How AI is powering smarter collections and renewals

A quiet crisis is unfolding within India’s financial services ecosystem. It is not visible in quarterly NPA disclosures, lapse ratios, or portfolio ageing reports. It sits beneath the dashboards, in the human cost embedded within how collections and renewals are still executed today. For decades, the sector has relied on a friction-first operating philosophy. If a customer misses a payment, the response is repetition: more calls, greater frequency, escalating pressure. The system is designed around persistence, not sustainability.

Every morning, contact centres across Noida, Bengaluru, Hyderabad, and Chennai come online. Early in the day, agents begin with energy and intent. By mid-afternoon, many have absorbed hours of verbal hostility, raised voices, and emotional distress from financially strained customers. By the end of a 100-call shift, cognitive fatigue is no longer an exception; it is the norm. India’s own labour and industry studies estimate that frontline BFSI contact roles experience 30-45% annual attrition, among the highest in the formal services economy. The reasons are consistent: emotional exhaustion, compliance pressure, and the psychological toll of adversarial conversations.

Expecting consistently high promise-to-pay (PTP) outcomes or perfect regulatory adherence from individuals operating under these conditions is unrealistic, and increasingly untenable. 

From operational choice to systemic necessity

Artificial intelligence is no longer a discretionary efficiency layer for BFSI. In the Indian regulatory context of 2026, it is fast becoming an operational and ethical necessity. Under the post-2025 regulatory environment, including enhanced personal accountability standards introduced across insurance and lending, the distinction between “in-house” and “outsourced” conduct has effectively collapsed. Principal liability now rests squarely with the institution. A single non-compliant interaction can trigger regulatory scrutiny, penalties, and reputational damage that far outweigh the cost of prevention. 

Fatigue is the hidden compliance risk

Human behaviour degrades under sustained stress. Tone shifts. Patience shortens. Scripts are paraphrased. Guardrails are unintentionally crossed. Not from malice, but from exhaustion. AI systems do not experience cognitive depletion. A voice interaction delivered at 9:30 AM is identical in composure, language discipline, and courtesy to one delivered at the 1,000,000th attempt. There is no escalation through frustration, no emotional provocation, no deviation under pressure. This consistency is not just operationally efficient, it is structurally compliant. 

Compliance by design, not audit after damage

Traditional compliance models in India remain largely reactive. Calls are recorded, sampled, and reviewed after the interaction has already occurred. By the time a deviation is identified, the customer experience and the brand exposure is irreversible. AI enables a fundamentally different architecture: compliance embedded at the point of interaction. Modern systems operate within pre-defined linguistic, ethical, and regulatory boundaries. They cannot issue prohibited language, imply coercion, or misrepresent terms not because they are “trained better,” but because such actions are structurally impossible. For human agents, this shifts compliance from a burden to a support system. Instead of memorising frequently updated RBI, IRDAI, or internal policy circulars, agents are augmented by systems that enforce correctness in real time. The result is lower error rates, reduced anxiety, and materially lower regulatory exposure. 

Empathy, delivered reliably and at scale

The assumption that empathy is exclusively human does not hold under fatigue. Most payment lapses in India are not wilful defaults. Public credit data consistently shows that short-term liquidity disruptions, missed reminders, or temporary income volatility account for a large share of delinquencies under 60 days.

When an interaction begins in a familiar dialect, Marathi, Tamil, Telugu, or Hinglish and maintains a neutral, non-threatening tone, the psychological resistance drops. The conversation becomes informational rather than confrontational.

This has measurable outcomes. Industry-wide operational studies in India show that early-stage, non-adversarial outreach significantly improves PTP conversion and reduces roll-forward delinquency. Institutions implementing automated, vernacular-first outreach models report 20–30% efficiency improvements in early collections, alongside near-elimination of language-related compliance breaches. More importantly, it reframes the interaction. The call is no longer a demand. It becomes a financial check-in. That distinction matters for lifetime value. 

Renewals: Moving beyond digital fatigue

Collections are only one side of the problem. Renewals, particularly in insurance, suffer from a parallel failure mode. The dominant strategy remains volume-based reminders: repetitive SMS alerts, generic IVR calls, and escalating nudges that customers increasingly ignore or actively block. In an era of rich behavioural data, this is not persistence, it is imprecision.

Predictive retention changes the operating logic. Instead of reacting to lapses, AI models identify early indicators: declining engagement, altered payment behaviour, or life-stage transitions. Outreach happens earlier, with context.

The tone shifts accordingly. Not “your premium is due,” but “we noticed a change, would a different payment structure help you stay covered?”This reframing has a direct commercial impact. Persistency improves, customer hostility drops, and renewals move from transactional pressure to relationship continuity. 

The economics of dignity

India’s contact-centre ecosystem pays a high hidden tax for human burnout. High churn inflates recruitment costs, erodes institutional knowledge, and degrades service quality. The human cost is equally significant. Automating the most repetitive, emotionally abrasive interactions does not eliminate human roles. It preserves them for where they add the most value. Complex cases, genuine hardship scenarios, and nuanced negotiations are better handled by rested, skilled professionals than by exhausted agents following scripts. Improving employee experience (EX) is not separate from customer experience (CX). In financial services, the two are structurally linked. 

A vernacular, voice-first future

India remains a voice-first economy. With 22 official languages and thousands of dialects, financial trust is built through familiarity, not formality. The next phase of BFSI technology will be defined less by novelty and more by latency, linguistic precision, and emotional neutrality. As voice systems approach real-time responsiveness and natural prosody, the distinction between human and machine becomes operationally irrelevant to the customer.

The objective is not to remove the human element from finance. It is to protect it. By delegating high-stress, high-volume interactions to systems designed for consistency and care, institutions can scale without sacrificing integrity. Debt recovery, renewals, and compliance do not have to be adversarial. They can be intelligent, contextual, and humane. That is not just better business. It is essential infrastructure for building a resilient, inclusive, five-trillion-dollar Indian economy. 

(The author is co-founder and CRO, Oriserve. Views are personal)