FICO publishes the percentage weight of each scoring factor — useful and under-known information. Five factors, in order: payment history (35%), utilization (30%), length of credit history (15%), new credit (10%), credit mix (10%). The interesting part: one underrated mechanic — letting unused cards close for inactivity — interacts with four of the five at once.

The short answer

Payment history 35%, utilization 30%, age 15%, new credit 10%, mix 10%. Top two = 65% of your score. The dormancy through-line: a single inactivity closure hits utilization, age, mix, and indirectly payment history all at once. Defending against it is the highest-leverage single action available.

Defend 4 of 5 factors → or jump to pricing

1. Payment history (35%)

The largest single factor. FICO is fundamentally a model of "will this person pay back debt." On-time payments are the strongest yes; late payments the strongest no.

What counts: every credit-card and loan payment, public records (bankruptcies, judgments, collections), charge-offs, foreclosures, repossessions. Each account has a monthly payment grid. One 30-day-late drops your score 50–100 points and stays on your report for 7 years. Recovery takes 12–24 months.

How to optimize: autopay the minimum on every account so an unintentional late never happens.

One action defends four of five FICO factors. ActiveCred runs a tiny authorized charge on every linked card monthly — prevents the inactivity closure that hits utilization, age, mix, and payment-history all at once. From $0.99/mo.
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2. Credit utilization (30%)

Percentage of available credit used. Total revolving balance ÷ total credit limit. FICO is non-linearly sensitive: 30% → 10% is a meaningful lift; 10% → 5% is smaller; 5% → 0% is mildly negative.

The dormancy connection is big: your denominator is the sum of credit limits across every open card, including ones you don't use. When an unused card gets closed for inactivity, its limit disappears from the denominator. Same spending, higher utilization, lower score.

How to optimize: pay down before statement close, spread balances across cards, protect every card from inactivity closure.

3. Length of credit history (15%)

Average age across all accounts, age of oldest, age of newest. Slow-moving lever — your average grows by exactly one year per year. Optimized mostly defensively: don't shrink it by closing old accounts or opening new ones unnecessarily.

The dormancy connection here is the most insidious. Closed accounts keep contributing to your average for 10 years after closure, then drop off. An inactivity closure today doesn't immediately reduce your average — but starts a 10-year clock that eventually does.

How to optimize: keep your oldest accounts open and active. Don't apply for new credit unless needed. Consider AU status on a family member's old card for thin files.

4. New credit (10%)

Hard inquiries and newly opened accounts. Each hard inquiry: 5–10 points temporarily, fading after 12 months, dropping off after 24. Each new account drops your average age and stacks an inquiry hit at the same time — a new application can be 10–20 points down for 6 months.

How to optimize: don't apply unnecessarily. Cluster applications you do make in short windows so the model treats them as one shopping event. Soft inquiries don't count.

5. Credit mix (10%)

Variety of account types. Revolving (cards), installment (auto, student, personal, mortgage), retail. Reward is small but real. Hardest factor to deliberately optimize — don't take out a loan you don't need just to improve mix; the cost exceeds the benefit.

Dormancy connection: closing a card narrows active mix slightly. If your remaining accounts are all installment loans, the score impact is mild but present.

The dormancy through-line

Notice that four of the five factors interact with whether your cards stay open and active:

  • Payment history — an unused card with autopay continues building positive history. A closed card stops.
  • Utilization — open cards contribute to the denominator. Closed cards don't.
  • Length of history — open cards keep aging. Closed cards age toward the 10-year drop-off.
  • Credit mix — open cards contribute to active diversity.

The single behavior that touches four of five factors: keep your existing cards alive. The bank's inactivity-review system closes cards that don't see regular activity. Each closure compounds across these four factors. A small monthly activity layer defends all of them at once.

What to optimize first

  1. Autopay on every account — defends payment history (35%)
  2. Pay down before statement close — improves reported utilization (30%)
  3. Activity layer on every unused card — defends utilization denominator, account age, and mix (55% combined)
  4. Stop applying unless necessary — avoids new-credit drag (10%)
  5. Wait for length-of-history — only time fixes this
  6. Let mix develop naturally — don't force it

The first three are high-impact. The rest is discipline.

Why dormancy is the strongest motivational angle

Most optimization tactics target one factor. The dormancy-prevention move is unique: it defends four at once. That's why, in terms of points-defended-per-dollar-spent, it's the hardest move on the list to beat. Most people don't think about it until after a card has already closed and the score has already moved. The fix takes years to undo. The prevention takes minutes to set up.