Model customer lifetime value accounting for credit losses and NPA risk
Price for credit losses upfront. Don't let hidden NPAs derail growth.
Book Free Growth CallCredit losses are baked into your unit economics. Price them upfront and build collections ops to improve recovery.
Book Strategy CallLTV:CAC is one metric. Learn the full suite of metrics that determine whether your fintech survives.
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Step 1: Pick your business model (Lending, BNPL, Credit Card, or Deposit). Step 2: Enter ARPU/month (monthly revenue per customer, including interest, origination fees, transaction fees, or spreads). Step 3: Enter gross margin % (gross profit before opex as % of revenue). Step 4: Enter monthly churn % (what % of customers you lose each month due to deactivation, switching, or natural attrition). Step 5: Enter annual default or NPA rate (% of your book that defaults or writes off annually). Step 6: Enter recovery rate (% of defaulted amount you recover through collections). Step 7: Enter CAC (blended customer acquisition cost).
Risk-adjusted LTV: Lifetime value after accounting for defaults, recoveries, and churn. This is your real number. LTV:CAC ratio: If above 3.5:1, you are fundable. 3:1 to 3.5:1 is marginal. Below 3:1 is a blocker. Default drag (INR): How much each customer loses in value due to credit risk. Verdict: Fundable, marginal, or not viable.
If your LTV:CAC is below 3.5:1, don’t scale CAC. Instead, fix one lever: improve underwriting (lower default rate), improve collections (higher recovery), or increase ARPU. Each 1% improvement in recovery rate can shift LTV:CAC from 3:1 to 3.3:1. Each 0.5% improvement in default rate can shift LTV:CAC by 0.2:1. Focus on operational excellence before you try to out-acquire competitors.

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Frequently asked questions
Because default risk silently compresses your unit economics. A lending fintech that ignores NPA rates looks profitable until defaults ramp in years 2-3. By then, you have burned investor capital and burned through customer cohorts. Risk-adjusted LTV forces you to price credit losses into payback math upfront, which prevents overpricing CAC or overestimating lifetime value.
NPA (Non-Performing Asset) is the RBI term. Default is the business term. Technically: NPA is a loan 90+ days past due. Default is when you write it off and stop accruing income. For this calculator, use your annual write-off rate (actual defaults that hit your P&L). If your NPA rate is 3% but only 60% of NPAs eventually write off, use 1.8% in the default field.
BNPL has higher default rates than lending (5-7% annual) due to transaction-level default vs relationship-based creditworthiness. Acceptable LTV:CAC for healthy BNPL is 3.5:1 or higher. Recovery rates are also lower (10-20% vs 25-40% for lending). Most BNPL fintechs model conservative 6% default and 15% recovery, which leads to healthy LTV:CAC in the 3.5-4.5:1 range.
Recovery rate is the % of defaulted loans you get back in collections. Higher recovery directly increases risk-adjusted LTV. A 2% increase in recovery rate (say, 25% to 27%) can shift your LTV:CAC from 3:1 (not fundable) to 3.2:1 (marginal). Invest in collections infrastructure early (SMS reminders, partial payments, debt recovery ops) to improve recovery and unlock unit economics.
No. Secured lending (backed by collateral, house, gold) has much lower default rates (0.5-1.5% annually). Recovery rates are higher (60-90%). Unsecured lending has higher default (2-4% annually) and lower recovery (20-40%). This calculator is for unsecured lending and BNPL. If you are a gold lender or mortgage fintech, your acceptable LTV:CAC can be lower (2.5:1 is healthy) because credit risk is lower.
No. Deposit fintechs don’t originate credit risk, so default rates don’t apply to their model. Their LTV is based on transaction volume and cross-sell of investment/insurance products. But they still need to model funding cost (what you pay depositors) vs yield on investments/loans, which is a different LTV:CAC calculation. Don’t use this calculator for deposit fintechs; focus on spread margin and customer stickiness instead.
If you assume zero recovery, you are modeling the worst case where every default is a total loss. This is conservative but unrealistic for most fintechs operating collections ops. Even if recovery is just 15-20%, your LTV:CAC improves materially. If your recovery is genuinely 0% (you are not doing collections), that’s a process problem to fix before you scale.