公开(公告)号：US20250053733A1

公开(公告)日：2025-02-13

申请号：US18446749

申请日：2023-08-09

Applicant: THE BANK OF NEW YORK MELLON

Inventor： Rafal Sitkowski ,  Jeffrey Hassan ,  Liza Antignani ,  Erazm Edward Malarczyk ,  Marcin Maciej Makowski ,  Boguslaw Fraszko

IPC: G06F40/186 ,  G06F3/0482

Abstract: Electronic document generation systems and methods include a processor, a memory component communicatively coupled to the processor, and machine-readable instructions. The machine-readable instructions cause the system to access an electronic document generation template including placeholders with nesting values indicative of a number populating conditions to generate an electronic document, populate one or more placeholders associated with corresponding nesting values of zero with data from a master data store or data that is based on a user input to a prompt, prompt, via a graphical user interface, the user to respond to one or more conditional prompts, populate one or more placeholders associated with the next lowest corresponding nesting value based on a user input to the one or more conditional prompts, and generate the electronic document based on the one or more placeholders as populated via the electronic document generation template for display on the graphical user interface.

公开(公告)号：US20250053397A1

公开(公告)日：2025-02-13

申请号：US18790613

申请日：2024-07-31

Applicant: THE BANK OF NEW YORK MELLON

Inventor： Jisoo LEE

IPC: G06F8/51

Abstract: Systems and methods for translating a first coding language into a second coding language train a machine learning (ML) model on a first coding language specific data set relating to the first coding language, in which the ML model is trained to translate one or more code sets of the first coding language to respective one or more code sets of the second coding language; using the ML model, generate various unit test cases, in which the unit test cases run the one or more code sets of the second coding language in parallel with the one or more code sets of the first coding language; iteratively test and refine the ML model until a maturity threshold is reached; and upon reaching the maturity threshold, containerize the one or more code sets of the second coding language into one or more applications.

公开(公告)号：US20250004889A1

公开(公告)日：2025-01-02

申请号：US18344541

申请日：2023-06-29

Applicant: THE BANK OF NEW YORK MELLON

Inventor： Shriniwas IYENGAR ,  Gerald VERRILLI ,  Narayan JHA

IPC: G06F11/14

Abstract: Provided are processes, systems, and methods for automation of investigation and resolution of transaction breaks such as, for example, a trade break, a reconciliation break, a dividend break, or a security position break. Breaks (e.g., discrepancies in records of transactions) often occur when there exist different systems or applications that operate in concert. A break refers to a situation where there is a discrepancy between details, attributes, or characteristics of a transaction across different computing systems or applications. In many cases, there exists a need to ensure consistency between the records of these different systems. Thus, for example, an entity may desire to resolve those breaks, such as to reduce risk, maintain compliance, or to provide accurate accounting of records.

公开(公告)号：US20240372864A1

公开(公告)日：2024-11-07

申请号：US18312118

申请日：2023-05-04

Applicant: The Bank of New York Mellon

Inventor： Jeffrey Hassan ,  Rafal Sitkowski ,  Hood Qaim-Maqami ,  Carl Albert Johnson ,  Liza D. Antignani

IPC: H04L9/40 ,  G06F3/0484 ,  G06F21/60

Abstract: Electronic document collaboration systems and methods includes one or more processors, one or more memory components communicatively coupled to the one or more processors, and machine readable instructions. The machine readable instructions cause the system to access an electronic document on a graphical user interface by a participant user of a collaborator group of one or more collaborator groups assigned to an entity of a plurality of entities, add a comment to the displayed electronic document via an entry by the participant user into the electronic document, assign the comment a unique identifier, prompt the participant user to select a security designation for the comment in response to the comment being added to the electronic document, and associate the security designation with the unique identifier of the comment.

公开(公告)号：US20240281599A1

公开(公告)日：2024-08-22

申请号：US18649444

申请日：2024-04-29

Applicant: THE BANK OF NEW YORK MELLON

Inventor： Claudio SOTO ,  Akashkumar DESAI ,  Aravind Kumar RAVINDRAN ,  Michal SZAFIRSKI

IPC: G06F40/177 ,  G06F40/103

CPC classification number: G06F40/177 ,  G06F40/103

Abstract: The disclosure relates to user interfaces that reconcile non-linear data and a table format to display the non-linear data across various screen sizes without loss of information. A system may access non-linear data such as a hierarchical data structure. The system may access a plurality of data elements that represent the non-linear data for rendering in a display container, which has a display height that varies depending on the screen size of a given display device. The system may obtain the available display height and determine a number of columns to render based on the display height and the plurality of data elements. The system may fill the columns with the plurality of data elements using a columnar format that maintains contiguity of groups of data elements that span more than one column. The system may configure a patch to visually indicate the contiguity.

