A few years ago, the word “collections” would make most borrowers cringe and most lenders sigh. It evoked images of endless calls, tense conversations, and a process that felt more punitive than productive. But over the past two years, India’s debt recovery landscape has quietly undergone a transformation — one powered not by aggression, but by empathy and artificial intelligence.
We’ve seen this shift play out in real time in the Indian debt collections space. The data tells a clear story: when empathy is built into the system — when communication is contextual, respectful, and timely — repayment rates go up, default rates go down, and trust between lenders and borrowers actually strengthens.
Let’s unpack how this new model works and why “AI with empathy” may be the most important change agent in India’s debt recovery ecosystem.
From Chasing to Conversing: A Paradigm Shift
Traditionally, collections were about contact and compliance. The focus was on getting borrowers to pay — often through persistence and pressure. But that approach no longer works in a world where most lending is digital, borrowers are diverse (especially the Indian demographic), and reputation risk can ripple fast across social media — stories about debt collectors harassing borrowers into taking their lives are not uncommon.
Today, the best recovery outcomes come from conversations that understand the borrower. A borrower who has just switched jobs or faced a health setback doesn’t need ten automated reminders — they need flexibility and acknowledgement. Similarly, a borrower who simply forgot a due date may just need a polite nudge.
The key difference is context — and that’s where AI has been transformative.
AI That Listens, Learns, And Personalises
It is important to build models that analyse thousands of borrower interactions to detect intent, tone, and behavioural patterns. Instead of treating every overdue account as a “default risk”, systems need to categorise borrowers based on their likelihood and capacity to repay — empathetically.
By embedding AI, conversational chatbots are trained not only to send reminders but also to recognise sentiment and respond appropriately. A message to a first-time late payer sounds different from one sent to a chronic defaulter. The tone, timing, and even language choice adapt dynamically.
This personalisation has a measurable impact. Across more than a million borrower interactions we analysed, AI-personalised outreach improved response rates by 5X on a daily basis, and resolution time dropped by nearly 40–50%, depending upon the use cases across delinquency stages.
Empathy isn’t softness — it’s strategy. And the data proves it works.
India’s New Borrower
The Indian lending ecosystem has evolved dramatically. Today, more than 500 million credit-active individuals and MSMEs are part of formal credit channels. With BNPL, microloans, and fintech-led credit surging, the borrower base is more diverse than ever.
That also means reasons for delinquency are more nuanced. A missed EMI could result from anything — salary delays, a tech glitch, or even simple forgetfulness. A one-size-fits-all approach is not just ineffective; it’s counterproductive.
AI helps decode this complexity at scale. By mapping repayment patterns, engagement rates, and financial behaviour, systems can predict why someone might default — often before they do. This enables early interventions that are empathetic yet effective.
For instance, one of our partner NBFCs found that borrowers who received early, friendly nudges based on predictive risk signals were more likely to give a definite PTP (Promise to Pay) and adhere than those reached through standard recovery workflows.
The Rise of Responsible Recovery
The Digital Personal Data Protection (DPDP) Act and the RBI’s new Fair Practices Code have accelerated a broader shift towards responsible recovery. Collections today are as much about compliance and borrower dignity as they are about efficiency.
This is where technology’s role becomes critical — not as a replacement for humans, but as an enabler of better human judgement and decision-making. AI helps recovery teams stay compliant, eliminate bias, and ensure every borrower interaction is traceable, auditable, and respectful.
In our experience, empathy scales best when it’s systematised. It’s not just about training a few agents to “be nice” — it’s about embedding borrower-first design in every process, message, and model.
Embedding Empathy into Debt Collection With AI
We’re entering a world where recovery is increasingly proactive and preventive. Imagine a system that reminds you of your due date when your salary credit hits your account — not after you’ve missed a payment. Or an AI agent that negotiates repayment plans to fit your cash flow without ever involving a call-centre representative.
This is not science fiction; it’s happening right now. Collections are no longer a back-office function — they’re a strategic touchpoint in the borrower lifecycle. When done right, they not only improve portfolio health but also enhance customer lifetime value.
At our company, we believe the future of debt recovery in India lies in predictive empathy — the ability to sense distress early, communicate intelligently, and solve collaboratively. AI gives us the tools; empathy gives us the direction.
A Human Problem, Solved Humanely — With AI
Let’s face it — debt is an emotional subject. Behind every missed payment is a story, and behind every recovery is a relationship. The best collections systems don’t just automate communication; they restore trust.
Empathy and AI might sound like strange bedfellows, but in the context of India’s financial ecosystem, they’re the perfect pair. By combining data intelligence with human understanding, we’re not just reducing defaults — we’re redefining what financial responsibility feels like.
Debt recovery no longer needs to be a dreaded experience. Done right, it can be a moment of partnership — one where both lender and borrower emerge stronger. And that, perhaps, is the most human outcome technology could deliver.
(Ananth Shroff, Founder & CEO, DPDzero.)
Views are personal, and do not represent the stance of this publication.
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