Fifth Third Bancorp’s patent involves a system using deep learning models to identify suspicious cash structuring activity in accounts. By analyzing daily and global inputs, the system generates a single score for the account, alerting users if it falls outside a set threshold. GlobalData’s report on Fifth Third Bancorp 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 Fifth Third Bancorp, was a key innovation area identified from patents. Fifth Third Bancorp's grant share as of February 2024 was 90%. Grant share is based on the ratio of number of grants to total number of patents.
Identifying suspicious cash structuring activity using deep learning model
A recently granted patent (Publication Number: US11868865B1) discloses a computer-readable medium storing instructions for identifying potentially suspicious cash structuring activity. The instructions involve receiving account data, determining global or daily inputs, generating a deep learning model using an ensemble teacher model with convolution layers and non-linear activation functions, and inputting daily inputs into the model. The output is aggregated by mixed pooling and normalization, with further modulation of global inputs and concatenation with the normalized output.
Additionally, the patent describes a method and system for identifying suspicious cash structuring activity. The method involves receiving account data, determining global or daily inputs, generating a deep learning model using an ensemble teacher model, and inputting daily inputs. The system includes processors for these functions, with features like mixed pooling, normalization, modulation of global inputs, and concatenation. The method and system aim to enhance the detection of potentially suspicious activities by utilizing deep learning models and ensemble teacher models, showcasing advancements in technology for financial monitoring and security purposes.
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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.
