NBFC costing

In NBFCs, unit cost per product (loan, lease, or service) is typically computed by allocating fixed/step-fixed employee and overhead costs across the number of transactions or portfolio size, while variable costs (like processing, collection, or direct commissions) are charged directly. The industry practice is to use activity-based costing (ABC) or cost-per-loan models, where fixed costs are spread over expected business volumes to arrive at a defensible per-unit cost.

• Activity-Based Costing (ABC):
  • Costs are traced to activities (loan origination, underwriting, servicing, collections) and then assigned to products based on activity drivers.
  • Cost-per-loan approach: Total operating costs ÷ number of loans disbursed/managed.
  • Portfolio-level allocation: For investment-type NBFCs, costs are allocated on assets under management (AUM) basis.

Key Industry Practices

• Benchmarking: Compare cost-per-loan with peers to ensure competitiveness.
• Audit defensibility: Document allocation bases (e.g., per-loan, per-branch) to withstand regulatory scrutiny.
• Scalability: Costs per unit decline as loan volumes grow, so NBFCs emphasize scale efficiency.
• Regulatory compliance: Ind AS requires transparent disclosure of cost allocation policies for audit and RBI supervision.

Thank you, that was helpful. You had mentioned about benchmarking with peers, but these datas are not readily available as such. How do we go about that.                

Practical Approaches to Benchmarking Cost-per-Loan

1. Public Financial Disclosures (Indirect Ratios)

• Use annual reports of listed NBFCs: Extract operating expenses, employee costs, branch costs, and loan book size.
• Derive proxy ratios:
• Operating expense ÷ Loan book (Opex-to-AUM ratio).
• Operating expense ÷ Number of branches (branch efficiency).
• Employee cost ÷ Loan disbursed (staff productivity).
• These ratios don’t give “cost-per-loan” directly but allow relative benchmarking.

2. Industry & Credit Bureau Reports

• Sources like CRISIL, ICRA, CARE Ratings, RBI Financial Stability Reports often publish sector averages:
• Cost-to-income ratios.
• Opex-to-AUM benchmarks for NBFCs vs banks.
• These can be adapted into internal cost-per-loan equivalents.

3. Peer Grouping by Business Model
•     Compare with peers in similar segments (e.g., microfinance NBFCs, vehicle finance NBFCs).
•     Each segment has different cost structures — microfinance has higher per-loan costs due to small ticket sizes, while vehicle finance benefits from scale.

4. Internal Benchmarking & Scaling
•     Use your own historical data: Track cost-per-loan over time as volumes grow.
•     Benchmark against your own targets (e.g., cost-per-loan should decline 10–15% as loan book doubles).
•     This creates defensible documentation for auditors and regulators.

5. External Data Sources
•     Industry associations (FIDC, MFIN) sometimes publish operational efficiency benchmarks.
•     RBI’s supervisory returns (though not public) often feed into rating agency reports — useful for indirect benchmarking.

Though you won’t get a neat “peer cost-per-loan” dataset, but by triangulating Opex-to-AUM ratios, rating agency benchmarks, and internal scaling trends, you can build a defensible, regulator-friendly benchmarking framework.

• Ind AS requires disclosure of allocation bases — not exact peer comparisons.
• RBI supervision focuses on efficiency ratios (Opex-to-AUM, cost-to-income), so aligning your benchmarking to those ratios ensures regulatory defensibility.

When documenting allocation bases:

• State clearly: “Cost-per-loan benchmarking is based on publicly available ratios (Opex-to-AUM, cost-to-income) from peer NBFCs, adapted internally to per-loan equivalents.”
• Disclose assumptions: ticket size, loan volume, branch spread.
• Highlight limitations: “Direct peer cost-per-loan data is unavailable; hence proxies are used.”
• This transparency makes the policy audit-proof.

Thank you. This helped.

My pleasure..