Abstract: Embodiments of the present invention provide a system for secure transfer of encrypted resources and asynchronous execution. In general, a user initiates an event with a merchant system and requests a secure resource transfer process associated with the event. Encrypted initial event details are transmitted through an asynchronous command form the merchant system to a computing device of the user, and resource information is identified at the computing device of the user. The computing device of the user then transmits the event details and the resource information to an event processing system for final execution.

Abstract: A data aggregator includes a memory, a network interface, a vectorization engine, and an aggregator. The memory stores a plurality of aggregation rules. The network interface retrieves a plurality of transactions that includes a first transaction and a second transaction. The vectorization engine determines a first transaction vector for the first transaction and a second transaction vector for the second transaction. The aggregator determines that the first transaction occurred during a first life event and that the second transaction occurred during a second life event. The aggregator also determines that the first life event and the second life event are the same and in response to that determination, assigns the first transaction and the second transaction to a cluster for the first life event. The aggregator further stores the first life event, the second life event, and an identifier for the cluster to the database.

Abstract: A method comprises creating a word vector from a message, wherein the word vector comprises creating a word vector from a message stored in a database, wherein the word vector comprises an entry for each word of the plurality of words and each entry indicating a number of occurrences in the message of the word for that entry. The method further comprising calculating a cosine difference between the word vector and each group vector of a plurality of group vectors and assigning the word vector to a group for a group vector of the plurality of group vectors based on the calculated cosine difference between the word vector and the group vector for the group. The method may also comprise reformatting the message to include a phrase and assigning the phrase to the same group that the word vector is assigned to. The method may also comprise notifying the user.

Abstract: In an embodiment of the present disclosure, an embodiment includes a user device comprises a conversion engine configured to receive a biometric file comprising biometric identification information of a user and convert the biometric file into a first numeric representation. The user device further comprises a hashing engine configured to create a superimposed numeric representation by performing a convolution operation on the first numeric representation and a second numeric representation, wherein the second numeric representation is based on a key file that is different from the biometric file. The hashing engine is further configured to convert the superimposed numeric representation into a hash value, send, over a network connection, the hash value for authentication, and receive a message indicating whether authentication was successful.

Abstract: In an embodiment of the present disclosure, a biometric identification device comprises a conversion engine configured to receive a key file, receive a biometric file, wherein the biometric file is different from the key file and comprises biometric identification information of a user, convert the key file into a first numeric representation, and convert the biometric file into a second numeric representation. The biometric identification device further comprises a hashing engine configured to create a superimposed numeric representation by performing a convolution operation on the first numeric representation and the second numeric representation, convert the superimposed numeric representation into a hash value, and store the hash value.

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: A computing platform may receive video, audio, and/or biometric information of one or more people. The computing platform may identify the people based on a comparison of the video, audio, and/or biometric information to stored information in one or more user profiles each associated with the people. For example, the computing platform may compare multiple types of biometric information, including fingerprint, retina scan, facial features, and the like, as part of a process for identifying the people. The computing platform may further determine one or more interactions between the people, and, based on the interactions, determine and/or identify a relationship between the people. The identified relationships may further be used for confirming identifies of the people. Based on the identifications (e.g., biometric, video, audio, relationships), the computing platform may further provide access for the people to one or more services.

Abstract: A computer system supports secondary authentication mechanism for authentication of a user, where the computer system may provide a variety of services including financial, scientific, academic, or governmental services. The computer system utilizes a multiphase distributed trust model in which the user is authenticated based on distributed trust of a set of randomly selected trusted contacts from a large set of trusted contacts initially chosen during an enrollment phase. During the authentication phase, a subset of contacts (affirmers) is selected from the contact list. The computer system then provides additional authentication information to each of the affirmers who subsequently share the information with the user. The user then provides this information from the computer system in order to complete the secondary authentication.

Abstract: Aspects of the disclosure relate to using natural language processing to identify a context of failure associated with a channel error and analyzing the identified context of failure in relation to historic data by machine learning algorithms to identify one or more of a severity ranking, alternate channel, and solution for the channel error. In some instances, a computing platform may receive data corresponding to a system event associated with a channel of server infrastructure, identify a technical issue, customer intent, and customer sentiment of the system event, determine a context of failure of the system event, generate a mapping of the context of failure in relation to historic data, and identify a suggested solution, severity assignment, and alternate channel for the system event based on the mapping of the context of failure in relation to the historic data.

Abstract: An apparatus includes a memory and a hardware processor. The processor detects that a transaction involving a mobile device occurred. After detecting the transaction, the processor receives, from the mobile device, transaction information about the transaction, the transaction information comprising an identification of a merchant performing the transaction and an identification of a user of the mobile device. The processor receives, from the mobile device, a media file generated by the mobile device during the transaction and links the media file to the transaction information. The processor stores the transaction information and the media file in the memory.

