Published on: 2024-08-10 18:35:48
Debt collection specialists in the analytical field play a vital role in predicting the likelihood of recovery and optimizing collection strategies. One useful tool for achieving this is a collections scorecard. In this article, we will outline how to build a comprehensive collections scorecard that accurately predicts the probability of recovery.
I. Variables and Data Types
A. Collection Behavior Data
- Number of phone calls made in the last 1, 2, and 3 periods
- Total number of phone calls made
- Number of phone calls connected in the last 1, 2, and 3 periods
- Total number of phone calls connected
- Connection rate for the last 1, 2, and 3 periods
- Pverall phone connection rate
- Number of days lost contact in the last 1, 2, and 3 periods
- Total days lost contact
- Number of valid friends
- Number of valid contacts
- Average call duration per call
- Total call duration
- Total number of call backs
- Total collection messages sent
- Total number of collectors involved
- Total number of collection letters sent
B. Customer Personal Information
- Age
- Gender
- Occupation
- Education
- Monthly income
- Marital status
- Housing situation
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