公开(公告)号：US20240273353A1

公开(公告)日：2024-08-15

申请号：US18166696

申请日：2023-02-09

Applicant: THE BANK OF NEW YORK MELLON

Inventor： Philipp RIEDER

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: The disclosure relates to systems and methods of determining gradient-based directional drivers of deep learning models. A system may access a plurality of features and a group definition that specifies one or more groups of features. The system may provide the plurality of features as input to a deep learning model trained to generate a model output based on a model function and the plurality of features. The system may obtain, for each feature, a gradient that represents a rate of change of the model function based on the feature and then aggregate, based on the group definition, the gradients obtained from the deep learning model; and for each group of features from among the one or more groups of features: determine a directional driver based on the aggregated gradients, the directional driver indicating an impact of the group of features on the model output.

公开(公告)号：US12050934B2

公开(公告)日：2024-07-30

申请号：US17887113

申请日：2022-08-12

Applicant: THE BANK OF NEW YORK MELLON

Inventor： Brian Blank

IPC: G06F9/50

CPC classification number: G06F9/5027

Abstract: A method for real-time data processing is described. The method being implemented on a computer system having one or more physical processors programmed with computer program instructions which, when executed, perform the method. The method comprising allocating a real-time dataset associated with a real-time data interaction to a node in a chain of nodes, wherein each node is representative of a user in the real-time data interaction; setting a node status of the node for the real-time dataset to pending; and independently of (i) a node status of the one or more upstream nodes and (ii) a node status of the one or more downstream nodes: periodically determining, by the computer system, an availability status of the node; and in response to the availability status satisfying the criterion, setting the node status for the real-time dataset as settled.

公开(公告)号：US20240071117A1

公开(公告)日：2024-02-29

申请号：US17894011

申请日：2022-08-23

Applicant: THE BANK OF NEW YORK MELLON

Inventor： Ibrahim GHALYAN ,  Binlin CHI

IPC: G06V30/32 ,  G06N3/04 ,  G06V30/182

CPC classification number: G06V30/32 ,  G06N3/0472 ,  G06V30/1823

Abstract: The systems and methods relate to electronic signature verification based on topological stochastic models (TSM). The TSM may be trained on samples of known authentic signatures of a signee. Training the TSM may include TSM features extraction on the training samples to extract feature vectors, TSM features aggregation to aggregate the feature vectors, and optimal threshold estimation to determine an optimal threshold value. The optimal threshold value and overall aggregate of feature vectors may be used to evaluate feature vectors extracted from a signature to be verified. For example, a distance between the resulting feature vector extracted from the input sequence and the aggregated feature vector is determined. The distance is compared to the optimal threshold value to determine whether the signature in the input image is verified. The signature in the input image is verified if the distance is less than or equal to the optimal threshold value.

公开(公告)号：US11893040B2

公开(公告)日：2024-02-06

申请号：US17826688

申请日：2022-05-27

Applicant: THE BANK OF NEW YORK MELLON

Inventor： Brian Blank

IPC: G06F16/00 ,  G06F16/27 ,  G06F16/23

CPC classification number: G06F16/273 ,  G06F16/2365

Abstract: In certain embodiments, multi-modal-based generation of settlement instructions may be facilitated. In some embodiments, a portfolio of a live environment may be emulated in a projected environment. A target portfolio may be generated in the projected environment based on the emulated portfolio. Partial synchronization between the target portfolio of the projected environment and the portfolio of the live environment may be performed such that a first subset of changes to the portfolio of the live environment are reflected in the target portfolio of the projected environment. Subsequent to the partial synchronization, the target portfolio of the projected environment may be updated such that the update of the target portfolio accounts for the first subset of changes. Subsequent to the update of the target portfolio, settlement instructions may be generated based on differences between the target portfolio of the projected environment and the portfolio of the live environment.

公开(公告)号：US20240036963A1

公开(公告)日：2024-02-01

申请号：US17878272

申请日：2022-08-01

Applicant: THE BANK OF NEW YORK MELLON

Inventor： Innamul Hassan Abdul AZEEZ ,  Badri V. MANGALAM ,  Sridhar M. SEETHARAMAN

IPC: G06F11/07 ,  G06N20/00

CPC classification number: G06F11/079 ,  G06N20/00 ,  G06F11/0709

Abstract: The disclosure relates to systems and methods of detecting anomalies using a plurality of machine learning models. Each of the machine learning models may be trained to detect a respective behavior of historical data values for a given metric. Thus, a system may perform anomaly detection based on different behaviors of the same metric of data, reducing instances of false positive anomaly detection while also reducing instances of false negative reporting. The plurality of machine learning models may be trained to detect anomalies across multiple different types of metrics as well, providing robust multi-metric anomaly detection across a range of behaviors of historical data values. The system may implement a pluggable architecture for the plurality of machine learning models in which models may be added or removed from pluggable architecture. In this way, the system may detect anomalies using a configurable set of machine learning models.