Toronto-Dominion Bank had three patents in big data during Q2 2024. The Toronto-Dominion Bank has filed a patent for a system that automatically generates a machine learning model to forecast the likelihood of compromise in transaction devices. This system can trigger actions on related computing devices based on potentially compromised transaction devices. GlobalData’s report on Toronto-Dominion Bank gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Toronto-Dominion Bank had no grants in big data as a theme in Q2 2024.
Recent Patents
Application: Systems and methods for automated compromise prediction (Patent ID: US20240119346A1)
The patent filed by The Toronto-Dominion Bank describes a computer-implemented method, system, and device for automatically generating a machine learning model to forecast the likelihood of compromise in transaction devices. The system retrieves transaction data, splits it into training and validation samples, and uses a gradient boosted algorithm to train the model. The model is then tested on new data to forecast the likelihood of compromise for each transaction device. The system can trigger actions on related computing devices based on the detected likelihood of compromise.
The system includes features such as out-of-time validation and out-of-sample validation, a buffer window separating feature extraction and testing periods, and the ability to remove transactions associated with compromised devices from training iterations. The extracted features include enterprise data features and fraud analytics features, with different window sizes for feature extraction based on the type of feature. The method also involves instructing computing devices associated with compromised transaction devices to take actions based on the likelihood of compromise detected. Overall, the system aims to automate the process of generating a machine learning model for forecasting compromise likelihood in transaction devices and triggering actions accordingly.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
