Automated decisions at Eleev

FIRE Probability

What it does

Monte Carlo simulation of your "Financial Independence / Retire Early" plan. Estimates the probability that your portfolio survives a multi-decade retirement based on random market scenarios.

Inputs it uses

• Current age and retirement age
• Current portfolio balance + ongoing contributions
• Expected mean return and volatility (you set these — defaults are educational, not predictions)
• Inflation rate (defaults to trailing 5-year Canadian CPI)
• Retirement spending target (annual, today's dollars)
• Optional: CPP/QPP estimate, OAS estimate, retirement age for government benefits
• The goal you picked, if any, which sets the withdrawal order and the CPP/QPP and OAS start ages (see Retirement goal search)

How it computes

Runs 1,000 random market paths per simulation. Each path applies a year-by-year random return drawn from a normal distribution defined by your mean + volatility. Result is the percentage of paths where your portfolio lasts to your plan-to age. Inputs, returns, and probabilities are visible — nothing is hidden in a "black box" model. When you pick a goal, the withdrawal order and the CPP/QPP and OAS start ages come from the search described under Retirement goal search; otherwise they are the ones you set.

How to read the result

The probability is a statistical artifact of your inputs, not a forecast of your actual future. A 90% number does NOT mean "90% chance you'll succeed in real life" — it means "90% of the 1,000 random paths under your assumptions held up." Real markets are not normally distributed (fat tails, regime shifts, correlation breakdowns). Use the number to compare scenarios (e.g. "saving 5% more lifts probability from 70% to 85%"), not to make a binary go/no-go decision.

Drawdown Probability

What it does

Monte Carlo simulation of a retirement drawdown strategy (TFSA-last, RRSP-meltdown, OAS-buffer, or a custom mix). Estimates the probability of meeting your spending target without depleting the portfolio over your plan horizon.

Inputs it uses

• Starting balances per account type (TFSA, RRSP/RRIF, non-registered)
• Annual after-tax spending target (today's dollars)
• Plan-to age (typically 90-100)
• Expected mean return and volatility (per asset class if customized)
• Inflation rate (defaults to trailing 5-year Canadian CPI)
• CPP/QPP + OAS start ages and amounts
• Drawdown strategy choice (TFSA-last / RRSP-meltdown / OAS-buffer)
• The goal you picked, if any, which sets the withdrawal order and the CPP/QPP and OAS start ages (see Retirement goal search)

How it computes

Runs 1,000 random market paths per simulation. Each path applies year-by-year random returns, real-dollar government benefit indexing, RRIF minimum withdrawal mandates from age 72, and the chosen drawdown ordering rule. Tax is computed using Canadian + provincial brackets including the marginal-rate cap to prevent silent advice-shaped recommendations. Result is the percentage of paths where the portfolio outlasts the plan horizon AND meets the spending target each year. When you pick a goal, the withdrawal order and the CPP/QPP and OAS start ages come from the search described under Retirement goal search; otherwise they are the ones you set.

How to read the result

Same statistical caveat as FIRE: the probability is a function of your inputs, not a prediction. Use it to compare strategies side-by-side ("TFSA-last vs RRSP-meltdown under MY parameters") — that is the strongest signal the tool produces. Absolute probabilities should be read as "this plan is fragile / solid / strong" — not as a precise life-outcome forecast.

Financial Health Score

What it does

Composite 0-100 score derived from up to 6 personal-finance vitals (savings rate, emergency cushion, non-mortgage debt, retirement progress, investment fees, diversification). Each vital is scored against common planning benchmarks; the composite is a weighted average of available vitals.

Inputs it uses

• Annual gross income
• Monthly expenses
• Emergency cash on hand
• Non-mortgage debt total
• Retirement savings to date
• Optional (signed-in only): portfolio diversification metrics; the portfolio fee weighted average additionally requires the Pro tier (Fee Analysis)

How it computes

Each vital scores 0-100 against a hard-coded planning benchmark (e.g. 15%+ savings rate = 100, 3-6 month emergency cushion range, 4% retirement withdrawal target). The composite is a weighted average of available vitals: diversification carries a reduced weight of 0.75, the other five carry 1, and missing inputs are excluded from both numerator and denominator. No machine learning, no external lookup; algorithm is in client-side TypeScript and fully visible in the public source. The public /score page also lets you change any of the five answers after the score appears and watch the result recompute. That runs the same algorithm on different inputs: nothing about the calculation changes, and nothing you try there is stored, sent to us, or counted as a result. With an account, the Financial Health tool runs the same algorithm on the numbers saved in your profile and portfolio.

