrower says or types and decide the next action from there. But what happens when that borrower asks a question no script anticipated, or replies on a channel nobody planned for?

This eBook explores where Workflow Agents actually fit inside the collections process, from early-stage reminders through payment negotiation and dispute handling. Retail banks, NBFCs, microfinance institutions, and digital lenders are all applying AI agent collections and automation banking use cases differently. Which of these is closest to how your own loan book operates, and where would the gaps show up first?

There's also a build sequence for teams rolling this out, along with the mistakes that surface most often once a workflow goes live. Some of these are more fixable than others; which ones would cost you the most to hit mid-rollout?

Finally, what does ‘working’ even look like once one of these is live? Which numbers actually move, and which ones just look good on a dashboard?

Download the eBook for the full breakdown, with the frameworks, deployment checklist, and lender examples behind it.