The bank's collections operation was drowning in volume, compliance risk, and inconsistent promise-to-pay capture. BootLabs built a conversational voice AI agent that handles the full outbound collections call flow autonomously — at 3x human throughput with 100% script compliance.
The bank's collections team was making thousands of outbound calls daily to customers with overdue EMIs, loan repayments, and credit card dues. Each call required a trained agent to identify the customer, explain outstanding dues, negotiate a payment date, capture a promise-to-pay, and escalate genuinely complex cases — hardship situations, disputes, fraud suspicion. The operation was expensive, volume-constrained, and carried significant compliance risk. RBI and SEBI regulations mandate that collection calls follow specific scripts, maintain customer dignity, and are fully auditable. Inconsistent agent behaviour under volume pressure created regulatory exposure and customer complaints. BootLabs built a conversational voice AI agent that handles the full outbound collections call flow autonomously — from greeting to promise-to-pay capture — with seamless escalation to human agents for complex cases and a 100% compliant, auditable script on every single call.
The bank's loan book growth outpaced the collections team's ability to scale. Thousands of overdue accounts needed outbound contact daily, but hiring proportionally more collection agents was cost-prohibitive and slow to ramp. Volume pressure meant a growing backlog of uncontacted accounts — reducing recovery rates and letting risk compound.
RBI guidelines and the bank's internal code of conduct require collection calls to follow specific scripts: permitted calling hours, mandatory disclosures, no harassment, and documented customer consent to payment commitments. Human agents — under volume pressure — deviated from scripts, creating audit findings and customer complaints that carried serious regulatory consequences.
When customers committed to a payment date, agents recorded it manually into the CRM — with inconsistent format, incomplete details, or missed entirely during high-volume shifts. Broken promise-to-pays went untracked and unescalated, meaning the bank had no reliable picture of which commitments were genuine and which needed follow-up.
The conversational AI agent places outbound calls using the bank's telephony infrastructure. It handles the full call flow in natural conversational Hindi and English (with regional language variants): greets the customer by name, states the purpose, provides specific overdue amount and account details pulled from core banking in real-time, and listens and responds to the customer's situation — end to end without a human on the line.
The agent handles common objections and scenarios — "I'll pay next week," "I've already paid," "I'm facing financial difficulty," "Transfer me to someone." It negotiates within pre-defined parameters (acceptable payment date range, minimum partial payment thresholds) and captures a structured promise-to-pay — script, amount, date — directly into the CRM via API, with no human transcription required.
The agent escalates to a human collector when it detects genuine financial hardship signals, legal threats, dispute of the amount owed, or fraud indicators. Escalation transfers the live call with full context — customer details, conversation transcript, and recommended resolution path — so the human agent has everything they need the moment they pick up.
Every call is recorded, transcribed, and stored immutably with full metadata. A compliance monitoring layer verifies that every AI-generated call follows the regulatory script. Post-call, a compliance score is generated per call, and any deviation from the approved script triggers an automated review flag. The full audit package is available for RBI inspection on demand, on any account.
The voice AI agent went live on the bank's existing telephony infrastructure without requiring a platform replacement. Collections throughput scaled immediately — not in weeks of hiring and training, but from day one of go-live. The compliance monitoring layer confirmed zero script deviations across every AI-handled call, and promise-to-pay data started flowing directly into the CRM in structured, actionable format from the first shift.
The collections team now handles only complex, high-value escalations — hardship negotiations, disputes, fraud cases — while the AI handles all routine volume. Human expertise is applied exactly where it creates the most recovery value.
Structured, immediate CRM updates mean follow-up actions trigger automatically the moment a commitment is made. Broken promise-to-pays are flagged and re-queued without manual review — closing a loop that was previously invisible.
Complete call evidence packages — recording, transcript, compliance score, metadata — are available on demand for any account, any call, any date. RBI inspection readiness went from a manual assembly exercise to an instant retrieval.
Consistent, dignified, and informative calls — every time. The AI never deviates from the approved script, never applies pressure beyond permitted parameters, and gives customers clear information about their account. Complaint rates from collection interactions dropped materially.
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