Abstract: A system for performing a timeliness control is disclosed. The system identifies a dataflow path for performing timeliness control and identifies a first network node and a second network node of the dataflow path for determining a latency between the first and the second network node. The system determines an output lineage corresponding to the dataflow path and identifies, from the output lineage, a first control value associated with the first network node and a second control value associated with the second network node. Then, the system extracts a first timestamp from the first control value and a second timestamp from the second control value and determines the latency based on the first timestamp and the second timestamp. Although the intranode latency is described herein with respect to a first and second nodes, the intra-node latency can be determined for up to n nodes using the techniques described herein.

Abstract: A computer implemented system and method are disclosed involving technological advancements in the processing of electronic transaction processing results. The system may comprise a computer apparatus implementing a checking account system, a savings account system, a merchant account and investment account on a funds management system, and one or more computer systems and mobile devices including a communication interface, processor, memory storing computer-executable instructions, and savings modules. Reward amounts may be calculated based on various techniques.

Abstract: A device that includes a node engine configured to determine a core distance for a correlithm object core. The node engine is further configured to select a first correlithm object in an n-dimensional space and set the first correlithm object as the root correlithm object. The node engine is further configured to receive a second correlithm object and determine the distance between the root correlithm object and the second correlithm object. The node engine is further configured to determine whether the distance between the root correlithm object and the second correlithm object is less than core distance for the correlithm object core. The node engine is further configured to identify the second correlithm object as a member of the correlithm object core in response to determining the distance between the root correlithm object and the second correlithm object is less than core distance for the correlithm object core.

Abstract: Aspects of the disclosure relate to computing systems for receiving user requests through channels of a webpage and performing computational functions corresponding to the user requests. In one embodiment, a computing platform may detect a change corresponding to input parameters for performing a user request through a first representation of a webpage. The computing platform may update, based on the detected change corresponding to the input parameters, a natural language processing application associated with a second representation of the webpage. The computing platform may generate, based on the updated natural language processing application associated with the second representation of the webpage, a logical table including one or more questions to ask a user through the second representation of the webpage in response to one or more user inputs.

Abstract: Aspects of the disclosure relate to multicomputer processing of client device request data using a centralized event orchestrator and a dynamic endpoint engine. A computing platform may receive, from a client computing device, event definition information defining an event. Subsequently, the computing platform may receive, from a recipient computing device associated with the event, a request for a recipient-selection user interface, and may determine that a dynamic endpoint option is available for a user of the recipient computing device. Thereafter, the computing platform may send, to the recipient computing device, a delivery selection user interface that includes a user-selectable option that, when invoked, causes the computing platform to create a new endpoint.

Abstract: A system is configured to allocate storage space on existing devices within the entity's networked system to create cloud storage space. In particular, unallocated space on computing devices, typically user devices, within an entity's network is utilized as a cloud data repository. Cloud data is indexed, divided into chunks, encrypted, and stored on numerous disparate endpoint devices connected to the network. Copies of cloud chunk data may be duplicated across multiple endpoint devices to allow for data redundancy, thereby ensuring cloud data uptime according to the availability needs of the entity. Cloud data may further be allocated to different devices based on regional data restrictions. In this way, the system provides an efficient and secure way to generate an internal cloud data storage repository within an entity's networked system.

Abstract: Systems, computer products, and methods are described herein for an improved secure certificate system for identifying potential authorized and unauthorized interactions between a web browser and a website. The certificate system utilizes stored certification requirements (e.g., pinned certification requirements, third-party certification requirement system, or the like), and compares the stored certification requirements with received certification requirements. The system may notify the user or prevent the interaction between the web browser and website when the stored certification requirements do not meet the received certification requirements (e.g., a threshold requirement of certificates to validate, validated certificates, or the like). The certificate system allows the interaction between the web browser and website when the stored certification requirements meet the received certification requirements and the website is verified based on the certification requirements.

Abstract: The invention utilizes a two-component system to detect third party security threats and drive internal system processes based on the detection. The first component of the system is a threat level engine, which collects external and internal system data on a real-time basis to determine changes in conditions that may give rise to a security threat. Based on the external and internal data, the level engine may calculate a threat assessment level to determine the level of the threat. The second component of the system is a third party analytics engine, which may comprise a machine learning component which is configured to detect threat patterns and anomalies, which may in turn be used to trigger events or to drive internal system processes.

Abstract: Embodiments of the present invention provide a system for controlling versions of codes during software integration and deployment. The system is typically configured for creating a program increment development branch in a first environment system, opening a first iteration candidate under the program increment development branch with a first iteration version number associated with a program increment version range of the program increment development branch, receiving at least one first development code from a first user via a smart tool user interface, moving the first development code to the first iteration candidate, receiving a first input from the first user to lock the first iteration candidate, locking the first iteration candidate, and closing the first iteration candidate.

Abstract: A smart transmission system is configured to upload data from a plurality of sources to a target application hosted in a cloud environment. A server receives a data stream from the plurality of sources. Using a priority algorithm, the server analyzes the data stream to determine which files and accounts are most critical for the target application's function. The files and their associated accounts are partitioned into tranches, and the tranches are uploaded to the target application in order of priority.

