Crypto card cashback after fees: what $1,000 a month really returns
A crypto card can advertise 2%, 3%, 8% or even 10% rewards and still produce a very different economic result. Lumpascan models the reward against only the costs that actually apply to the user's spending pattern: crypto conversion, foreign-currency spend, ATM usage and fixed card fees.
$20 on $1,000 before costs
After the full fee scenario below
95% of headline value disappears
Effective value = rewards − costs that actually apply
For a monthly spending amount S, the simplified model is: reward value = S × reward rate; FX cost = S × foreign-spend share × FX fee; conversion cost = S × crypto-conversion fee; ATM cost = ATM withdrawals × ATM fee; fixed cost = monthly fee + annual fee ÷ 12. Effective return is net value ÷ S.
How 2% becomes 0.10%
This is a sensitivity test, not the tariff of a named card. Each row adds one realistic cost variable while keeping monthly card spend fixed at $1,000. It shows why ranking cards by the largest advertised reward percentage can be economically misleading.
| Scenario | Rewards | Conversion | FX | ATM | Fixed | Net | Effective |
|---|---|---|---|---|---|---|---|
| Headline only | +$20.00 | −$0.00 | −$0.00 | −$0.00 | −$0.00 | $20.00 | 2.00% |
| + 0.9% crypto conversion | +$20.00 | −$9.00 | −$0.00 | −$0.00 | −$0.00 | $11.00 | 1.10% |
| + 1% FX on 30% of spend | +$20.00 | −$9.00 | −$3.00 | −$0.00 | −$0.00 | $8.00 | 0.80% |
| + $5 fixed monthly cost | +$20.00 | −$9.00 | −$3.00 | −$0.00 | −$5.00 | $3.00 | 0.30% |
| + $100 ATM at 2% | +$20.00 | −$9.00 | −$3.00 | −$2.00 | −$5.00 | $1.00 | 0.10% |
Conversion cost can eat the reward before FX matters
A 0.9% conversion cost on the full $1,000 removes $9 from a $20 reward. The effective return is already down from 2.00% to 1.10% before foreign-currency spend, ATM use or fixed fees are considered.
FX should apply only to foreign-currency spend
If 30% of monthly spend is in another currency, a 1% FX fee should be charged to $300, not to the whole $1,000. That is a $3 cost. Adding every fee percentage to total spend would overstate the cost and produce bad comparisons.
Fixed fees punish low spend more heavily
A $5 monthly cost is 0.50% of a $1,000 spending base but only about 0.17% of a $3,000 base. A card that looks weak for a light spender can have different economics for a heavier user, even before reward caps or tiers.
ATM economics are a separate bucket
A 2% ATM fee does not mean 2% of all card spending. If the user withdraws $100, the modeled cost is $2. Free ATM thresholds, operator surcharges and tier rules can change the real result further.
Why headline cashback percentages are not directly comparable
The current verified Lumpascan catalog contains materially different reward structures. Bybit publishes programmes up to 10% depending on region/tier; Wirex advertises up to 8%; Bitget Wallet up to 3%; Nexo up to 2% in Credit Mode; Coinbase uses rotating rewards rather than a permanent fixed rate; Crypto.com varies by tier, plan and market. Those percentages describe different products and qualification rules, so the correct comparison is effective value for a defined user scenario, not the largest number in the marketing headline.
Costs this simple model still does not pretend to know
Reward caps, excluded merchant categories, staking or subscription requirements, borrowing interest in credit-mode products, opportunity cost of locked tokens, card-network exchange rates, tax treatment, free ATM thresholds and issuer-specific spreads can all change the result. They should be added only when the current product terms make them relevant to the chosen scenario.
Test the economics behind the headline cashback.
Enter the current fee terms for a card and your own spending pattern. The calculator applies each fee only to the relevant spending bucket instead of adding unrelated percentages together.
Illustrative calculator only. Cashback caps, excluded merchant categories, free ATM thresholds, card tiers, staking requirements, tax treatment and issuer exchange rates can materially change the result.