Act faster than fraudsters with real-time Fraud Detection
In 2024, financial losses from fraud reached record levels, with consumers in the US alone reporting over $12.5 billion in losses, a 25% increase from the year prior. Globally, scams pilfered over $1.03 trillion. This magnitude of crime makes it blatantly clear that current fraud detection systems are no match for modern-day criminals.
Current fraud detection systems rely on data collection and aggregation across multiple channels as the first step in identifying fraudulent activities. Once data is collected, well-engineered features are required to make predictions and identify patterns, by creating attributes commonly associated with fraudulent activity. After this, model training and validation takes place. Models are trained on an initial data set to learn patterns and relationships, and are then exposed to a validation dataset, different from the training data, used to assess the model’s performance.
Fraud is behavior
Fraud detection functions on the premise that fraud is an anomaly indicated by a change in behavior. The problem with current fraud detection systems is that, even if models are rigorously trained, fraudsters often move faster than models can adapt. Businesses need mechanisms that can both intervene when fraudulent activities occur in real-time, as well as correctly identify vulnerabilities and act pre-emptively.
In terms of recognising and understanding behavior, and changes thereof, the ecosystem.Ai Prediction Platform is backed by pre-configured modules such as Interaction Science, which automatically enrich features with deep behavioral insights. Understanding the difference between fraud and a simple act of impulsivity sits at the centre of behaviorally-informed fraud detection.
Our Fraud Management Module combines capabilities such as real-time scoring, real-time learning, graph-based network strategies to detect coordinated crime, and generative explanations to assist human-led investigations.
Fraud detection systems need to get smarter with the fraudsters they are up against. A revised approach to fraud detection is essential to immunise your business from becoming part of the statistics.
