Abstract: A method for finding historically similar incidents is disclosed.

Abstract: A computer-implemented method for determining a signature embedding vector for information technology events. The method including: receiving a current data object representing an occurrence of an information technology event associated with a configurable item; obtaining a graph database of logical associations of the configurable item; applying a clustering algorithm to the graph database to determine a subset of graphs; extracting associated data of the subset of graphs; applying an embedding model to the extracted associated data to determine an embedding vector for each subset of graphs; aggregating the embedding vector for each subset of graphs to determine a signature embedding vector; and utilizing the signature embedding vector to perform further analysis of the current data object.

Abstract: A method for loop escape analysis includes receiving a set of executable computer instructions stored on a storage medium, and determining a number of inputs to a loop associated with a data structure, storage space that would be saved by compressing the data structure, and a size of new elements required to compress the data structure. Upon reaching an end of the loop, the method determines whether to compress the data structure based on a comparison between the size of the new elements and the saved storage space. In response to determining to compress the data structure, the method compresses the data structure.

Abstract: Systems and methods for application management are disclosed. The system may include a probe system and one or more director systems, each comprising at least one memory and one or more processors configured to execute instructions. The instructions may include monitoring an availability of an application; updating a status associated with the availability of the application in a first data store; polling the first data store in intervals to retrieve the status associated with the availability of the application; upon retrieving at least a consecutive predetermined number of statuses associated with the application being unavailable, determining the application is unavailable; determining whether at least one other director system of the one or more director systems has determined the application is unavailable; and upon determining the at least one other director system of the one or more director systems has determined the application is unavailable, triggering a failover process.

Abstract: The present disclosure relates to methods and systems for natural language processing (NLP). An example method includes techniques enabling a chatbot to join a group conversation, receive a request from a user in the group conversation, and analyze and confirm the authorization level of each member in the group. If each member of the group is authorized, then the chatbot can process the request, including categorizing, selecting a processing approach, and applying the processing approach.

Abstract: A method and system for generating predictive data related to institutional risks. An application programming interface (API) request for data includes multiple fields indicating a data type parameter, a dataset to be accessed, and operations to be performed on the dataset to generate first model output data. The first model output data is generated using a trained document data machine learning model. The operations indicated in the fields of the API request are performed. A data format associated with the requestor device is determined. A data stream usable by the requestor device is generated by formatting the data stream into a particular structure usable by the requesting device, the generated data stream based on the first model output data and at least one criterion of the API request. The formatted data stream is sent to a trained statistical data machine learning model to generate predictive data related to institutional risks.

Abstract: A data analytics system including an append-only first data store accessible to multiple clients and a second data store is disclosed. The data analytics system can be configurable to, in response to receiving first instructions from a first target system of a first client, the first target system separate from the data analytics system, create a first pipeline between the append-only first data store and the second data store. The first pipeline can be configured according to the first instructions to generate a client-specific data object and store the client-specific data object in the second data store. The data analytics system can be configurable to tear down the first pipeline upon completion of storing the client-specific data object in the second data store.

Abstract: A system for scoring user conversation satisfaction. The system comprises one or more memory devices storing instructions, and one or more processors configured to execute instructions to perform operations. The operations comprising receiving data corresponding to a conversation between the user and a third-party service provider. The operations further comprising parsing the data into conversation subsets, and analyzing each respective subset with a first model. The operations further comprising determining a user conversation satisfaction score based on the first model analyzed subset; storing, in a database, the parsed data subsets, and the determined conversation satisfaction score; and training a second model with the data stored in the database.

Abstract: Systems and methods are provided for implementing automated user interface testing with integrated machine learning models. Systems and methods for detecting and preemptively correcting flow path errors are disclosed. Systems and methods for minimizing user input and optimizing testing efficiency are disclosed. A result dashboard is disclosed in which testing results and errors are displayed and a user may interact with interactive testing reports.

Abstract: Systems and methods are disclosed for data processing, data verification, and categorization of items. The method includes receiving a request from a first sub-system, wherein the request includes a plurality of data associated with an access device. Determining the first sub-system and/or the access device has the authorization to access a service. Determining contextual data of one or more purses associated with the access device and/or status of the first sub-system, wherein the contextual data includes an expiration date and/or rules associated with the one or more purses. Transmitting the request to a second sub-system based on the contextual data and/or the status of the first sub-system for categorizing one or more items associated with the request into one or more categories. Executing the request based on one or more categories.

Abstract: A method for training and using a machine-learning based model to reduce and troubleshoot incidents in a system may include receiving first metadata regarding a previous modification, extracting a first feature from the received first metadata, receiving second metadata regarding a previous incident, extracting a second feature from the received second metadata, training the machine-learning based model to learn an association between the previous modification and the previous incident, based on the extracted first feature and the extracted second feature, and using the machine-learning based model to determine a risk level for a proposed modification to a system.

