10%
Of BHPH balances delinquent, Q3 2025, vs 3.8% traditional · Fed
16.6×
More likely to be in active repossession than a traditional loan · Fed
4-5 d
Median assignment-to-completion once repo is ordered · CFPB
27-38%
Share of repo assignments that ever complete · CFPB

Two curves, not one

The core identity is simple. Expected recovery on day d past due = net resale value(d) × probability of physical custody(d) − recovery costs(d). In buy-here-pay-here the asset is the loan and the collateral is the only real protection, so everything about repossession timing reduces to how those two curves move against each other.

They move at completely different speeds. Used vehicles are depreciating slowly right now, roughly 1% a month in 2026 wholesale data (Black Book and Manheim indices). The odds you ever get the car back are the fast term: they collapse the moment a delinquent borrower stops answering, lets insurance lapse, disables the GPS, and starts hiding the unit. The car is not the bleed. The custody probability is, and it is the term most operators never put a number on.

One denominator discipline matters here. Net resale value is what the unit itself would fetch at sale. It is deliberately not multiplied by an ABS-style loan-balance recovery rate, the 30s,40s percent figures lenders report measure recovery against the loan balance, a different denominator, and folding them in would double-count loss severity.

The slow term: what the car does

At the 2026 wholesale norm of ~1% a month, ninety days of delay costs a unit about 3% of its value from depreciation alone. The model adds a condition drag for wear, miles, and neglect while the car sits with a non-paying borrower, about 0.095% of value per day past due, capped at 14%. Even at a stress case of 1.5% or more a month, the vehicle side of the identity moves single-digit percentages over a full quarter. If that were the whole story, waiting would be cheap.

The fast term: the custody curve

Custody probability is modeled as a logistic slide from a high starting point down to a posture-dependent floor. The parameters below are the actual presets the model runs on, three borrower postures, each with a starting probability, a floor, a midpoint (the day past due at which half the slide has happened), and a steepness scale.

Borrower postureOdds at day 0FloorMidpoint of slideSteepness scale
Cooperative97%66%day 7815 d
Going quiet95%30%day 4610 d
Hiding it90%7%day 287 d
Modeled scenario priors, not measured rates. On top of the posture curve, each hard trigger present cuts custody odds a further 16% (multiplicative, capped at a 55% total penalty, with a 2% floor). GPS dormancy or device tampering escalates the file one posture worse automatically.

Read the "hiding it" row again. Half the slide is done by day 28, and the floor is 7%. On a concealed unit, a month of delay converts a near-certain recovery into a long-shot skip file, while the car itself has lost barely 1% of its value.

InferenceThe shape of these curves is the interpretive step, but it is anchored to a public pattern: CFPB repossession data shows capture is heavily front-loaded, a median of ~4-5 days from assignment to completion when it completes, yet only ~27-38% of assignments ever complete, and ~96% of completions land within 90 days. Repossession outcomes look bimodal. Either you secure the unit early, or the file drifts into a long tail where most assignments never convert. A steep early decay with a low floor is the curve that pattern implies.

The trigger ledger: stage the file vs repo now

The model does not treat days past due as the decision variable. Behavior is. Two tiers of signals govern the file's footing.

TierSignal
Hard · repo footingGPS shows the unit dormant 72h+ or out of the area
Hard · repo footingStarter-interrupt or GPS tampered with or disabled
Hard · repo footingInsurance lapsed, collateral now uninsured
Hard · repo footingPayment reversed / NSF and no contact since
Hard · repo footingBroke a second promise-to-pay
Hard · repo footingNo contact for 10+ days (skip behavior)
Soft · stage the fileMissed within the first 3 payments (early-payment default)
Soft · stage the fileFirst scheduled payment missed
Soft · stage the filePartial payment only
Soft · stage the fileBroke first promise-to-pay
Soft · stage the filePhone disconnected / mail returned
Soft · stage the filePaying later each month (deteriorating pattern)
The staging logic: any hard trigger puts the file on repo footing, dispatch if lawful, or serve the right-to-cure notice today and pre-stage the recovery agent if not. Two or more soft signals, or any early-payment default, means stage and serve: open the legal window now so a hard trigger becomes a same-day repo instead of a three-week scramble. One soft signal is a watch-close; log it and tighten contact.

