Abstract: Techniques are provided for electronic document management in a computing environment. A business unit and a document type determined for an electronic document may be used to determine that an electronic document is required to adhere to an event-based retention policy. An entry for the document can be created in an event-mapping data structure. Events and actions that occur at each system of record can be tracked by generating an entry in an event tracking data structure. The system of record and attribute value from each entry in the event tracking data structure may be utilized to identify matching entries in the event-based mapping data structure. The expiration date in a matching entry, which corresponds to an electronic document, can be updated using the event date in the event tracking entry and the duration of the event-based retention policy included in the matching entry.

Abstract: The End-to-End Encryption and Hot Wallet Key Recovery Apparatuses, Processes and Systems (“E2EEHWKR”) transforms key backup request, key recovery request datastructure/inputs via E2EEHWKR components into key backup response, key recovery response outputs. A key backup request datastructure specifying a wallet private key, a private key backup server identifier, a PIN shard fracture scheme definition, and a plurality of PIN shard backup devices is obtained. A user security PIN is obtained and utilized to encrypt the wallet private key. A symmetric key is calculated from a public key associated with the private key backup server identifier and an app private key. The encrypted wallet private key is encrypted utilizing the symmetric key. The twice encrypted wallet private key is sent to a private key backup server. The user security PIN is encrypted utilizing an asymmetric keypair. Encrypted user security PIN shards are generated and sent to PIN shard backup devices.

Abstract: The Transfer Transaction Blockchain with Clawback Apparatuses, Processes and Systems (“NBSA”) transforms authenticating NFT generation input, NFT authentication input, document publishing input, NFT document access input, transfer transaction input, clawback transaction input datastructure/inputs via NBSA components into authenticating NFT generation output, NFT authentication output, document publishing output, NFT document access output, transfer transaction output, clawback transaction output outputs. A transfer transaction processing request datastructure structured as specifying a transaction requestor blockchain address, a transfer transaction identifier, and authorization data is obtained. The authorization data is evaluated to verify control over the transaction requestor blockchain address. A clawback post transaction is submitted to a blockchain.

Abstract: The NFT Based Secure Authentication and Notification Apparatuses, Processes and Systems (“NBSA”) transforms authenticating NFT generation input, NFT authentication input, document publishing input, NFT document access input datastructure/inputs via NBSA components into authenticating NFT generation output, NFT authentication output, document publishing output, NFT document access output outputs. An NFT document access request datastructure is obtained. An owner blockchain address is determined. Authorization data is evaluated. An NFT metadata datastructure associated with a notification NFT identifier is obtained. A document publishing transaction identifier associated with the notification NFT identifier is determined. A first document hash specified via a document publishing transaction is determined. A second document hash associated with a document object corresponding to a document object identifier specified via the document publishing transaction is determined.

Abstract: Systems and methods are described for preventing fraud in transactions in real-time. A first computing device associated with an issuing authority may generate compliance certificates including one or more restriction rules that prohibit specific transactions from being executed by an entity that is regulated by the issuing authority. When a user requests a second computing device associated with the entity to perform a transaction, the second computing device determines whether it can execute the transaction in the request in view of the one or more restriction rules in the compliance certificate. In case the transaction includes attributes that would violate at least one of the one or more restriction rules, the second computing device rejects or blocks the transaction. On the other hand, in the case, the transaction includes attributes that does not violate any of the one or more restriction rules, the second computing device executes the transaction.

Abstract: Methods and apparatuses are described for user authentication during an electronic signature workflow. A server authenticates user credentials included in an electronic signature request. The server generates activity variables based upon parameters associated with the electronic signature request. The server creates a multidimensional vector using the activity variables. The server executes a trained machine learning classification model on the multidimensional vector to generate an anomaly score for the electronic signature request. The server determines additional authentication requirements for the electronic signature request based upon the anomaly score. The server initiates the additional authentication requirements for the electronic signature request, including validating user authentication data received from remote computing devices.

