aiAutoPilot ML®
Automatically optimise your fraud strategy with an advanced, machine learning-powered capability.
- Optimise fraud detection performance
- Automated strategy change recommendations
- Single-click strategy updates
Smarter fraud detection,
less effort
aiAutoPilot ML® revolutionises fraud management by optimising fraud strategies, saving fraud analysts hours of manual work. Fraud patterns are analysed daily, and tailored recommendations are made to enhance detection accuracy.
By refining strategies based on real-time fraud trends, aiAutoPilot ML® boosts operational efficiency and ensures fraud teams stay ahead of evolving threats. With single-click integration into aiRiskNet®, fraud managers can quickly implement AI-driven updates, allowing your team to focus on other strategic projects.
Key features
Daily fraud strategy
New rules and model options are automatically generated, along with removal recommendations for underperforming rules.
Single-click strategy updates
Fraud managers can instantly apply strategy changes via the aiRiskNet® API, ensuring that the fraud strategy remains agile and current with the latest trends.
Automated fraud strategy optimisation
aiAutoPilot ML® takes the complexity out of managing fraud detection by automating the evaluation and selection of the most effective rules and models. With roughly 10 minutes of manual input daily, fraud managers receive optimised strategy updates.
Continuous model and rule creation
New models and rules are developed and tested as soon as new fraud data is available.
Performance monitoring
Constant assessment of live model and rule effectiveness ensures new strategy recommendations remain optimal.
Secure API connectivity
Seamless integration with aiRiskNet® allows single-click strategy changes.
Full audit trail
A complete record of all interactions provide accountability and transparency.
Choose aiAutoPilot ML®
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Automation
aiAutoPilot ML® takes care of fraud strategy maintenance by ensuring all rules and models are optimised for the current fraud activity. aiAutoPilot ML® suggests new machine learning-generated rules and models whilst identifying underperforming rules for removal. -
Optimisation
aiAutoPilot ML® optimises all rules and models for the best-performing strategy - leading to a reduction in rules, false positives and increased fraud detection. -
Effective Detection
Produces highly effective rules, many suitable for immediate card blocking. -
Operational Efficiency & Cost Saving
Increases efficiency by reducing the number of alerts, enabling fraud analysts to focus on complex cases.
Implement a fraud strategy within minutes
A process that usually takes days manually, is implemented automatically with aiAutoPilot ML® in minutes.
- Determine the performance of your current rules and models in the system and know whether they are performing well.
- Assess the best data filters to detect as much fraud as possible whilst minimising data noise.
- Automatically create machine learning rules and models from the filters.
- Deploy rules and models into production immediately if they are approved.
| Task | Manual Process | aiAutoPilot ML® |
|---|---|---|
| Determine the performance of your current rules and models in the system and see whether they are performing. | 10 minutes per rule | N/A |
| Determine the best data filers to apply to detect as much fraud as possible whilst reducing the non-fraud data. | ½ - 1 day | N/A |
| Create machine learning rules and models using aiSmartScore and aiSmartRule from the filters. | 1 day per run | N/A |
| Deploy the rules and models into production. | 1 day per run | N/A |
The aiAutoPilot ML® process
aiAutoPilot ML® monitors fraud data in real-time, using machine learning to assess fraud patterns, trial new models, and produce strategy recommendations daily. With a streamlined, API-enabled integration with aiRiskNet®, fraud managers can implement these recommendations instantly.
- Discover – An extensive data assessment will occur, to understand where the fraud is coming from.
- Build models – The machine will automatically build new machine learning models to solve the fraud problem
- Optimise – The best combination of rules and models are identified, to ensure optimal fraud strategy performance
- Go Live! – aiAutoPilot ML® will put your new strategy into production