Abstract: Systems and methods for authenticating a user are disclosed.

Abstract: The disclosed embodiments provide a system that verifies user attributes. During operation, the system obtains financial data containing a set of strings representing a set of deposits into one or more financial accounts of one or more users. Next, the system generates one or more clusters of the deposits according to a similarity between pairs of strings in the set of strings. For each cluster from the one or more clusters, the system associates a subset of the strings in the cluster with an income source and extracts one or more employment attributes of a user from a subset of the deposits associated with the user in the cluster. Finally, the system uses the one or more employment attributes to provide an automatic verification of an income of the user.

Abstract: Certain aspects of the present disclosure provide techniques for generating a human readable summary explanation to a user for an outcome generated by a complex machine learning model. In one embodiment, a risk assessment service can receive a request from a user in which a risk model of the risk assessment service performs a specific task (e.g., determining the level of risk associated with the user). Once the risk model determines the risk associated with the user, in order to comply with regulations from a compliance system, the risk model can provide a user with an explanation as to the outcome for transparency purposes.

Abstract: The disclosed embodiments provide a system that facilitates electronic communication among users. During operation, the system obtains financial data as a set of financial transactions. Upon receiving a request to transmit a message, the system obtains one or more recipient attributes from the request. Next, the system uses the financial transactions to identify a set of recipients that matches the one or more recipient attributes. The system then transmits the message to the set of recipients without revealing the PII for the set of recipients to a creator of the message.

Abstract: A method and system assist users of an electronic bookkeeping system to sort financial transactions into accounts representing bookkeeping categories. The method and system generate vectors representing the accounts and the merchants known to the bookkeeping system. The method and system generate compressed versions of the vectors by compressing the vectors. The method and system assist users to sort the financial transactions by analyzing the compressed vectors.

Abstract: A method and system assists users of an electronic bookkeeping system to sort financial transactions into accounts representing bookkeeping categories. The method and system generates vectors representing the accounts and the merchants known to the bookkeeping system. The method and system generates compressed versions of the vectors by compressing the vectors. The method and system assists users to sort the financial transactions by analyzing the compressed vectors.

Abstract: Systems and methods for authenticating a user are disclosed.

Abstract: A method and system authenticates a user of a data management system. The method and system store an identification tag in the transaction description for a transaction between the user and the data management system. When the user attempts to access the data management system at a later date, the method and system requests that the user provide access to the transaction description. If the user is able to provide access to a transaction description that includes the identification tag, then the method and system can authenticate the user.

Abstract: A method may include generating a source transaction description, encoding, by an encoder model of a machine translation model executing on a computer processor, the source transaction description to create a context vector, decoding, by a decoder model of the machine translation model, the context vector to predict a target entity description, generating a transaction including the target entity description, detecting an acceptance, by a user, of an action performed on the transaction, in response to detecting the acceptance, updating a translation accuracy metric for the target entity description, determining that the updated translation accuracy metric satisfies a translation accuracy criterion, and in response to determining that the updated translation accuracy metric satisfies the translation accuracy criterion, adding the target entity description to golden entity descriptions.

Abstract: Aspects of the present disclosure provide techniques for training a machine learning model. Embodiments include determining a set of unlabeled user transaction records associated with a user. Embodiments include selecting a first unlabeled user transaction record associated with a first vendor from the set of unlabeled user transaction records based on a transaction record prioritization scheme. Embodiments include presenting the first unlabeled user transaction record to the user in a label query. Embodiments include receiving, from the user in response to the label query, a label of a first account for the first unlabeled user transaction record. Embodiments include selecting a second unlabeled user transaction record associated with a second vendor from the set of unlabeled user transaction records based on: the transaction record prioritization scheme; and a determination that the second vendor is least likely to be categorized by the user in the first account.

Abstract: Certain aspects of the present disclosure provide techniques for generating a human readable summary explanation to a user for an outcome generated by a complex machine learning model. In one embodiment, a risk assessment service can receive a request from a user in which a risk model of the risk assessment service performs a specific task (e.g., determining the level of risk associated with the user). Once the risk model determines the risk associated with the user, in order to comply with regulations from a compliance system, the risk model can provide a user with an explanation as to the outcome for transparency purposes.

Abstract: During a verification technique, claim information for a claim made by an entity (which includes an attribute characterizing an entity) is verified using verification information determined from at least an account of the entity. For example, an individual may pre-register with a provider of the verification technique and authorize the provider to access the account, such as a social network, a financial account, and/or an account associated with a financial application (e.g., an accounting application, an income-tax preparation application, etc.). Subsequently, when the individual makes or provides the claim information associated with the claim, verification information associated with the claim information is aggregated and used to verify that the claim is valid. By verifying the claim, the verification technique may make it easier for individuals to prove their reputable identity attributes without disclosing additional confidential information, thereby maintaining their privacy.

