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Multifamily Bad Debt Calculator

Bad debt benchmarks vary 1–5% by class and operator collections discipline.

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Total bad debt

$178,200

Bad debt %

0.03%

Skips loss

$64,800

How the math works

Bad debt = GPR × (skips + evictions + write-offs).

$5.4M × (1.2% + 1.5% + 0.6%) = $5.4M × 3.3% = $178,200 bad debt.

How to Use

  1. Enter gross potential rent.
  2. Enter skips %.
  3. Enter eviction loss %.
  4. Enter other write-offs %.
  5. Read total bad debt.

Frequently Asked Questions

Bad debt benchmarks?

Class A urban: 0.8–2.0% bad debt. Class B suburban: 1.5–3.0%. Class C affordable: 2.5–5.0%. Includes: skips (move-out without paying), evictions (collected as much as possible during process), payment plan defaults, write-offs. Drivers: screening discipline, collections process, eviction timeline (state varies 30–180+ days). Best operators: weekly collections call, automatic late fee + lease violation cycle, partial payment policies. AI risk scoring (TransUnion, Experian RentBureau) reduces bad debt 20–35%.

How does this support multifamily underwriting?

Multifamily acquisition and operations teams use this calculator alongside rent roll, T-12 P&L, expense ratio benchmarks, and comp set rents. Pair with a unit-level upside model and concession reconciliation. Sensitivity testing on rent growth, expense growth, and exit cap is essential — small changes compound on stabilized NOI and IRR.

Class A vs B vs C variance?

Class A: newer construction, premium amenities, higher rents but lower yield, lower expense ratio (~35–45%). Class B: 1990s–2000s build, value-add target, mid yield, expense ratio 40–50%. Class C: 1970s–1980s, deep value-add or workforce, higher yield but higher expense ratio (45–60%) and capex burden. Adjust assumptions to class.

When does this metric actually move the deal?

Single-line items rarely change a deal materially, but stacked operational improvements compound. A 3% rent increase + 1.5% expense reduction + 50 bps cap compression = 25–40% IRR uplift over 5 years. Use this calculator alongside others in the operations stack to identify the best 3–5 levers to focus on post-close.

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