How to read the result

The score is a snapshot relative to common planning rules of thumb — NOT a comparison to other Eleev users or a credit-score-like grade. A 60 means "your inputs sit roughly in the middle of common planner ranges," not "you are worse than 40% of users." Use the composite as a directional signal and the per-vital breakdown to see which specific area moves the needle most.

Rent vs Buy Verdict

What it does

Compares buying a home against renting and investing the difference, across three ownership scenarios (buy-to-live, buy-and-rent-out, or already-own and sell). Produces a break-even year and a net-worth comparison over the horizon you choose.

Inputs it uses

• Home price, down payment, mortgage rate and amortization
• Property tax, maintenance, insurance, and other carrying costs
• Rent and its expected annual increase
• Expected home appreciation and investment return (you set these — defaults are educational, not predictions)
• Which scenario you're comparing (buy-to-live / buy-and-rent-out / already-own)
• For the rental scenario: monthly rental income, the share of the home you occupy, and whether the rented unit is self-contained or CCA was claimed

How it computes

Projects both paths year by year over your chosen horizon: the buy path accrues mortgage paydown, appreciation, and carrying costs; the rent path invests what buying would have cost instead, net of rent. For the rental scenario, net rental income (rent minus its prorated share of deductible expenses) is added to the buy path, and a resale gain is computed using the Canada Revenue Agency's mixed-use property rule (Folio S1-F3-C2): the rented share of any gain is taxable only if the unit is self-contained or CCA was claimed — otherwise the sale stays fully tax-free. Every formula is deterministic (no simulation, no randomness) and visible in the tool itself; the same inputs always produce the same output.

How to read the result

The comparison depends entirely on the numbers you enter — appreciation, rent growth, and investment return are assumptions, not predictions, and a small change to any of them can move the break-even year by several years. Use it to see how sensitive your own numbers are, not as a single verdict to act on. For the rental scenario specifically, whether a resale gain is taxable depends on a real tax classification (self-contained unit or CCA claimed) that only you — or a tax professional — can confirm for your actual property.

Retirement goal search

What it does

When you pick a goal (leave the most, or spend more), Eleev tests your retirement plan with every withdrawal order and every start age for CPP/QPP and OAS. It keeps the combination with the best result for that goal. That combination becomes the order and the ages of your plan when you answer the goal question, or when you press Use under a goal in the comparison. It stays until you change one of them yourself in Detailed. In Detailed, a plan saved before goals existed keeps the order and start ages you had changed, until you press Use.

Inputs it uses

• Your balances by account type, your spending, return, inflation, plan-to age and province
• Your CPP/QPP contributory years and any other income you entered (a pension, a locked-in account, rental, work, an annuity)
• The goal you picked

How it computes

No random draws and no machine learning: the same inputs always give the same result. For each goal, Eleev tries two withdrawal orders (TFSA last, RRSP first), CPP/QPP starting between 60 and 70 (72 for QPP) and OAS starting between 65 and 70, counting from your age today. A combination that runs out of money before your plan-to age is left out. The combination with the highest number is shown. If two give exactly the same number, the one with ages closest to 65 wins, then TFSA last. For "leave the most", the number is what is left after tax at your plan-to age. For "spend more", Eleev finds the largest yearly amount, to the nearest $10, that your plan can pay until the plan-to age.

How to read the result

The result is arithmetic on your numbers under the rules above. It is not a recommendation of an order or a start age. It leaves out your health, a spouse, future changes in the law and the markets. The Probability tab shows how fragile a plan is under random markets; this search does not.

Eleev provides information and modeling tools for personal use — not personalized financial, tax, or legal advice. For decisions that commit your money, consult a professional registered with your provincial regulator (AMF in Quebec, OSC elsewhere). See also our privacy policy.