Abstract: A method for presence based mobile payment. The method includes registering, by a mobile payment service, a user based on a request for registration with a mobile payment service, wherein registering includes storing information items identifying the user. The method also includes receiving, from a point of sale system (PoS), an information item from the information items, and a payment authorization for a transaction. The information item is broadcast through an advertising channel by a mobile device to the PoS in accordance with a communication standard without pairing the PoS to the mobile device. The advertising channel is a channel of the communication standard and is used for identification of available nearby devices. The method also includes facilitating, based on the information item and by the mobile payment service, payment for the transaction from an electronic financial account of the user.

Abstract: Certain aspects of the present disclosure provide techniques for determining similarities between businesses. One example method generally includes receiving a similarity query and receiving transaction data associated with a plurality of businesses for comparing the plurality of businesses. The method further includes generating a set of vectors representing the plurality of businesses based on the transaction data and generating a set of compact vectors based on the vectors by applying a dimensionality reduction technique. The method further includes generating based on the set of compact vectors, a similarity index and determining a response to the similarity query using the similarity index.

Abstract: Embodiments disclosed herein relate to a method of writing a transaction to a data store having one or more data tables. An application agent receives transaction data for a first transaction of a first type. Application agent attempts to write the first transaction of the first type to a data table in the data store, provided that a transaction of the first type has been committed to the data store. Application agent scans a plurality of additional data stores for previously committed transactions of the first type Application agent determines additional transactions of another type that are co-located in a data table. Application agent ranks the additional transactions of the other type. Application agent identifies a data table in the data store to which a top ranking additional transaction of the other type has been committed. Application agent writes the first transaction to identified data table in the data store.

Abstract: A method for presence based mobile payment comprises receiving, from a user, a request for registration with a mobile payment service, registering, by the mobile payment service, the user based on the request, broadcasting, by a point of sale (PoS) system and through an advertising channel, an identification of a transaction, wherein the transaction comprises an item, wherein the advertising channel is used for discovery of available devices, and wherein the user is purchasing the item at the PoS system, receiving, from a mobile device of the user, a payment authorization for the transaction, and facilitating, by the mobile payment service, payment for the transaction.

Abstract: Certain aspects of the present disclosure provide techniques for determining similarities between businesses. One example method generally includes receiving a similarity query and receiving transaction data associated with a plurality of businesses for comparing the plurality of businesses. The method further includes generating a set of vectors representing the plurality of businesses based on the transaction data and generating a set of compact vectors based on the vectors by applying a dimensionality reduction technique. The method further includes generating based on the set of compact vectors, a similarity index and determining a response to the similarity query using the similarity index.

Abstract: Certain aspects of the present disclosure provide techniques for detecting and protecting personally identifiable information. In one example, a method includes retrieving a user-specific dataset from a multi-user dataset; filtering the user-specific dataset to create a user-specific data subset; determining a user frequency of each user-specific token of a plurality of user-specific tokens in the user-specific data subset; determining a multi-user frequency for each user-specific token of the plurality of user-specific tokens in the multi-user dataset; computing a frequency ratio based on the user-specific frequency and the multi-user frequency of each user-specific token of the plurality of user-specific tokens; and protecting each user-specific token whose frequency ratio is above a frequency ratio threshold.

Abstract: A system and method for use with a data management service provides automatic assistance of transaction data sorting to an account based on account name inferences. A table is generated from transactions that have been previously sorted to accounts, in which the table contains occurrence frequencies of associations between merchants and accounts. The occurrence frequencies of the table are utilized to analyze an unsorted transaction. The merchant associated with the unsorted transaction is matched to a merchant of the table. The occurrence frequencies of the accounts of the table associated with the matched merchant are determined. The accounts of the table are matched to accounts of the user's chart of accounts. A determined likelihood account is calculated for the unsorted transaction for account sorting.

Abstract: Mobile payments and processing data related to electronic transactions. A near field communication connection is established between a mobile communication device of a consumer that serves as a mobile wallet and an electronic payment device of a merchant. Authorization data is shared between the mobile communication device and the electronic payment device without providing electronic payment instrument (e.g. credit card) data to the merchant. Authorization data is transmitted from the mobile communication device to a cloud computer or resource that serves as a cloud wallet and hosts respective data of respective electronic payment instruments of respective consumers, and from the electronic payment device a payment processor computer. The payment processor computer presents the authorization data to the cloud wallet, and in response, the cloud wallet transmits the credit card data to the payment processor computer, which processes the transaction.