The clock that gates all of this is legal, not behavioral. In the model, the cure notice goes out on day 10 past due, and the lawful repo day is that notice day plus the state and contract cure window. Some states allow repossession at default with no notice; others require a cure or notice period, on the order of ~10 days in Rhode Island and Maryland, ~15 in Pennsylvania, ~21 in Illinois. The lawful day is the best day the decay curve will ever offer, which is why the staging logic is built around reaching it pre-positioned rather than starting the process there.

The read Auction math tells you what the car is worth. Timing math tells you whether you will ever hold the car. Because custody probability collapses far faster than the vehicle depreciates, the recovery decision is won or lost in the days around the lawful gate, not at the sale. The operators who treat the cure notice as the start of the process, rather than the end of a staged one, pay the difference.

A worked example: the decay table

The table below runs the model end to end on a synthetic default file: an $8,500-net unit, 1.0%/month depreciation, "going quiet" posture with no hard triggers, cure notice served day 10, a 15-day cure window (lawful day 25), $875 in fixed recovery and disposal costs, and $25/day of holding cost from the notice day. Every figure is illustrative.

Day past dueUnit net valueCustody oddsCosts accruedExpected net recovery
Day 10 · notice served$8,39193%$875$6,952
Day 25 · lawful day$8,22988%$1,250$5,984
Day 40$8,06972%$1,625$4,182
Day 60$7,85743%$2,125$1,242
Day 90$7,54331%$2,875−$552
Day 120$7,23630%$3,625−$1,451
Synthetic and illustrative throughout. Note the columns: over 110 days the unit loses about 14% of its value, while the custody odds lose two-thirds of theirs. Past day 90 the expected recovery on this file is negative, the holding and recovery costs exceed what the collapsing odds are worth.
The waiting tax, days 25 to 60
On the synthetic file above, $5,984 of expected recovery is on the table on the lawful day. Holding to day 60 leaves $1,242 of it.
21% 79% forfeited by waiting Still recoverable at day 60 Same car, worse odds
Synthetic example, model output. Custody odds are modeled scenario priors, not measured rates.

The decomposition is the point. At 30 days past due on this file, the next 30 days of waiting cost the unit about 4% of its value, and cost the custody odds about 49% of theirs. Almost the entire waiting tax is the second term. Early custody also keeps the borrower's redemption and reinstatement options alive: in CFPB data, redemptions run ~22-34% of completed repossessions, and most happen within 30 days of the repo.

InferenceThe same CFPB data shows ~94% of disposals still end in a deficiency, meaning the sale of the unit rarely clears the balance, and the deficiency claim against a deep-subprime borrower is worth little in practice. If the recovered vehicle is, realistically, most of what a BHPH operator will ever collect on a defaulted loan, then the custody-odds curve is not one input among many. It is the loss model.

Limits

Honesty about what this method cannot see. The custody curves are priors, not measurements. No public source reports a daily custody probability by borrower posture, days past due, GPS status, or broken promises; the posture parameters and trigger penalties are calibrated to the directional CFPB and Fed findings, not fitted to an event-level repossession dataset. The structural claim, custody odds collapse faster than vehicle value, so timing beats auction math, is well supported. The exact coordinates are estimates that should be recalibrated against an operator's own repo history before any dollar figure is trusted. The ~1%/month depreciation figure is a market-wide wholesale index, not any particular lane or segment. The model ignores agent capacity, lot constraints, bankruptcy stays, and the economics of reinstatement. And the legal gate is state- and contract-specific: cure, notice, and self-help rules vary widely, and nothing here substitutes for confirming them in the relevant jurisdiction.

Sources & notes BHPH delinquency (10% vs 3.8%), the 16.6× active-repossession intensity, average origination ($15.4k) and APR (25.4%) are from the Federal Reserve's FEDS note on buy-here-pay-here lending (May 2026). Assignment-to-completion timing (median ~4-5 days), completion share (~27-38%), the 90-day completion concentration (~96%), redemption share (~22-34%, most within 30 days), deficiency incidence (~94% of disposals), and typical recovery costs (agent ~$500, disposal ~$300-350, forwarders adding ~$30-100+) are from CFPB auto-repossession data, 2022-2025. Wholesale depreciation near ~1%/month is from Black Book and Manheim index data. State cure and notice windows (e.g. RI ~10, MD ~10, PA ~15, IL ~21 days) are set by state statute and contract; see the companion note on state recovery law. The worked decay table, the split bar, and all custody-probability figures are synthetic and illustrative model output, not measured rates. LendRisk Analytics is an independent research publication with no position in, and no affiliation with, any company mentioned. Not investment, legal, or accounting advice.
Have a question about the market, or a different view? Send it through →.