Abstract: Apparatus and methods for protecting biometric authentication information associated with a paper document are provided. A mobile device application may pre-associate the document with a biometric input. The mobile device application may generate a first composite hash value based on a combination of a numerical representation of a first image of the paper document and a numerical representation of a first biometric input. Subsequently, an authentication server may generate a second composite hash value based on a combination of a numerical representation of a second image of the paper document and a numerical representation of a second biometric input. The authentication server may determine whether an edit distance separating the second composite hash value and the first composite hash value is less than a threshold distance. If the edit distance is less than a threshold distance, the paper document may be authenticated.

Abstract: An apparatus includes a memory and a hardware processor. The processor detects that a transaction involving a mobile device occurred. After detecting the transaction, the processor receives, from the mobile device, transaction information about the transaction, the transaction information comprising an identification of a merchant performing the transaction and an identification of a user of the mobile device. The processor receives, from the mobile device, a media file generated by the mobile device during the transaction and links the media file to the transaction information. The processor stores the transaction information and the media file in the memory.

Abstract: In an embodiment of the present disclosure, a biometric identification device comprises a conversion engine configured to receive a key file, receive a biometric file, wherein the biometric file is different from the key file and comprises biometric identification information of a user, convert the key file into a first numeric representation, and convert the biometric file into a second numeric representation. The biometric identification device further comprises a hashing engine configured to create a superimposed numeric representation by performing a convolution operation on the first numeric representation and the second numeric representation, convert the superimposed numeric representation into a hash value, and store the hash value.

Abstract: In an embodiment of the present disclosure, an embodiment includes a user device comprises a conversion engine configured to receive a biometric file comprising biometric identification information of a user and convert the biometric file into a first numeric representation. The user device further comprises a hashing engine configured to create a superimposed numeric representation by performing a convolution operation on the first numeric representation and a second numeric representation, wherein the second numeric representation is based on a key file that is different from the biometric file. The hashing engine is further configured to convert the superimposed numeric representation into a hash value, send, over a network connection, the hash value for authentication, and receive a message indicating whether authentication was successful.

Abstract: A method comprises creating a word vector from a message, wherein the word vector comprises creating a word vector from a message stored in a database, wherein the word vector comprises an entry for each word of the plurality of words and each entry indicating a number of occurrences in the message of the word for that entry. The method further comprising calculating a cosine difference between the word vector and each group vector of a plurality of group vectors and assigning the word vector to a group for a group vector of the plurality of group vectors based on the calculated cosine difference between the word vector and the group vector for the group. The method may also comprise reformatting the message to include a phrase and assigning the phrase to the same group that the word vector is assigned to. The method may also comprise notifying the user.

Abstract: Embodiments of the present invention provide a system for secure transfer of encrypted resources and asynchronous execution. In general, a user initiates an event with a merchant system and requests a secure resource transfer process associated with the event. Encrypted initial event details are transmitted through an asynchronous command form the merchant system to a computing device of the user, and resource information is identified at the computing device of the user. The computing device of the user then transmits the event details and the resource information to an event processing system for final execution.

Abstract: An apparatus includes a memory and a hardware processor. The memory stores one or more scheduling histories. The processor receives a first list from a first client device and a second list from a second client device. The first list includes a first job and the second list includes a second job. The processor calculates a first resource requirement to execute the first job and a second resource requirement to execute the second job. The processor determines that a conflict exists between the first job and the second job and in response, communicates messages to the first and second client devices indicating the conflict and proposed times for executing the jobs. The processor determines based on responses to the messages, execution times for the first and second jobs, assigns permission identifiers to the first and second jobs, and communicates a schedule.

Abstract: In an embodiment of the present disclosure, an embodiment includes a user device comprises a conversion engine configured to receive a biometric file comprising biometric identification information of a user and convert the biometric file into a first numeric representation. The user device further comprises a hashing engine configured to create a superimposed numeric representation by performing a convolution operation on the first numeric representation and a second numeric representation, wherein the second numeric representation is based on a key file that is different from the biometric file. The hashing engine is further configured to convert the superimposed numeric representation into a hash value, send, over a network connection, the hash value for authentication, and receive a message indicating whether authentication was successful.

Abstract: In an embodiment of the present disclosure, a biometric identification device comprises a conversion engine configured to receive a key file, receive a biometric file, wherein the biometric file is different from the key file and comprises biometric identification information of a user, convert the key file into a first numeric representation, and convert the biometric file into a second numeric representation. The biometric identification device further comprises a hashing engine configured to create a superimposed numeric representation by performing a convolution operation on the first numeric representation and the second numeric representation, convert the superimposed numeric representation into a hash value, and store the hash value.

Abstract: A method comprises creating a word vector from a message, wherein the word vector comprises creating a word vector from a message stored in a database, wherein the word vector comprises an entry for each word of the plurality of words and each entry indicating a number of occurrences in the message of the word for that entry. The method further comprising calculating a cosine difference between the word vector and each group vector of a plurality of group vectors and assigning the word vector to a group for a group vector of the plurality of group vectors based on the calculated cosine difference between the word vector and the group vector for the group. The method may also comprise reformatting the message to include a phrase and assigning the phrase to the same group that the word vector is assigned to. The method may also comprise notifying the user.