Abstract: A device that includes a node engine configured to define a number of child correlithm objects for a string correlithm object. The node engine is further configured to select a correlithm object from an n-dimensional space and set the selected correlithm object as a parent correlithm object. The node engine is further configured to iteratively identify the defined number of child correlithm objects, where identifying the defined number of child correlithm objects involves randomly selecting correlithm objects less than the standard distance away from the parent correlithm object and defining the selected correlithm objects as a child correlithm object. The node engine is further configured to link the defined child correlithm objects with the parent correlithm object in the node table to generate the string correlithm object.

Abstract: A distributed node network to emulate a correlithm object processing system, includes a resolution node, a first calculation node, and a second calculation node. The first and second calculation nodes determine the n-dimensional distances between an input correlithm object and first and second portions of each source correlithm object of a mapping table, respectively. The resolution node adds the n-dimensional distance determined for the first portion of each source correlithm object with the n-dimensional distance determined for the second portion of each source correlithm object. It compares these determined n-dimensional distances to each other to identify the source correlithm object with the smallest n-dimensional distance to the input correlithm object. It identifies the target correlithm object that corresponds to the identified source correlithm object, and outputs that target correlithm object.

Abstract: A system for resolving item-processing exceptions typically includes a processor, a memory, and an exception resolution module stored in the memory. The exception resolution module is typically configured for: receiving an item-processing exception; determining a source of the item-processing exception; based on the source of the item-processing exception, identifying a defined exception resolution process; based on the defined exception resolution process, creating and configuring a pipeline context for resolving the item-processing exception, the pipeline context including the defined exception resolution process; storing the pipeline context in a pipeline database; adding the pipeline context to a pipeline queue; selecting, via a pipeline manager service, the pipeline context from the pipeline queue; and executing, via a worker thread, the pipeline context by executing the defined exception resolution process.

Abstract: Aspects of the present disclosure are directed to electronic computer implemented methods of data communication. The method includes receiving a plurality of virtual nodes with EDI data payload including a node attribute, a GPS location attribute and a biometric ID attribute and at least one data element associated with the GPS location attribute. In further aspect, the method includes electronically via a data communications network, processing the EDI data payloads including the node attribute, the GPS location attribute and the biometric ID attribute and the at least one data element associated with the GPS location attribute. Then, electronically processing the EDI data payloads in a network with machine learning and providing an electronic message responsive thereto. In yet a further aspect, the data communications method includes a step of processing the smart data set in the network with machine learning and providing an electronic message responsive thereto.

Abstract: Embodiments are described herein for improved verification utilizing dynamic authentication information. Dynamic authentication may include utilizing dynamic authentication information, which is user information that is personal to the user and that changes over-time, such as over various time periods. This type of dynamic authentic information is readily known to the user, but would be difficult for others to determine. The present invention may be utilized to improve the security of the interactions made by the user due to the dynamic authentication information.

Abstract: Embodiments of the present invention provide a system for indicator regression and modeling for implementing system changes to improve control effectiveness. The system is typically configured for presenting, prompting for and receiving a selection from a list of controls from a user, via a control effectiveness application user interface on a user device. The system is also for receiving two or more consideration indicators from the user device, via the control effectiveness application user interface forming a consideration set; applying a regression algorithm on the consideration set of indicators; reducing a number of the subset of the consideration set of indicators based on a threshold correlation or a threshold number; finalizing the final equation with the number of the subset, each having a corresponding coefficient; and, in response to finalizing the final equation, automatically performing an action configured to improve effectiveness of the control based on the final equation.

Abstract: An apparatus includes a scanner and a resolution engine. The scanner detects first and second software exceptions. The scanner also determines that the first software exception occurred previously in a plurality of desktops and that the second software exception did not occur previously in the plurality of desktops. The resolution engine determines a first solution and a second solution for resolving the first software exception and that the first solution has a higher ranking than the second solution. The resolution engine also generates a software patch that implements the first solution and deploys the software patch. The resolution engine further determines a series of steps implemented to resolve the second software exception and records the series of steps to prepare a second software patch if the second software exception occurs again in the plurality of desktops.

Abstract: Embodiments of the present invention provide a system for real-time transmission of data associated with trigger events. The system is configured for identifying one or more priorities associated with a user, extract one or more triggers associated with the one or more priorities of the user, receiving an indication that at least one condition associated with at least one of the one or more triggers is met, determining that the user is performing one or more actions associated with at least one priority of the one or more priorities based receiving the indication, in response to determining that the user is performing the one or more actions associated with the at least one priority, dynamically extracting information associated with the user, and transmitting, in real-time, the extracted information associated with the user to at least one third party entity.

Abstract: Aspects of the disclosure relate to utilizing smart data tags to track and control secure enterprise data. A computing platform may receive, from an enterprise user computing device, enterprise data. Subsequently, the computing platform may determine one or more tags to be applied to the enterprise data. Then, the computing platform may generate a smart data object based on the enterprise data received from the enterprise user computing device and the one or more tags determined to be applied to the enterprise data received from the enterprise user computing device. Next, the computing platform may send, to an enterprise data storage platform, the smart data object, and sending the smart data object to the enterprise data storage platform may cause the enterprise data storage platform to store the smart data object in a repository comprising a plurality of smart data objects maintained by the enterprise data storage platform.