9.2 Headcount by AUM
The headcounts below are indicative, not prescriptive. Adjust to the specific operating mix (more anchor programmes need more partner ops; more own-channel needs more sales).
Stage 1: ₹30 Cr book (year 1)
Section titled “Stage 1: ₹30 Cr book (year 1)”Total: ~20 – 28 people including founders.
| Function | Headcount |
|---|---|
| Executive | CEO + 1 |
| Sales / channels | 2 – 3 |
| Credit | Head + 2 – 3 analysts |
| Operations | Head + 3 – 5 (KYC, disbursement, recon, customer support combined) |
| Collections | 1 – 2 (in-house) + outsourced agents |
| Engineering | 6 – 10 (platform, data, integrations) |
| Finance | Head + 1 – 2 |
| Compliance + CS | Compliance officer + CS |
| Risk | CRO (often combined with credit head at this stage) |
| InfoSec | 1 (could be fractional + vendor SOC) |
| Vendor / partner mgmt | 1 |
Stage 2: ₹100 Cr book (year 1.5–2)
Section titled “Stage 2: ₹100 Cr book (year 1.5–2)”Total: ~50 – 75 people.
| Function | Headcount |
|---|---|
| Executive | CEO + COO + 1 |
| Sales / channels | 5 – 8 (split by partner, DSA, direct, CA) |
| Credit | Head + 5 – 8 analysts + risk analyst |
| Operations | Head + 8 – 12 (KYC + disbursement + recon + LMS ops + customer support) |
| Collections | 5 – 8 in-house + outsourced |
| Engineering | 15 – 22 (split by module teams) |
| Data / Analytics | 2 – 3 |
| Finance | Head + 3 – 5 |
| Compliance | Compliance Officer + 1 – 2 |
| Risk | CRO + 1 – 2 (separated from credit by now) |
| InfoSec | 2 – 3 (incl. SOC analyst) |
| Vendor / partner mgmt | 2 – 3 |
| Internal Audit | 1 |
Stage 3: ₹300 Cr book (year 2.5–3)
Section titled “Stage 3: ₹300 Cr book (year 2.5–3)”Total: ~120 – 180 people.
| Function | Headcount |
|---|---|
| Executive | CEO + COO + Heads |
| Sales / channels | 15 – 25 (multi-channel) |
| Credit | Head + 12 – 18 (analysts + senior + segment-specific) |
| Risk | CRO + 4 – 6 (model, monitoring, ALM) |
| Operations | Head + 25 – 35 (departments) |
| Collections | 12 – 20 in-house + scale outsourced |
| Engineering | 35 – 55 (platform teams) |
| Data + ML | 8 – 12 |
| Finance | Head + 8 – 12 |
| Compliance | 4 – 6 |
| InfoSec | 5 – 8 |
| Vendor / partner mgmt | 5 – 8 |
| Internal Audit | 2 – 3 |
| Legal | 2 – 3 |
- Engineering scales superlinearly with platform complexity, not book size. A
₹300 Crbook with3co-lending partners needs more engineering than one with1partner. - Collections scales with NPA pipeline, not book size alone. A book with
3% NPAneeds different staffing than1% NPA. - Sales/channels scales with origination strategy. Heavy CA / partner / embedded distribution scales slower in headcount than direct DSA distribution.
- Compliance and InfoSec must scale with regulatory complexity, not strict-line book size. Going NBFC-ML or onboarding additional partners adds non-linear obligations.
Hiring trap to avoid
Section titled “Hiring trap to avoid”The recurring trap: hiring sales / DSA aggressively before underwriting / collections capacity is built. The result is a surge of poor-quality applications, declines (or worse, approvals that go bad), DSA frustration, and reputation damage. Hire credit and collections ahead of sales, not behind.