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Tools

Standalone calculators and interactive widgets. Bookmark this page — these are the same widgets embedded in the lessons, pulled out so you can use them without scrolling.

Expected Loss Calculator

The master equation of credit risk: EL = PD × LGD × EAD. Move the sliders to see how each component drives the result. From Module 1.

Expected Loss Calculator
Expected Loss $900

FICO Score Simulator

The five FICO components at their published weights, mapped onto the 300–850 range. A pedagogical simplification (the real model is segmented, not linear) — see Module 2 for the honest caveats.

FICO Score Simulator

Each slider represents how strong that part of a credit file is, from worst (0) to best (100). Weights are FICO's published component weights.

Simulated score 712 / 850
Band Good
300580670740800850

Altman Z-Score Calculator

Paste in raw financials and get all three Altman variants — original Z, Z′ for private firms, Z″ for non-manufacturers and emerging markets — with zone interpretations. The disagreements between them are as instructive as the scores. From Module 3.

Altman Z-Score Calculator

Enter figures from the balance sheet and income statement. Units don't matter (thousands, millions, pesos, dollars) as long as they're consistent — every input enters through a ratio.

Z — original 1968, public manufacturers
– –
Z′ — 1983, private firms (book equity)
– –
Z″ — 1995, non-manufacturers & emerging markets
– –

Zone cutoffs — Z: distress < 1.81, grey 1.81–2.99, safe > 2.99 · Z′: distress < 1.23, grey 1.23–2.90, safe > 2.90 · Z″: distress < 1.10, grey 1.10–2.60, safe > 2.60.

Yield Curve Builder

Set the policy rate, the expected long-run rate, the speed of convergence, and a term premium — and watch the yield curve take shape, expectations component and full curve side by side. From Module 4.

Yield Curve Builder

A yield is the average short rate the market expects over the horizon, plus a term premium. Set the policy path and the premium — the curve follows.

12% 9% 6% 3% 0% 0y 2y 4y 6y 8y 10y expectations only full curve (with premium)
1y yield –
10y yield –
Slope (10y − 1y) –
Shape –

Bond Price Explorer

Coupon, maturity, and yield in; price, Macaulay and modified duration, DV01, and convexity out — with the price-yield curve and its duration tangent drawn live. From Module 5.

Bond Price Explorer

Price is present value; duration is the slope of the price-yield curve; convexity is the bend. The dashed line is what duration alone predicts — the gap is convexity working for the holder.

– – – – – 0% 3.75% 7.5% 11.25% 15% price-yield curve duration approximation
Price (per 100) –
Macaulay duration –
Modified duration –
DV01 (per 100) –
Convexity –

Merton Model Explorer

Equity as a call option on the firm's assets: adjust asset value, volatility, leverage, and maturity to see the risk-neutral PD, distance to default, and implied credit spread respond. From Module 6.

Merton Model Explorer

A firm with asset value V owes a single zero-coupon debt payment D at maturity T. Default happens if assets are worth less than the debt when it comes due.

Risk-neutral PD –
Distance to default (d₂) –
Credit spread –
Equity value E –
Debt value B = V − E –
Leverage D·e⁻ʳᵀ / V –

Hazard Rate Simulator

Default as a surprise with intensity λ: survival curves under flat, rising, and falling hazard term structures, plus the credit-triangle CDS spread. From Module 7.

Hazard Rate Simulator

Default arrives as a surprise with intensity λ. The survival curve is S(t) = exp(−∫₀ᵗ λ(s) ds) — watch how its shape changes with the level and slope of the hazard.

100% 75% 50% 25% 0% 0y 2y 4y 6y 8y 10y
1-year PD –
5-year cumulative PD –
CDS spread ≈ λ(1−R) –

Transition Matrix Explorer

Apply a stylized 1-year rating transition matrix N times and watch the rating distribution spread and the cumulative default probability compound. From Module 8.

Transition Matrix Explorer

Start a bond at a rating, apply a stylized 1-year transition matrix N times (illustrative long-run averages, not any agency's published data), and watch where the rating distribution goes.

Cumulative PD by horizon –
Still at starting rating –
Investment grade (BBB−+) –

CAMELS Scorer

One headline ratio per CAMELS component, scored 1–5 with a mechanical composite — the intuition version of how supervisors grade banks. From Module 9.

CAMELS Scorer

One headline ratio per component, scored 1 (strong) to 5 (critically deficient) on illustrative thresholds. Real examiners use many metrics per component plus judgment — this is the intuition version.

Mechanical composite –
Component average –
Reading –

WOE Binning Explorer

Move the bin edges on a synthetic utilization variable and watch each bin's Weight of Evidence and the total Information Value respond — the binning trade-offs of scorecard construction, live. From Data Science Module 2.

WOE Binning Explorer

A synthetic portfolio where higher utilization means more defaults. Move the four cut points and watch each bin's Weight of Evidence and the total Information Value respond.

Bin Pop. share Bad rate % goods % bads WOE IV contrib.
Total Information Value –
Diagnostics –

Portfolio Loss Distribution (Vasicek)

The closed-form loss distribution behind the Basel IRB formula: same PD and LGD, different correlation — watch expected loss stay put while the tail transforms. From Module 10.

Portfolio Loss Distribution (Vasicek)

An infinitely granular portfolio where every borrower loads on one common factor. Same PD and LGD, different correlation — watch the tail.

