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Financial Services Calling

Qualify loan eligibility, confirm card credentials, and dispatch collections follow-up campaigns securely.

Automating Financial Inquiries & Pre-Qualification

Banks, NBFCs (Non-Banking Financial Companies), and fintech platforms process thousands of lead inquiries and pre-qualification applications weekly. Outbound validation is critical to identify high-value applicants, but manual calling is slow and introduces significant operational latency. When prospects submit loan forms, their intent declines quickly if they do not receive a follow-up call. Human call centers waste valuable time chasing contacts who are unqualified or provide invalid data.

Closerr automates the financial validation pipeline, allowing organizations to qualify borrower interest in under 60 seconds. When a lead registration is triggered, our voice AI agent initiates a telephone call to gather necessary verification metrics: income brackets, employment status, requested loan tenure, and credit card usage history. High-value leads are pre-qualified and synced directly to your underwriting system, while low-intent submissions are filtered out automatically.

NBFC Credit Pre-Qualification Mappings

Outbound campaigns qualify applicants against standard NBFC underwriting benchmarks, collecting crucial parameters in real time. The voice agent guides the caller through qualification loops and evaluates candidate fit dynamically:

  • Monthly Salary Checks: AI agents ask and verify the candidate's net monthly inflow to calculate Debt-to-Income (DTI) metrics.
  • Employment Verification: The system logs whether the lead operates as a salaried employee, self-employed practitioner, or business owner.
  • Existing Financial Liabilities: Prospects declare active loans or credit commitments to evaluate total liability exposure.
  • Identity Verification: The agent confirms the last four digits of national identification numbers (PAN or Aadhaar in India) to match records before routing.

Automated Billing & Collection Follow-Ups

Managing accounts receivable and unpaid balances requires consistent outreach. Manual collection calling is often inefficient, stressful, and subject to strict regulatory guidelines. Closerr helps finance teams automate friendly billing reminders and collection notifications.

Outbound voice agents call accounts with overdue balances, notify them of payment details, confirm receipt of invoices, and offer localized payment links. If a user agrees to pay, the system triggers a payment link SMS dynamically during the call, allowing the user to complete the transaction without hanging up.

Overdue Billing API Call:
POST /api/v1/campaigns/collections
{
  "lead_phone": "+919876543210",
  "amount_due": "INR 12,500",
  "due_date": "2026-06-25",
  "invoice_id": "inv_882910"
}

AI Outbound Agent Script:
"Hello! I am calling from Closerr Finance. This is a reminder that invoice inv_882910 for INR 12,500 is due on June 25. Would you like me to send you the secure payment link via SMS?"

Credit Criteria Boundaries & NBFC Routing Logic

During loan pre-qualification calls, Closerr's voice agents check candidates against preset credit boundaries to optimize loan approvals. Administrators configure minimum monthly salary thresholds, employment history requirements, and debt-service coverage ratio (DSCR) constraints inside the dashboard. As the lead responds, the conversational engine parses the numerical values, checks the values against the active matrix, and calculates an eligibility score.

If a candidate meets the criteria, the agent dynamically maps the application to the most suitable NBFC partner database. For instance, small-ticket personal loans are directed to specific consumer-finance APIs, while larger mortgage requests are pushed to institutional underwriting systems. This intelligent, multi-tenant routing is managed via secure, tokenized API endpoints:

POST /api/v1/routing/nbfc
{
  "application_id": "app_99182",
  "qualification_score": 0.85,
  "metrics": {
    "income": 75000,
    "requested_amount": 500000,
    "credit_type": "secured"
  },
  "nbfc_destination_id": "nbfc_muthoot_02"
}

By evaluating eligibility before human handoff, financial organizations increase sales efficiency. Underwriters review pre-screened profiles with verified income claims and completed identity credentials, reducing application processing costs and improving credit book performance.

PCI-DSS Telemetry Security & Wallet Capping

Closerr implements security practices to protect billing data and API keys. Stored database tokens and credentials are secure in our hosted environment. We enforce role-based access control (RBAC), meaning call logs and transcripts are restricted to authorized underwriting accounts.

Additionally, to prevent accidental billing overheads or API key abuse, Closerr incorporates dynamic wallet capping. Administrators can configure credit limits per campaign. Once a campaign's calling minutes reach the balance threshold, the telephony loop terminates automatically, shielding your account from unexpected costs. Full auditing logs track all configuration changes, ensuring complete transparency.

We also support advanced voice biometrics and secure credential processing. Callers can enter verification digits via DTMF (Dual-Tone Multi-Frequency) touch-tones. The DTMF signals can be configured to process credentials without showing them in general transcript logs, protecting user financial details.

Outbound campaigns also enforce strict calling windows. To maintain compliance with regional telecom laws (like local opt-in rules and TRAI), Closerr limits outgoing dials to legal telemarketing hours (typically 9:00 AM to 7:00 PM local time). The system reads the recipient's geographic routing code, evaluates active local time zones, and suspends outbound queues if the contact falls outside the compliant calling window, resuming them automatically when the next window opens.

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Closerr AI Telephony Private Limited, India.

AI Output Disclaimer: All call transcripts and voice agent responses are automatically generated and may contain errors. Do not rely solely on AI outputs for critical decisions.