Bank of New York Mellon has been granted a patent for a system that uses resolved exceptions information to predict dividend classifications for transactions. The system utilizes a neural network to generate decision trees and assign dividend-related classifications based on unresolved exceptions. GlobalData’s report on Bank of New York Mellon gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Bank of New York Mellon, Corrosion resistant battery packaging was a key innovation area identified from patents. Bank of New York Mellon's grant share as of January 2024 was 90%. Grant share is based on the ratio of number of grants to total number of patents.
Model-based dividend classification system for transactions
A recently granted patent (Publication Number: US11887013B2) discloses a system for facilitating model-based dividend classification of transactions. The system involves a computer system with processors programmed to obtain resolved exceptions information, provide it as input to a neural network to generate decision trees, and assign dividend-related classifications to transactions based on the decision trees. The neural network comprises multiple layers of neural units, and the system analyzes the accuracy of each decision tree to select the most accurate one for classification. Additionally, the system can generate narrations for transactions based on the decision tree's attributes, enhancing the understanding of the classification process.
Furthermore, the patent includes a method implemented by a computer system to perform the model-based dividend classification of transactions. The method involves obtaining resolved exceptions information, providing it to a prediction model to generate decision trees, and assigning dividend-related classifications to transactions based on the nodes of the decision trees. The accuracy of each decision tree is analyzed to select the most accurate one for classification purposes. The method also includes generating narrations for transactions and predicting dividend-related classifications for various transactions based on the decision trees. Overall, the system and method aim to streamline the dividend classification process by utilizing neural networks and decision trees to enhance accuracy and efficiency in assigning classifications to transactions based on resolved exceptions information.
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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.