EL VaR
Expected loss –
Loss VaR –
Capital (VaR − EL) –
Reading –

Copula Simulator

Two borrowers, 2,000 simulated years, three copulas. Same correlation, different tail dependence — the joint-default corner tells the 2008 story. From Module 11.

Copula Simulator

Two borrowers, 2,000 simulated years. Each point is a year; the red corner is both defaulting. Same correlation, different copulas — watch the corner.

Borrower 1 (uniform scale — low = bad year) Borrower 2
Joint defaults observed –
If independent (PD²) –
Tail multiplier –

Feature Attribution Explorer

A glass-box additive credit model with a SHAP-style waterfall and auto-generated adverse-action reasons. From Module 12.

Feature Attribution Explorer

An additive credit model, opened up: each feature contributes log-odds relative to the average borrower (baseline PD 4%). Red pushes toward default, green away.

← safer (log-odds contribution) riskier →
Baseline PD 4.0%
This borrower's PD –
Top adverse-action reasons (auto-generated) –

Classification Metrics Explorer

Two score distributions, a threshold, and a base-rate slider — AUC, Gini, KS, and the accuracy lie, computed live. From Data Science Module 4.

Classification Metrics Explorer

Goods score low, bads score high (two Gaussians). Move the separation, the cutoff, and — the punchline — the base rate.

Score distributions goods bads ROC curve false positive rate KS = max gap
AUC –
Gini –
KS –
Accuracy –
Precision –
Recall –

PSI Drift Meter

Shift, widen, or contaminate a live population against its development baseline and watch the Population Stability Index cross its thresholds. From Data Science Module 6.

PSI Drift Meter

Outline bars: the population your model was built on (frozen). Solid bars: today's applicants. PSI measures how far today has walked away from development.

score deciles (development-time bins)
PSI –
Status –
Worst bin –

Convention: PSI < 0.10 stable · 0.10–0.25 monitor closely · > 0.25 material shift, investigate before trusting the model.

Beta-Binomial PD Explorer

Low-default PD estimation done honestly: prior, data, posterior, and the credible interval — including why zero observed defaults never means PD = 0. From Data Science Module 7.

Beta-Binomial PD Explorer

Estimating a PD from a portfolio that rarely defaults. Dashed curve: what you believed before the data. Solid curve: what you should believe after.

MLE
MLE (k/n) –
Posterior mean –
90% credible interval –
Reading –

Budget Allocator

Your planned spending per category against the recommended percentage ranges, with the 50/30/20 rollup and a "left to assign" check. From Personal Finance Module 1.

Budget Allocator — % vs. Recommended Ranges
Needs — guide: ≤ 50%
Wants — guide: ~ 30%
Savings & extra debt payoff — guide: ≥ 20%
Left to assign — aim for exactly $0

Sinking Fund Planner

Target minus saved, divided by months — the monthly set-aside that turns annual bills into line items. From Personal Finance Module 2.

Sinking Fund Planner

Money you set aside monthly for expenses that don't arrive monthly. Edit anything.

Fund Target $ Saved so far Months away Monthly set-aside
Total monthly set-aside — this is your budget's "planned savings transfer" $0

Net Worth Calculator

Assets minus liabilities, with the AFORE included where it belongs. From Personal Finance Module 3.

Net Worth Calculator
Assets (what you own)
Liabilities (what you owe)
net worthowed to others
Total assets —
Total liabilities —
NET WORTH —

Debt Payoff Simulator

Avalanche vs. snowball, simulated month by month with rolling minimums — see what the difference actually costs. From Personal Finance Module 4.

Debt Payoff Simulator — Avalanche vs. Snowball
Debt Balance Annual rate % Minimum payment
AVALANCHE — highest rate first — total interest: —
SNOWBALL — smallest balance first — total interest: —

Retirement Calculator

Your number (25× rule at an adjustable withdrawal rate), the years to reach it at your savings rate, and the growth curve crossing the target. From Personal Finance Module 5.

Retirement Calculator — How Much, How Long, and How Long It Lasts

Enter nominal returns and inflation — the calculator converts to real returns, so every result is in today's money. The retirement-phase return is lower on purpose: once you live off the portfolio, you move it somewhere safer.

Getting there
Your number (portfolio needed) —
Years until you reach it —
Desired retirement spending — per month, in today's money
Living from it — the portfolio keeps earning in retirement
Interest alone pays you —
Years it lasts at your spending —
Capital left after 30 years retired —

The whole lifecycle: the green curve climbs to your number while you save, then retirement starts at the dashed marker. From there, the solid orange curve spends your desired amount while the rest keeps compounding at the safer return (eating capital), and the dashed green line lives on interest alone (capital intact forever).

Fee Drag Comparator

The same portfolio compounded under two expense ratios — why 0.03% vs. 1.75% is not a rounding error. From Personal Finance Module 6.

Fee Drag — What an Expense Ratio Really Costs
Fund A (low fee)
—
Fund B (high fee)
—
The fee difference costs you —

Rental Yield Calculator

Gross yield, cap rate, and — with a mortgage — cash flow and cash-on-cash, including the negative-leverage warning. From Personal Finance Module 7.

Rental Yield Calculator
Gross yield — annual rent ÷ price
Net yield (cap rate) — NOI ÷ price
NOI / month — after vacancy & expenses
With a mortgage? (leverage)
Mortgage payment / month —
Cash flow / month —
Cash-on-cash return — annual cash flow ÷ cash invested

That's the full set — every interactive widget from all three tracks, in one place. If a lesson's widget is missing here, it lives embedded in its module instead (the time-series, backtesting, and confounding demos make more sense in context).