Use case · NBFC collections

Bulk reminder runs with execution-level reporting.

NBFC collections teams use Vocily AI to run reminder batches in Hindi, Hinglish, and regional languages — with every call landing as a structured execution record.

The problem

Daily-due lists outgrow daily-callable capacity.

NBFC due lists hit thousands every morning across cities and languages. Human teams can only touch a fraction before the due-date window closes, and the calls that do happen aren't always scripted consistently. Vocily AI handles the bulk run so humans handle the cases that need a person.

Problem · Solution

The problem today

An NBFC's daily-due list outgrows daily-callable capacity by mid-month. A mid-size NBFC has thousands of borrowers due every cycle across cities, languages, and bucket stages — and a calling team that can realistically touch 30–45% of that list once. The rest go unreached, slip past the due window, and become a more expensive problem. Bucket-1 reminders that should be polite nudges become bucket-2 escalations because nobody actually called in time. Reporting is patchy because outcomes are filled in after the call, when at all.

How Vocily AI handles it

  • Daily-list bulk runs

    Load the full daily-due CSV (or push via API) — Vocily AI runs the entire list in a single shift, with paced concurrency so nothing rate-limits.

  • Per-portfolio segmentation

    Separate agents, scripts, and caller IDs per portfolio (personal loan, two-wheeler, gold, MSME) — outcomes report cleanly per book.

  • Live LMS integration

    Real outstanding, due date, last payment, and bucket — pulled from your LMS at call time and confirmed back when the conversation closes.

  • Bucket-stage tone calibration

    Bucket-1 conversations stay warm and reminder-style; later buckets shift to firmer language while staying compliant. Tone is the script, not the agent's mood.

  • Daily reporting roll-up

    Per-call outcomes roll up into the daily numbers your collections head wants — coverage, PTP rate, disputes, escalations, language mix.

How the conversation runs

Conversation, then action.

Step 01

Portfolio queued

Borrowers due this week are loaded into a batch.

Step 02

Calls placed

Vocily AI runs the batch through the assigned agent and provider stack.

Bulk run
Step 03

Per-call outcomes

Each call writes back to your collections system through API tools.

Step 04

Daily reporting

Custom analysis builds the daily numbers leadership wants to see.

Listen in

Bucket-1 reminder, Hinglish.

Hinglish

Hi Suresh ji, ABC NBFC se. Aapki EMI ₹4,200 due hai — kal tak pay kar denge?

Salary 7 tareekh ko aayegi, 8 ko pay kar dunga.

Got it. 8 tareekh ka promise note kar diya. Late fee avoid karne ke liye 8 tak hi ho jayega na?

Captures PTP + reaffirms

Haan, pakka 8 ko.

Illustrative — real call flows run end-to-end inside Vocily AI

Common questions

What teams ask before they switch.

Vocily AI places calls at the concurrency your provider stack and your LMS write-back can sustain — call volume scales with what your downstream systems can absorb, not with a hard platform limit.