CLIENT PROFILE
A digital lending institution with a high-volume, small-ticket unsecured loan book, originating personal loans and consumer durable finance across tier-2 and tier-3 markets in multiple states.
BUSINESS CONTEXT
The institution’s early-bucket portfolio required daily outbound contact at a scale the in-house tele-calling team could not sustain, particularly across the range of regional languages spoken by its borrower base.
Reliance on manual calling meant coverage gaps, inconsistent scripting across agents, and limited ability to scale outreach during periods of portfolio growth without proportionally increasing headcount.
CHALLENGE
- The tele-calling team could realistically contact only a fraction of the early-bucket portfolio each day, leaving a large share of accounts uncontacted between billing cycles.
- Manual calling scripts varied by agent, leading to inconsistent messaging and, in some cases, unstructured or incomplete capture of Promise-to-Pay commitments.
- Language coverage was limited to a handful of regional languages, reducing engagement quality in several geographies.
- There was no systematic way to identify borrower hardship or disputes during a call, meaning genuine service issues were sometimes treated as routine non-response.
CLEARDU PLATFORM IMPLEMENTED
Primary platform: VoiceBot
VoiceBot was implemented as the primary platform because the requirement was high-volume, consistent, multilingual borrower outreach with structured response capture – the core purpose of ClearDu’s AI-powered borrower engagement platform.
DETAILED SOFTWARE IMPLEMENTATION
- Outbound calling campaigns were configured by DPD bucket, with separate conversation flows for early reminders, PTP follow-ups, and payment confirmation calls.
- Conversation scripts were built and validated in the borrower base’s principal regional languages, with natural-language handling for common borrower responses.
- Borrower identity verification and account-level context were integrated at the start of each call, allowing VoiceBot to reference the correct loan and outstanding amount.
- Response classification logic captured payment intent, PTP commitments with dates, callback requests, and hardship or dispute flags, feeding this data directly into the collection workflow.
- Calls flagged for hardship, dispute, or complex negotiation were automatically escalated to human agents with full call context, avoiding the need for the borrower to repeat information.
- Campaign-level analytics dashboards were configured to track contact rates, PTP capture, and conversion by language, bucket, and time of day.
PROCESS TRANSFORMATION
Before: Before VoiceBot, outbound contact was limited by manual calling capacity, with inconsistent scripting, narrow language coverage, and unstructured capture of borrower responses.
After: After implementation, the institution runs consistent, multilingual outreach across the full early-bucket portfolio daily, with structured PTP capture and automatic escalation of complex cases to human agents.
- Tele-calling teams focus on escalated, complex, or high-value accounts rather than routine reminder calls.
- Collection managers gained campaign-level analytics on contact and conversion by language and bucket.
- Borrowers received consistent communication in their preferred language with a working self-service payment path.
PLATFORM CAPABILITIES USED
- Automated outbound calling campaigns
- Multilingual borrower conversations
- DPD-based calling campaign configuration
- Promise-to-Pay and payment intent capture
- Borrower response classification
- Hardship and dispute identification
- Escalation to human agents with call context
- Callback scheduling
- Campaign-level analytics
KEY RESULTS
- 42% reduction in manual calling effort
- 1X increase in daily borrower contact coverage
- 54% Promise-to-Pay conversion on VoiceBot-initiated calls
- 22% reduction in cost per contacted account
- 31% improvement in language-appropriate engagement across tier-2 and tier-3 accounts
IMPLEMENTATION CONSIDERATIONS AND CONTROLS
- Calling windows and frequency were configured to align with communication consent and applicable regulatory norms.
- Escalation thresholds ensured borrowers raising hardship or disputes were promptly routed to a human agent.
- Call outcomes and interaction history were logged for each account to maintain a consistent communication record.
- Campaign scripts were reviewed and iterated based on response analytics to improve engagement quality over time.
CONCLUSION
By deploying VoiceBot for structured, multilingual outbound engagement, the institution scaled daily borrower contact well beyond manual calling capacity while maintaining consistent messaging and reliable PTP capture. Human agents were freed to focus on escalated and high-value cases, improving both operational efficiency and the quality of borrower engagement across the portfolio.