
Task | Manual Process | aiAutoPilot ML ® |
---|---|---|
Determine the performance of the current rules and models in the system and know where they are performing well or not | 10 minutes per rule | N/A |
Determine the best data filters to apply to detect as much fraud as possible whilst reducing the non-fraud data | 0.5 – 1 day | N/A |
Create machine learning rules and models using aiSmartScore and aiSmartRule from the filters | 1 day per run | N/A |
Put the rules and models into production | 1 day per run | N/A |
Can quickly and easily detect 80% of the fraud already being detected with a combined reduction in alerts
It can contribute to upwards of 20% reduction in fraud losses, compared with managing fraud manually
80% of the fraud analyst team can be applied to other business areas due to the vast reduction in alerts.
Produces highly effective rules, many suitable for immediate card blocking
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