Abstract: Disclosed herein are systems and methods for managing transaction disputes. Techniques include accessing a transaction pattern model associated with a user account; detecting deviation of a transaction from the transaction pattern model; transmitting, based on the detected deviation, transaction data to a user device; receiving an input at the user device in response to the transmitted data; generating, based on the received input, dispute data; storing the dispute data; monitoring data extracts associated with the user account; detecting, based on the monitoring, a data extract indicating a posted state of a transaction associated with the dispute data; and updating the dispute data based on the data extract indicating the posted state.

Abstract: A data analytics system configured to perform operations is disclosed. The operations can include creating, in response to instructions received from a user, a first pipeline. This pipeline can be configured to extract data from an append-only first data store, extract identifying characteristics from the extracted data, provide the identifying characteristics to an identity service, and receive a tenancy identifier from the identity service. The pipeline can further be configured to create a data object in a second data store using the extracted data; create a tenancy object in a metadata store, the tenancy object associated with the data object, the metadata store implementing a hierarchical data object ownership graph; and associate the tenancy object with a parent object in the hierarchical data object ownership graph. The data analytics system can then tear down the first pipeline.

Abstract: Consistent with disclosed embodiments, systems, devices, and methods for extracting data from scanned documents using artificial intelligence may be provided. Disclosed embodiments may involve obtaining at least one document associated with at least one entity and identifying at least one table located on the at least one document. Disclosed embodiments may involve extracting text within the identified at least one table based on predicted coordinates of the at least one table and reproducing the at least one table using the extracted text by: identifying at least one header of the at least one table; identifying a final row of the at least one table; identifying, using a sliding window technique, columns of the at least one table; and presenting the extracted text in rows and columns. Disclosed embodiments may store the reproduced at least one table in a database.

Abstract: The disclosed embodiments include a method for providing cloud computing semantic layer. The method comprises receiving a description of a semantic layer operation performed by a semantic layer, the description including multiple implementations of the semantic layer operation, the multiple implementations differing in at least one of cloud operations used or cloud computing platforms used; receiving a request that indicates performance of the semantic layer operation; receiving first resource usage indications corresponding to the cloud operations, wherein the first resource usage indications comprise direct or indirect indications of least one of a storage amount, a compute amount, a number of transactions, a bandwidth, a number of application programming interface calls, or an application or database type associated with each of the cloud operations; selecting a first one of the multiple implementations; and communicating with the first one of the cloud providers to perform the semantic layer operation.

Abstract: Systems and methods are disclosed for generating a dynamic customized script to facilitate communication between a user and a service provider. The method includes receiving, via an interactive voice response (IVR) system, a request from a mobile device associated with at least one user. The contextual information associated with at least one user is processed, in real-time, based, at least in part, on the request. A dynamic customized script specific to the request is generated, in real-time, based, at least in part, on the processing of the contextual information. The request is routed, via the IVR system, to an agent from a pool of agents of the service provider. A presentation of the dynamic customized script is generated in a user interface of a device associated with the agent, wherein the dynamic customized script is step-by-step guidance to the agent for handling the request of at least one user.

Abstract: The present disclosure provides systems and methods for computerized methods and systems for processing transaction disputes and processing transactions associated with compromised accounts. According to one exemplary method, a server receives, from a user device, an instruction for disputing a transaction associated with a user account. The server can initiate, based on a record of the transaction, a dispute investigation, and issue provisional credit to the user account for the transaction. Based on a transaction history associated with the user account, the server can determine a plurality of expected transactions associated with the user account and cause the determined expected transactions to be displayed on the user device. After receiving a transaction authorization for at least one of the plurality of expected transactions, the server can process payments for the at least one of the plurality of expected transactions, and generate a notification indicating a status of the dispute investigation.

Abstract: Systems and methods for real-time account access, allowing access to accounts (such as deposit, credit, or debit accounts) through network processing infrastructures such as Electronic Funds Transfer (EFT). In some embodiments, consumers and/or merchants are able to effect transaction requests against accounts, using a pseudo-Identifier or other identifier, and without the need to provide an account number or card number. In other embodiments, payment networks are able to route and process transaction requests against accounts, without having a card number or account number. In other embodiments, account processing systems are able to determine an appropriate account based on transaction requests that do not contain card numbers or account numbers.

Abstract: Systems and methods for real time, online transaction processing are disclosed. The system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform a method. The method may include receiving, from an event broker, event data that includes account data. The operations may include using a data structure to identify an issuer system associated with the account data and an enrollment status of the issuer system. The method may include generating a filtered transaction data structure to an analyzer and receiving a result data structure. The method may include generating, based on the result data structure, a linked data structure comprising installment loan parameters and an online address. The method may include routing the linked data structure to a user device and receiving approval data that triggers an account allocation.

Abstract: Systems and methods, and computer readable media for image transaction processing are disclosed. The method receives an input of images of documents. The method may then analyze the input using an image processing engine to determine attributes associated with the images of the documents and identify an account linked to the attributes and a transaction associated with the account. The method may also evaluate confidence level of association links between the transaction and the account based on confidence scores of the attributes that may identify a type of the attribute. The method may use the transaction and account to split the images of documents into sets of images of documents with each set of images with confidence level of an association link between the transaction and the account associated with them being greater than a threshold value.