Examples
Examples
Try the starting example
- Categories: name, covered loss $, category sublimit $
- Jewelry,500,200 Electronics,400,500
- Single deductible after category caps ($)
- 100
- Overall remaining payout limit ($)
- 1000
- Loss after each category sublimit ($)
- Jewelry: 200.00; Electronics: 400.00
- Total reduction from category sublimits ($)
- $300.00
- Model payout after deductible and overall limit ($)
- $500.00
- Total entered loss retained ($)
- $400.00
Try another scenario
- Categories: name, covered loss $, category sublimit $
- Jewelry,500,200 Electronics,400,500
- Single deductible after category caps ($)
- 100
- Overall remaining payout limit ($)
- 300
- Loss after each category sublimit ($)
- Jewelry: 200.00; Electronics: 400.00
- Total reduction from category sublimits ($)
- $300.00
- Model payout after deductible and overall limit ($)
- $300.00
- Total entered loss retained ($)
- $600.00
Calculation method
Calculation method
Loss after each category sublimit ($)
min(category loss,category sublimit).
Total reduction from category sublimits ($)
Sum original category loss−capped loss.
Model payout after deductible and overall limit ($)
min(overall limit,max(0,sum capped categories−single deductible)).
Total entered loss retained ($)
Original total loss−model payout.
Symbols and units
- a
- Categories: name, covered loss $, category sublimit $
- b
- Single deductible after category caps ($)
- c
- Overall remaining payout limit ($)
Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.
Assumptions & limits
Assumptions & limits
- Applies category caps, then one deductible, then one global payout limit in exactly that order. Real policies can use a different order; this does not determine coverage.
Are these inputs private?
These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.
Further reading
NAIC: insurance terminology background; the displayed model is user specified ↗
Background reading; this does not imply endorsement or independent review of SumFizz.