The shift towards human+AI collaboration in debt collections and customer retention

The way organisations approach debt collections and customer retention is undergoing a fundamental transformation. What was once a rigid, script-driven process handled largely through call centres is now giving way to more nuanced, technology-enabled interactions. Customers, even in sensitive financial situations, increasingly expect speed, empathy, and personalised engagement — a reality that traditional models struggle to deliver.

Adding to this shift are regulatory and compliance pressures. One-size-fits-all collection strategies are becoming less effective and, in some cases, risk running afoul of evolving frameworks that demand fairness, transparency, and customer-first communication. Against this backdrop, the industry is beginning to recognise the power of Human+AI collaboration.

Why Human+AI Collaboration Works

For context, research finds that 71% of consumers expect personalized interactions and 76% feel frustrated when they’re absent; companies that execute personalization well typically see a 5–15% revenue lift.      
Neither humans nor machines, on their own, can address the complexities of modern collections. Automated tools are great at speed and consistency, but they often miss the human touch — the pauses, tone shifts, and emotional cues that shape genuine conversations. People, on the other hand, bring empathy and judgement, though they can quickly get overwhelmed when the workload is high.

The real breakthrough comes when the two work together. Routine, data-heavy work is where technology proves its worth. By taking on those tasks, it frees people to focus on the conversations that truly matter — the ones that demand empathy, careful listening, and negotiation. This isn’t about replacing human involvement; it’s about creating the right balance, where technology does the groundwork and people bring the depth of judgement and understanding that only they can offer.
In practice, large-scale field evidence shows complementarity: in a study of 5,179 customer‑support agents, gen‑AI assistance increased issues resolved per hour by ~14% on average (and by 34% for novices).

AI Voice Assistants in Action

A clear example of this collaboration is the rise of AI-powered voice assistants. Far beyond basic chatbots, these tools can now engage in natural, conversational dialogues that remain compliant and respectful. They work round the clock, take on high-volume outreach, and ease the workload on call centre teams.

Adoption and ROI are accelerating: venture funding into AI voice agents grew from about $315 million (2022) to $2.1 billion (2024), and analysts expect ~75% of new contact centers to incorporate generative AI by 2028; studies also estimate chatbot‑driven service savings of $7.3 billion in banking by 2023 and over $8 billion per year across sectors. 

Crucially, they don’t work in silos. These tools are able to sense when a customer is uncertain, frustrated, or simply needs more attention, and at that point they can shift the conversation to a human agent. This smooth transition makes sure customers get the right support at the right time, without the impersonal experience of being trapped in a fully automated process.

Personalisation as the Key to Retention

Debt collection is no longer just about recovering dues; it is also about preserving customer relationships. AI systems can analyse payment histories, behavioural patterns, and sentiment signals to recommend personalised repayment plans or engagement strategies.
Personalization has shown tangible impact: typical revenue lift of 10–15%, with most customers expecting it; even small retention gains compound—e.g., a 5% increase in customer retention can raise profits by 25–95%. 
When a customer hesitates, expresses frustration, or requires a tailored arrangement, human agents can step in to provide empathy and flexibility. When technology and human insight work together, the outcome goes beyond faster repayments. Customers are more likely to feel understood and supported, which in turn builds loyalty and strengthens long-term relationships. What could have been a difficult or negative encounter becomes an opportunity to earn trust.

Keeping Compliance and Ethics at the Core

In financial services, compliance and ethics cannot be treated as an afterthought. Technology can speed up the process, but it cannot be left unchecked. Human judgement is still needed to make sure communication follows the law, stays respectful, and feels transparent. Customers also deserve honesty — they should be told when they’re interacting with an AI system. Above all, the tone must protect dignity and fairness.
In addition to disclosure and fairness requirements in lenders’ Fair Practices Codes, supervisory guidance in India (RBI) and the U.S. (CFPB) codify respectful communication norms such as restricted call times and frequency presumptions. 

Measuring Success

The results of Human+AI collaboration show up in two places. On the collections side, one can see faster repayments, shorter cycles, and leaner costs. On the retention side, the signs are different — fewer customers leaving, stronger repeat relationships, and more positive feedback.

These measures highlight not just stronger financial results, but also a better customer experience — an area that is fast becoming a decisive factor in competitive advantage.

Looking Forward

The next chapter in this journey will move from reactive to predictive. As AI systems grow more capable of recognising risk signals early, organisations will be able to intervene before defaults occur, taking a more proactive approach to customer retention.

In this future, Human+AI collaboration won’t simply mean doing things faster. It will mean doing them smarter — anticipating needs, responding with empathy, and reshaping collections into a process that protects relationships as much as it recovers dues.
 

Maaz Ansari

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Maaz Ansari is Co-Founder, Oriserve, an enterprise-grade AI solutions company