Case Study | Improving risk assessment for payday loans
| Sector | Payday loans |
|---|---|
| Products | cipher:risk |
| Application | Credit risk |
With many more households now struggling to make ends meet, more and more of them are turning to payday loans to get them through to the end of the month. But these same pressures have also driven a rise in first party fraudulent behaviour, with consumers intentionally entering financial agreements with no intention of meeting their obligations. Predicting these intentions can enhance scorecards where credit bureau data is used, especially when applications are received from sub-prime consumers with little credit history. For lenders not using credit bureau data, the insight provided by Fraudscreen can offer a cost effective alternative that leaves no credit foot-print. This case study, for a well known payday lender, shows how Fraudscreen was able to accurately predict which customers were most or least likely to default, despite having passed a credit check. The analysis was used to add a new level of insight to the existing scorecards, refining accept/decline decisions.
