MODEL LIBRARY
Fraud prediction
Lower the rate of fraud with an AI model that provides accurate and up-to-date insights to prevent fraudulent transactions and conduct more efficient screenings
3 facts about the solution for predicting fraud
An AI model can enable businesses to develop plans to minimize harmful events before they arise. Our model analyzes historical transaction data to detect fraudulent patterns.
The model uses customer data and transactions to predict the likelihood of fraud
Significantly reduce false-positive rates when carrying out anti-money laundering, trade surveillance, or fraud checks
The model uses customer data and transactions to predict the likelihood of fraud
Discover the value of detecting fraud with AI
Number of transactions/claims:
Average claim/transaction value per case:
Estimated percentage of fraudulent transactions/claims (%):
With an AI model, you can:
Detected fraudulent transactions/claims
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Recoverable Value
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Assumptions (click to expand)
AI model accuracy (%)
Our solution
We offer a variety of standard models ready to be fitted to your data. The fraud prediction model is a standard model that stores which customer profile is associated with fraud and which of the descriptive variables are most likely to classify the cases. While predicting the probability of fraud, the model also produces model insights for each prediction.
The business outcome
Using our fraud prediction model gives you an overview of the likelihood of fraud in a transaction, claim, etc. Your organization can then direct its screening efforts to those customers who have a high risk of fraud. Furthermore, you will gain insights into what drives fraud and, with this information, starts to change or lower the rate of fraud by screening more effectively.
Interested in lowering the rate of fraud with AI?
If you think our solution for predicting fraud would be relevant for your organization, please book a demo – we would love to help you get started. Alternatively, you can download our GRACE brochure for more information.