How to take a holistic approach to combating generative AI fraud
Building an end-to-end fraud strategy ensures a robust defense against GenAI fraud and future threats.
The 4 pillars of a holistic fraud strategy
Leverage a comprehensive suite of signals and evidence
Collect a wide array of data points and evidence such as user behavior analytics, device identification, identity proofing evidence, and verification data to develop a nuanced understanding of a user's risk profile.
Surface more insights by combining data
No single provider or model can handle all fraud vectors. Use each risk signal collected in order to create an ensemble model - a combination of different models, signals, and algorithms - to detect and pinpoint what’s risky from the data collected.
Analyze your data at the population-level to find connections between bad actors
Examine your data as a whole in order to identify trends, repeat patterns, and anomalies in user behavior that would be indicative of a potential fraud threat and block them immediately.
Use an identity platform that supports active segmentation to make better-informed decisions in real time
By fully leveraging the collected signals and evidence, ensemble models, and population-level insights, you can actively segment users based on their risk level. You can surface the right approach at the right time.
The strategic guide to fighting GenAI fraud
Learn what you can implement now to actively defend your business against GenAI-powered fraud while respecting legitimate users and preventing economic losses.
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