Historical Data
Why Historical Data Matters
Historical data is imperative for building effective anomaly detection models. It provides the foundation for understanding normal patterns of behavior within transactions and customer interactions. By analyzing historical data, our models can identify deviations that signal potential fraud or other anomalies. This allows for proactive measures, reducing risks and ensuring the integrity of your financial operations.
Data is securely stored using advanced encryption methods and carefully anonymized to ensure the highest level of confidentiality and privacy protection, safeguarding sensitive information while maintaining compliance with industry standards.
Request Data
To create a robust anomaly detection model tailored to your needs, we require the provision of historical data to train the model. These fields help us capture the full scope of transactional, customer, and other relevant activities.
Providing an ample amount of historical data is crucial for the optimization of our anomaly detection model, which is designed to identify and mitigate potential fraud and risks. Historical data serves as the foundation for training our model, enabling it to understand normal behavior patterns and accurately detect anomalies. By supplying comprehensive historical data, clients enhance the model’s ability to learn from past transactions, both legitimate and fraudulent, which significantly improves its predictive accuracy and robustness. This, in turn, allows our clients to proactively identify and respond to suspicious activities, thereby strengthening their overall fraud prevention and risk management strategies.
You can find a detailed breakdown of the datasets we request for, with decriptions of each data point and the format we require for them in here.
How To Submit Historical Data
Historical data files must be sent in a compressed zip file.
The files should comprise of a JSON file with an array of all transactions.