Home ⇒ Early Stage Collections
Early Stage Collections
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Know which accounts have the highest probability of going
or loss, proven through a back test validation on your portfolio, to
focus collection efforts on accounts with the most impact on cash flow.
Client determines bad definition.
Improve customer satisfaction by not working accounts that will “self
Use validated dollars at risk to improve collection process efficiency
and effectiveness in making economic based decisions, reducing collection
Leverage your internal performance data, which is the most predictive
data for this type of model, it’s readily available, it’s free, and you
can score all accounts (no bureau no-hits).
Multifunctional: Collection strategy prioritization, credit/lease line
management, control risk of repeat transactions with existing customers,
and calculating bad debt reserves.
MedicalCollectionScoreSM - Score patients from “day one” after treatment, late stage delinquency, charge-offs and accounts placed for collection through tertiary and beyond. Net30ScoreSM – Commercial (B2B) portfolio management model for credit and collections that predicts the probability that a GOOD paying customer will become BAD at some point during the next six months for trade credit, primarily Net/30, 10-day terms, but can be adapted to handle almost any terms.
UtilityScoreSM – Portfolio management model designed for collection prioritization and determination of deposits. The model predicts the probability that a GOOD paying customer will become BAD at some point during the next six months for residential and industrial and commercial accounts for electric, gas, water, and telecommunications companies.ScoreMinerSM - Web-based credit and collection scoring, data mining, report and query system that leverages the predictive power of PredictiveMetrics’ industry/finance specific and custom portfolio scores. Customers use ScoreMiner’s various filtering and reporting capabilities to review and analyze information, to measure credit and collection performance and provides detailed information and graphical analysis by risk class and credit risk change over time.