Case Study | Predicting payment success in debt collection
| Sector | Debt collection |
|---|---|
| Products | cipher:collections |
| Application | Collections |
A great deal of time, resource and money is expended by debt collection agencies on building accurate propensity models that will predict payment rates across different types of debt. Those that get it right benefit from significant improvements in the cost effectiveness of their operations and an improved return on investment. Fraudscreen's Cipher coding solution is highly predictive of future payment intent, having analysed the historic payment behaviour of 17 million consumers across multiple retail organisations. In this case study, Fraudscreen demonstrates the predictive capability of this solution which can be used in isolation or as an enhancement to existing models.
