Finance Buddha
Client Snapshot
Finance BuddhaFintech / Personal & SME Lending — IndiaSize: 250
Finance Buddha (Finbud Financial Services Limited) is a Bangalore-headquartered fintech and personal-loan marketplace serving SME, Business Loan, Loan Against Property, Overdraft and Gold Loan borrowers across India. Inbound enquiry volume from digital and DSA channels feeds a high-velocity counselling motion where speed-to-lead and qualification accuracy directly drive disbursed-loan volume.
Caller Digital’s Conversational AI
Caller Digital deployed Anjali — a custom-trained outbound voice AI agent positioned as a Finance Buddha relationship manager — supported by an integrated WhatsApp engagement layer. Anjali runs a stage-driven Hinglish-first conversation: greeting and verification, value intro, structured need discovery (one question at a time), pre-qualified offer pitch, application-link consent, and optional warm-transfer to a logged-in human counsellor. The agent captures 12 core qualification fields plus 7 AI-inferred briefing fields (objection type, competitor name, rate quoted, sentiment, next best action) for the human counsellor's pre-call brief. WhatsApp fallback fires after 3–4 unanswered attempts with an approved application-link template via the WhatsApp Business API. The system writes 15 distinct dispositions back to the Caller Digital dashboard, with CRM API write-back scheduled for post-POC integration. DPDP-aligned consent capture, TRAI DLT scrubbing, and RBI Fair Practices Code script enforcement (no aggressive sales, no rate commitments, instant DND honour) are built into the agent's guardrails.
Anjali went live in 16 working days from contract signature. The POC is configured against nine measurable performance standards including ≥90% lead qualification accuracy, ≥95% information response accuracy, ≥95% lead information capture, ≥95% counsellor warm-transfer success, ≥98% outbound dial-out success, ≥98% WhatsApp workflow execution, and ≤3-second P50 bot initial response latency. The 13-day connectivity analysis Finance Buddha ran before launch identified 12 PM–2 PM as peak pickup (38–39%) and the dialler is prioritised against that window. Transparent INR per-minute pricing at ₹5/min on a 10,000-minute prepaid POC, with no enterprise minimums and no multi-year lock-in, gave the lead-operations team the cost predictability that manual SDR scale-up could not.
Anjali went live in 16 working days from contract signature. The POC is configured against nine measurable performance standards including ≥90% lead qualification accuracy, ≥95% information response accuracy, ≥95% lead information capture, ≥95% counsellor warm-transfer success, ≥98% outbound dial-out success, ≥98% WhatsApp workflow execution, and ≤3-second P50 bot initial response latency. The 13-day connectivity analysis Finance Buddha ran before launch identified 12 PM–2 PM as peak pickup (38–39%) and the dialler is prioritised against that window. Transparent INR per-minute pricing at ₹5/min on a 10,000-minute prepaid POC, with no enterprise minimums and no multi-year lock-in, gave the lead-operations team the cost predictability that manual SDR scale-up could not.
Before Caller Digital
Manual SDR calling could not maintain sub-15-minute speed-to-lead at scale
Qualification fields captured inconsistently across counsellors
Competitor offers discovered too late to defend against
Counsellor pre-call briefing took 5–10 minutes of manual lead review
No structured AI summary or sentiment scoring for cold leads
Hindi-Hinglish-English code-switching depended on which SDR picked up the lead
After Caller Digital
Sub-15-minute outbound on every inbound lead, Hinglish-first by default
12 core fields plus 7 AI-inferred briefing fields captured on every connected call
Competitor name, rate and offer captured live in the qualification flow
AI Counsellor Summary + Next Best Action surfaced to seniors pre-handoff
Sentiment + objection type tagged on every call for funnel diagnostics
Consistent Hinglish-first persona across 100% of dispositioned calls
Benefits of Integration
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Frequently Asked Questions
An outbound voice AI agent (Anjali) for first-level lead qualification across SME Loans, Business Loans, Loan Against Property, Overdrafts and Gold Loans, supported by a WhatsApp engagement layer for follow-ups and re-engagement after unanswered calls.
Hindi, English and Hinglish (the natural Hindi-English code-mix Indian telecallers use). The default register is Hinglish; the agent mirrors whichever language the borrower is comfortable in.
During the POC, lead ingestion is via CSV / Excel, and call outcomes — dispositions, transcripts, AI summary, sentiment, recordings — are accessible via the Caller Digital dashboard and email alerts. CRM API push from the Finance Buddha lead-source system is planned for post-pilot integration.
Caller Digital's agent enforces RBI FPC at the platform layer: no aggressive sales language, no commitment to specific interest rates or sanctioned amounts, immediate DND honour on opt-out keywords (English or Hindi), transparent disclosure that the agent is calling on behalf of Finance Buddha, and prohibited terms screening throughout the conversation.
The POC is measured against nine performance standards: ≥90% lead qualification accuracy, ≥95% information response accuracy, ≥95% lead information capture, ≥95% counsellor warm-transfer success, ≥90% escalation routing accuracy, ≥98% outbound dial-out success, ≥98% WhatsApp workflow execution, ≥99% retry-logic execution, and ≤3-second P50 bot initial response latency.
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