3 facts about the solution
The model uses customer data and transactions to predict the likelihood of fraud
It detects, analyzes, and links fraudulent patterns to real-time transactions
Significantly reduce false-positive rates when carrying out anti-money laundering, trade surveillance, or fraud checks
Why predict fraud with AI?
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. For more details on our AI solution for predicting fraud, download the factsheet.
In our model library, you will find 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.