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Debt collection glossary

What is a collectability score?

A predictive score estimating the likelihood and expected amount of recovery on an account, used to prioritize collection effort.

Definition

A collectability score is a model-generated estimate of the probability that an account will pay, and often the expected recovery amount, derived from attributes of the debt (type, age, balance, stage), the debtor (contactability, payment history, credit signals where permissible), and behavior (response to prior outreach, portal visits, partial payments). Scores update as new information arrives.

Scoring replaces the traditional approach of working accounts by balance size or due date. Effort shifts toward accounts where contact will change the outcome, while low-probability accounts get low-cost automated channels and high-probability accounts get a payment link rather than a phone call.

Example

Two $2,000 accounts arrive the same day. One debtor opened a prior email and visited the portal; the other has a disconnected phone and returned mail. The first scores 0.71 and receives a payment plan offer by text; the second scores 0.12 and is routed to skip tracing before any outreach.

How HL Hunt handles it

HL Hunt scores every account continuously and uses the score to drive channel, timing, offer, and escalation. Scores never use prohibited factors, and the attributes used are documented for fair lending and UDAAP review.

Frequently asked questions

Does a collectability score use credit bureau data?

It can, under permissible purpose, but HL Hunt's core model works primarily on debt attributes and observed behavior, with bureau data optional.

Can scoring create fair lending risk?

Scoring must not use protected class or proxy variables. HL Hunt excludes them and provides documentation of model inputs for compliance review.

How is a collectability score different from a credit score?

A credit score predicts future default on new credit. A collectability score predicts recovery on an existing delinquent account and incorporates collection-specific behavior.

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