Abstract: A computer-implemented method is provided for producing a test for a software application that is generated based on metadata. The method includes providing to the user a library of predefined test logic for testing multiple software components. Each software component is a reusable element comprising application logic, visual styling and user interface. The method also includes guiding the user to define (i) at least one execution path that specifies an order for testing one or more pages of the software application, and (ii) test instructions for one or more components on each of the one or more pages. The method further includes retrieving, from the library, predefined test logic for the one or more components if they are present in the library based on the test instructions supplied by the user, and automatically configuring a test file incorporating the predefined test logic in an order specified by the execution path.

Abstract: The NFT Based Secure Authentication and Notification Apparatuses, Processes and Systems (“NBSA”) transforms authenticating NFT generation input, NFT authentication input, document publishing input, NFT document access input datastructure/inputs via NBSA components into authenticating NFT generation output, NFT authentication output, document publishing output, NFT document access output outputs. An authenticating NFT generation request datastructure structured to specify a set of source asset identifiers and an owner blockchain address is obtained. For each respective source asset identifier, source asset data associated with the respective source asset identifier is obtained, a hash of the source asset data is generated, and a source asset object associated with the respective source asset identifier is stored in an adjunct repository. A master hash is generated from the generated hashes. An NFT metadata datastructure structured to specify the master hash and a link to each source asset object is generated.

Abstract: Computerized systems and methods are provided for identifying connection between at least one application in a set of client applications within a multi-tenant network and a service application hosted on a server. Audit logs are generated that track activities for respective ones of the client applications over a predetermined duration. Information from a first audit message of each client application is extracted that includes an audit identification and a connecting IP address associated with the corresponding client application. Information from a second audit message of each client application is extracted that includes an audit identification and a process identification of the corresponding client application. The extracted information is used to identify one or more client applications as being connected to and consuming the service application.

Abstract: Systems and methods are described for predicting tasks that users perform on websites. More specifically, a machine learning model is trained using page session data (that includes page flows which are a sequence of pages visited by a user) for each user that is associated with the website. In addition, the machine learning model is fine-tuned using previous page flows associated with the user, user attribute data that is associated with the user, and user tasks, which are tasks that have been previously completed by the user. When a user visits the website, the machine learning model determines a predicted task after the user visits a predetermined number of webpages. A recommended content is generated based on the predicted task and displayed before the user.

Abstract: A computerized method is provided for automated profiling and comparison of electronic data including in different environments and formats. Data column comparison and/or mapping can be efficiently accomplished without input of human experts through a three-step process including column name direct matching, a fuzzy string matching algorithm (token sort ratio) on unmatched columns, and finally a column data comparison for remaining unmatched columns.

Abstract: Methods and apparatuses are described for intelligent text classification with limited or no training data. A server computing device receives one or more of structured text or unstructured text corresponding to compliance text data from a database. The server computing device executes a trained few-shot natural language inference (NLI) classification model on one or more sentences in the received compliance text data to identify whether the one or more sentences comprise a compliance violation. The server computing device transmits the results of the model execution to a remote computing device.

Abstract: Methods and apparatuses for synchronizing data recovery files in cloud-based database management platforms include a server that allocates physical storage media for database management platforms hosted in a cloud computing environment and attaches a source database management platform in a first region of the environment to the allocated storage media. The server attaches a target database management platform in a second region of the environment to the allocated storage media. The server establishes a periodic replication job between the source database management platform and the target database management platform, including validating change files associated with differential data changes in a primary database instance and transmitting the validated change files to the target database management platform for replication in a secondary database instance.

Abstract: A method for identifying the presence of a logo in an image includes providing a neural network having an image encoder, a text encoder, and a score calculator. The method includes receiving the image and a textual description associated with the logo. The method further includes providing the image to the image encoder and the textual description to the text encode. The method includes executing the image encoder and the text encoder, wherein the image encoder generates one or more image embeddings from the image and the text encoder generates one or more text embeddings from the textual description. The method further includes executing the score calculator, wherein the score calculator generates a score from the one or more image embeddings and the one or more text embeddings. The method also includes determining the presence of the logo in the image based on the score.

