How a Leading Indian Microfinance Company Handles 2M+ Calls/Month with AI Voice Agents
Scaling debt collection from 350,000 to over 2 million calls per month — while cutting costs by 60% and achieving zero compliance violations.
Company Overview
[COMPANY NAME] is one of India's leading microfinance and digital lending institutions, serving millions of borrowers across 15+ states. With a loan book exceeding ₹10,000 crore, they manage one of the largest collections operations in the Indian NBFC sector.
Microfinance / NBFC
Pan-India (15+ states)
Millions of accounts
2M+ calls/month
Scaling Collections Without Scaling Costs
[COMPANY NAME] faced a challenge common to every fast-growing NBFC in India: their loan book was growing faster than their ability to collect.
Agent Capacity Ceiling
400+ agents fully utilised. Adding more meant linear cost growth with diminishing returns.
Language Coverage Gaps
Agents covered only 4–5 languages. Borrowers in Odisha, Assam, and Kerala were underserved — recovery lagged 15–20%.
Rising Costs
Agent salaries rising 10–15% annually. 45% attrition meant constant recruitment. Cost per minute exceeded ₹20.
Compliance Pressure
RBI guidelines tightening. Every human call a potential compliance risk. QA could audit only 5% of calls.
Breeze AI Voice Agents for Collections
[COMPANY NAME] partnered with Simpragma to deploy Breeze — an AI voice agent platform purpose-built for high-volume, multilingual collections in India.
Own Telephony Infrastructure
Proprietary Asterisk-based SIP stack with direct trunking to Indian telcos. Eliminated Twilio dependency and reduced telephony costs by 80%.
11 Indian Languages
Hindi (including dialects), Tamil, Telugu, Kannada, Marathi, Bengali, Gujarati, Malayalam, Odia, Punjabi, and English — automatic language selection based on borrower region.
Collections-Specific AI
Payment reminders, promise-to-pay capture, objection handling, payment plan negotiation, real-time payment link delivery, and smart escalation to human agents.
Deep LMS Integration
Real-time borrower data: loan details, payment history, risk scoring, compliance flags. The AI knows exactly who it's calling and why.
100% Compliance Coverage
Every call recorded, transcribed, and checked against time-of-day restrictions, script adherence, DND compliance, and full audit trails.
From Kickoff to 2M Calls in 6 Months
Discovery & Design
Weeks 1–3Requirements gathering, LMS integration spec, conversation flow design
Pilot Deployment
Weeks 4–810,000 calls/month, Hindi only, 1–15 DPD segment
Production Rollout
Weeks 9–14200,000 calls/month, 4 languages, 1–30 DPD
Scale Expansion
Weeks 15–242,000,000 calls/month, 11 languages, full portfolio
Results That Speak for Themselves
Volume & Reach
| Metric | Before | After | Change |
|---|---|---|---|
| Monthly calls | 350,000 | 2,000,000+ | +471% |
| Accounts contacted/cycle | ~120,000 | ~650,000 | +442% |
| Languages supported | 4–5 | 11 | +120% |
| Daily call capacity | 15,000 | 80,000+ | +433% |
Cost
| Metric | Before | After | Change |
|---|---|---|---|
| Cost per connected minute | ₹20–22 | ₹7–9 | −60% |
| Monthly collections OpEx | ₹85L+ | ₹37L | −56% |
| Telephony cost/min | ₹3–4 (cloud) | ₹0.80 (own stack) | −78% |
| Human agents required | 400+ | 80 (escalation only) | −80% |
Compliance & Quality
Key Insights
AI Outperforms Humans for Early-Stage Collections
For 1–15 DPD accounts, AI agents slightly outperformed human agents on promise-to-pay rate. Consistency, timing, and reach matter more than negotiation skill for reminders.
The Hybrid Model Is Essential
For accounts past 30 DPD, human agents still outperform on conversion. The optimal model: AI handles volume and pre-qualification, routing complex cases to a smaller, specialised human team.
Own Telephony Stack Is Non-Negotiable at Scale
The difference between ₹3.50/min (cloud) and ₹0.80/min (own stack) at 2M calls/month is ₹54 lakh per month — ₹6.5 crore annually.
Language Coverage Drives Regional Recovery
Adding Odia, Assamese, and Malayalam increased contact rates in those regions by 3x and recovery rates by 18%.
“We evaluated multiple voice AI platforms. Most could demonstrate a compelling pilot. Breeze was the only one that could prove scale — 2 million calls per month with the reliability and compliance framework we needed. The cost structure, with their own telephony stack, made the economics work at our volume.”
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