Case Study | Predicting fraudulent claims for goods lost in transit
| Sector | Home shopping |
|---|---|
| Products | cipher:risk |
| Application | Risk/claims |
The losses associated with goods lost in transit can be substantial, as is the impact on internal resources required for their careful investigation. Making a quick and accurate decision on the claim is essential for reducing bad debts and retaining customer loyalty. The current financial pressures on consumers have resulted in a rise of this type of first party fraud - claiming that goods bought were never delivered or claiming a refund on goods supposedly returned. In this example for a major home shopping business, Fraudscreen demonstrated how its solution could accurately predict which claims were most or least likely to be fraudulent.