Abstract: Methods and apparatuses are described for digital content classification and recommendation using constraint-based predictive machine learning. A server trains a machine learning (ML) recommendation model to generate digital content layouts each comprising digital content item slots arranged according to one or more digital content selection constraints. The server receives user profile information for a first user. The server executes the trained ML recommendation model to generate a plurality of digital content item displays, each including a selected digital content item placed in each slot. The server determines, for each digital content item display, an interaction prediction score for each digital content item in the display. The server selects a digital content item display based upon the interaction predictions scores. The server transmits the selected digital content item display to a client device.

Abstract: The Distributed Benefits Coverage Validation Apparatuses, Processes and Systems (“DBCV”) transforms provider info, add provider transaction request, employee subscriber ID card data datastructure/inputs via DBCV components into add provider transaction response, benefit coverage validation notification outputs. A benefit coverage validation request datastructure structured to specify subscriber ID card data associated with a beneficiary is obtained. A blockchain address of a smart contract associated with the beneficiary is determined via the subscriber ID card data. Encrypted benefit coverage data associated with the beneficiary is obtained by sending a blockchain transaction to the blockchain address of the smart contract. An encryption key corresponding to the encrypted benefit coverage data is obtained from a key management server. The encrypted benefit coverage data associated with the beneficiary is decrypted with the encryption key.

Abstract: A computerized method is provided for user authentication using hand gestures. Multiple points on a user's hand can be tracked using cameras or various sensors and the motion of those points in space and relative to each other can used to create gesture-based passwords. Such user authentication techniques have advantages in augmented and virtual reality applications where traditional text-based passwords may be difficult. Gesture-based user authentication can be augmented with physical characteristics of the specific user's fingers and hands including size, shape, and distinguishing marks to enhance security.

Abstract: Techniques are provided for monitoring the integrity of a table in a dataset. The table may include one or more columns and one or more rows, in which data elements in the table are associated with a specific row and a specific column. A coverage rule set may be generated based on metadata of the table, which describes attributes of the table and the columns associated with the table. The coverage rule set includes table rules and column rules. A table fault value is generated for each table rule in the coverage rule set and a column fault value is generated for each column rule in the coverage rule set. An error is detected when a table fault value or a column fault value exceeds at least one of a corresponding table rule threshold or a corresponding column rule threshold. A notification is transmitted for error detected.

Abstract: A computer-implemented method for adaptively discretizing a position of a textual object in a document includes receiving, by a computer system, an image of the document and determining, by the computer system, an absolute position of the textual object in the image of the document. The method further includes normalizing, by the computer system, the absolute position to determine a relative position of the textual object. The method also includes calculating, by the computer system, a bin size such that at least one axis of the image is divided into a plurality of separate bins, wherein a distance between each bin along the at least one axis and its adjacent bin equals the bin size. The method includes discretizing, by the computer system, the relative position based on the bin size to determine a discretized position of the textual object; and providing, by the computer system, the discretized position and a textual content of the textual object as an input to a machine learning model.

Abstract: The Thematic Protocol and Circle Datastructure Apparatuses, Processes and Systems (“TPCD”) transforms TOP-RC search request, TOP-RC selection request inputs via TPCD components into TOP-RC search response, TOP-RC selection response, pool distribution notification request outputs. A thematic circle join request datastructure that includes a user object identifier, a portfolio object identifier associated with the user object identifier, and a thematic circle template identifier is obtained. A thematic circle object instantiated based on a thematic circle template corresponding to the thematic circle template identifier is determined. The user object identifier is added to participants datastructure. A portfolio object corresponding to the portfolio object identifier is marked as locked. A set of creation criteria associated with the thematic circle object is evaluated. The thematic circle object is activated based on a determination that the set of creation criteria has been met.