FrenzoCollect
15-12-25
India’s digital lending sector continued its explosive growth in 2025, while delinquency rose alongside. Digital NBFCs accounted for roughly 80 percent of new personal loan volume, about 3 crore loans in Q1 FY26, and carried an outstanding portfolio of approximately ₹1.2 lakh crore. Despite rapid expansion, stress levels were elevated. Fintech loan portfolios saw the 180 plus days past due bucket increase to about 8.6 percent by mid-2025 from 7.1 percent a year earlier. Microfinance institutions faced acute strain as microloan delinquencies surged, even while gross loan books contracted. Stressed retail loans doubled over FY20–25, making unsecured retail and SME lending the largest drivers of bad loans in India and pressuring lenders to adopt smarter recovery strategies.
Modern borrowers expect convenience and exhibit varied trust levels. UPI AutoPay adoption rose sharply, with mandates tripling from 58 million in January 2024 to 175 million in January 2025. More than half of recurring payments, including loan EMIs, now flow over UPI, indicating a marked preference for one-click mandates over manual debit. Encouraging borrowers to set up UPI mandates or auto-debit via BBPS or UPI can convert collections into near-passive deductions.
At the same time, outreach must be personalised. Data-driven lenders segment borrowers by channel and language, using past response patterns to contact each borrower on their preferred medium. In India’s multilingual market, vernacular disclosures and regional language communication materially improve engagement. Many borrowers, notably rural or first-time borrowers, distrust faceless automation. A compassionate human voice often overcomes the shame and fear associated with debt, while bots can feel impersonal. The leading approach in 2025 was a hybrid model. Automated outreach handled routine reminders, and human agents stepped in for complex negotiations and hardship cases.
Recovery platforms in 2025 were omnichannel and AI-powered. Messaging apps, and WhatsApp in particular, emerged as the most effective touchpoint. Messaging delivers read receipts, richer content, and higher engagement than SMS or calls, and it supports embedded payment links that let borrowers settle dues within the conversation. WhatsApp interactions commonly showed far higher open and click rates than SMS, and they delivered measurable uplifts in early collections.
Voice remained important for real-time negotiation, but human contact centres were costly and increasingly ineffective for cold outreach. AI voicebots filled the gap by making outbound calls in local languages, using natural language processing to detect sentiment, and auto-escalating to human agents when necessary. Predictive analytics also matured, with machine learning models combining bureau data, transaction history and UPI/payment signals to score payment intent in real time. Lenders used these scores to prioritise outreach to accounts where intervention would be most effective.
In practice, advanced systems ran workflows that escalated through channels automatically. A missed SMS reminder would be followed by a WhatsApp message, then an email, and eventually an automated call, all orchestrated by business rules. Self-service portals and one-tap pay links reduced friction. Conversational AI answered routine queries like statements and EMIs, while gamification and small incentives were sometimes used to nudge timely repayment. Overall, technology extended collections from a nine-to-five calling model to a 24x7 intelligent system.
Innovation in collections occurred within a stricter compliance framework. Recent RBI directives intensified requirements around transparency, disclosures and the flow of funds. Lenders were required to ensure that disbursements and repayments flowed directly between borrower bank accounts and regulated lenders, and fintechs had to disclose co-lending partners and full fees up front. These rules reinforced the need for Key Fact Statements and explicit borrower consent.
Collections practices remained governed by fair practices principles. Harassment, abusive language and out-of-hours calls are prohibited, and borrowers have clear rights to grievance redressal. Regulators emphasised record-keeping of every call, message and consent, making audit trails mandatory. Telecom rules and do-not-disturb registries further constrained automated dialling. Modern collections platforms therefore embed compliance by design, enforcing do-not-call lists, limiting contact frequency, and capturing consent for each channel and message. These controls convert compliance from a risk cost into a trust advantage.
Traditional collections relied on large teams of agents and manual processes, which are error-prone and expensive. Digital collections platforms demonstrated meaningful efficiency gains by automating day-one reminders, flagging persistent defaulters, and prioritising accounts for human intervention. Early contact and structured messaging reduced slippage into deeper buckets and improved cash flows.
The lending ecosystem spends tens of thousands of crores annually on retail collections, and only a small portion of that spend had been digitalised by 2025, leaving significant headroom. Digital outreach lowered per-contact costs, and moving from SMS to WhatsApp reduced outreach spend materially. AI chatbots and automated journeys improved DPD30 recovery rates in several deployments, showing how tech reduces cost-per-collection and lets small teams manage large portfolios more effectively.
Key platform features that drove gains included automated omnichannel outreach, AI segmentation that prioritised collector effort, agent dashboards and mobile field apps for real-time updates, centralised audit trails for compliance, and customizable workflows by product and borrower segment. Together, these features standardised best practices, reduced manual effort and improved borrower experience.
The trends in 2025 affected all lenders. Digital NBFCs with high-volume, small-ticket loans needed scalable, multilingual automation and predictive models. Retail NBFCs and MSME lenders prioritised predictable recovery performance and audit readiness. SME lenders benefited from borrower-centric workflows and regional language communication. Banks and co-lenders increasingly adopted SaaS platforms or outsourced early-stage collections to trim costs. Neo-banks and embedded finance players demanded API-first, cloud-based collections backends. BNPL and credit-card issuers relied on instant app and WhatsApp nudges for fast cycles. Microfinance institutions required highly empathetic, local language scripts to avoid the perception of harassment.
Across these segments, the common need was a modern collections platform that pairs AI-driven automation with compliance guardrails and human empathy. Such platforms enable collection heads to reduce DPDs, risk officers to maintain ethical standards, CTOs to integrate robust APIs, and CEOs to improve unit economics. For day-to-day users, unified dashboards provide visibility into buckets, agent performance and consent logs, replacing fragmented spreadsheets and manual notes.
India’s lending ecosystem in 2025 stood at an inflection point. Digital credit expanded financial inclusion while creating operational and asset quality challenges. The winners were lenders that coupled data-driven automation with borrower-centric practices. Advances in AI, UPI autopay and messaging apps offered powerful levers to reach borrowers efficiently, while regulatory expectations mandated traceability and transparency. The practical solution is hybrid. Automation must operate at scale, and every automated step must be fully auditable and humane in execution.
Tech-forward collection platforms became table stakes. By embedding AI segmentation, omnichannel outreach, self-service settlement options and compliance features from day one, lenders could reduce costs and NPAs without sacrificing borrower goodwill. Embracing these innovations lets Indian lenders defend asset quality while continuing to expand credit access. The path forward turns compliance and cost efficiency into strategic advantages rather than constraints.