Fraud detection

Context

Every year, fraud can cost your company several hundred thousand euros. And that’s not to mention the negative impact it can have on your brand image.

Because dealing with fraud is an essential part of being competitive, you’ve decided to handle it internally.

Every day, your teams of data scientists work on analyzing suspect behavior, detecting weak signals and creating models to produce effective algorithms.

Their aim is to:

  • Detect suspect behavior as early as possible
  • React as quickly as possible
  • Improve your operational performance

Challenges

  • Designing an algorithm is only part of the solution. You then need to implement and deploy it. And to undertake this, you first need to build a complete technological environment.

  • The real challenge is to successfully manage the multitude and interrelationship of different functional layers.

  • How can you ensure you maintain the intellectual property of your machine-learning algorithm – and the fruits of its learning?

In practice, this means long, complex projects that use multiple expert resources and are extremely costly.
Your data science teams will work for months or years and clock up millions of euros in expenses before they can deliver the first benefits for your company.

The ForePaaS Solution

With ForePaaS, you can optimize your algorithms for detecting fraud

  • Thanks to full platform automation, ForePaaS allows you to capitalize on your data science processes in record time
  • Maintain ownership of your intellectual property: by internalizing your algorithms, you’ll ensure your competitors are denied access to your sector-specific solution

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