Recovery

How time and resources, not to mention money, do you spend on an account that doesn’t pay or pays very little? Margins are slim. Your time, money, and collection success are very valuable attributes to your bottom line. Don’t waste them; optimize them by using a custom Recovery Scoring Model developed by PredictiveMetrics (PMI).

PMI has introduced a new recovery scoring application that is proven to increase liquidation rates and reduce costs. PMI recovery models utilize actual payment performance data, of charged-off bad debt, and apply statistical analysis to develop a validated score. Internal performance data is proven to be a much more powerful predictor of recovery than models based merely on external bureau data, because the information is specific to the charged-off debt in the portfolio.

This automated predictive decision system is designed to rank order and segment recoveries enabling you to employ different collection strategies based upon cost and/or impact. PMI applies statistical analysis in the form of a multivariate non-linear regression model to estimate the probability of payment and collection amount. The model leverages internal accounts receivable / placement data as well as collection performance and socio-economic / demographic data supplied by PMI.


Furthermore, the recovery model can be used as part of the due diligence process in buying portfolios.

Recovery Scoring Models can be easily implemented on PMI’s system, which reduces IT implementation time, resources, and costs. PMI can also provide technical specifications to implement the model on your system. We work closely with your IT department to ensure proper model implementation.

Benefits of Recovery Scoring Models

• Maximize liquidation rates by using a dollar and payer score to prioritize collections
• Reduce collection costs and collection time
• Optimize the use of valuable resources
• Produce an effective evaluation tool for portfolio pricing by accurately determining overall collectability