Credit risk expected loss.

Expected loss is a credit risk metric: the average loss you'd experience on a loan given the probability of default, exposure at the time of default, and loss given default (how much you can't recover). Basel banking framework uses this formula; insurance and lending firms use it daily for pricing and provisioning.

5% probability of default × 100,000 exposure × 40% loss given default = 2,000 expected loss. That's the amount the lender should price into interest rate as a credit spread. If the lender charges less than this, they're expected to lose money on average. Charging more creates profitable credit portfolio, but only if PD estimates are accurate.

PD is the hardest input. Historical default rates vary by industry, credit rating, and economic cycle. Investment-grade corporate: 0.1-1% annual. Sub-investment grade: 3-10%. Consumer personal loans: 5-15%. Mortgage default rates typically 1-3% in normal times, 5-10% in recessions. Always use recent vintages for current PD, not long-run averages.

A worked example

Try the defaults: probability of default of 5%, exposure at default of 100,000, loss given default of 40%. The tool returns 2,000.00. You can adjust any input and the result updates as you type — no submit button, no reload. That's the real power here: seeing how sensitive the output is to one or two assumptions.

What moves the number most

The result responds to Probability of Default %, Exposure at Default, and Loss Given Default %. Not every input has equal weight. Flip one at a time toward extreme values to feel which ones move the needle most for your situation.

The formula behind this

Expected Loss = Probability of Default × Exposure at Default × Loss Given Default. Everything the calculator does is shown in the formula box below, so you can check the math against your own spreadsheet if you want.

What the score tells you

Headline financial numbers — income, savings, debt — each tell part of the story. This calculation stitches several together into a single read you can track over time. The value is in the direction, not the absolute number.

What this doesn't capture

The score is a composite of the inputs you provide. Life context — job security, family obligations, health, housing — doesn't appear in the math but shapes the real picture. Use the number as a prompt, not a verdict.