Abstract: In some aspects, a machine-learning model, which can transform input attribute values into a predictive or analytical output value, can be trained with training data grouped into attributes. A subset of the attributes can be selected and transformed into a transformed attribute used for training the model. The transformation can involve grouping portions of the training data for the subset of attributes into respective multi-dimensional bins. Each dimension of a multi-dimensional bin can correspond to a respective selected attribute. The transformation can also involve computing interim predictive output values. Each interim predictive output value can be generated from a respective training data portion in a respective multi-dimensional bin. The transformation can also involve computing smoothed interim output values by applying a smoothing function to the interim predictive output values.

Abstract: An online identity can be verified based on data from multiple identity sources stored in a blockchain. For example, a request for a token is received from an entity for authenticating an online identity of the entity to an online service. The request can be stored in a blockchain that represents the online identity of the entity by adding a new block to the blockchain. The new block can include data indicating the request for the token. The token can be generated based on the one or more ordered blocks in the blockchain. The token can be transmitted to the entity. The token can be received from the online service. Confirmation of the online identity of the entity can be transmitted to the online service based on receiving the token from the online service.

Abstract: A telecommunications network server system provides a digital identifier to a user device. The digital identifier may include identification data corresponding to a user of the user device. In addition, the telecommunications network server system receives, from one or more third-party systems, requests to authenticate the user for an electronic transaction with the respective third-party system. The telecommunications network server system provides a unique electronic transaction code to each third-party system. Responsive to receiving from the user device one of the unique electronic transaction codes, the telecommunications network server system provides, to the respective third-party system, authentication of the user.

Abstract: Certain aspects involve facilitating the integration of sensitive data from a data provider into an instance of a web-based, third-party application. For example, a data provider service can receive an authentication API call from a third-party system. The authentication API call can include a user identifier and a request for an access token usable by a web-based interface of the third-party system. The data provider service can generate an access token for the third-party system from which the authentication API call is received. The data provider service can subsequently receive, from the user device, a feature API call including the access token and a feature request for sensitive data. The data provider service can generate output data specific to the user identified by the access token included in the feature API call. The data provider service can provide the output to the user device via the web-based interface.

Abstract: In some aspects, a computing system can generate and optimize a neural network for risk assessment. The neural network can be trained to enforce a monotonic relationship between each of the input predictor variables and an output risk indicator. The training of the neural network can involve solving an optimization problem under a monotonic constraint. This constrained optimization problem can be converted to an unconstrained problem by introducing a Lagrangian expression and by introducing a term approximating the monotonic constraint. Additional regularization terms can also be introduced into the optimization problem. The optimized neural network can be used both for accurately determining risk indicators for target entities using predictor variables and determining explanation codes for the predictor variables. Further, the risk indicators can be utilized to control the access by a target entity to an interactive computing environment for accessing services provided by one or more institutions.

Abstract: Certain aspects involve optimizing neural networks or other models for assessing risks and generating explanatory data regarding predictor variables used in the model. In one example, a system identifies predictor variables compliant with certain monotonicity constraints. The system generates a neural network for determining a relationship between each predictor variable and a risk indicator. The system performs a factor analysis on the predictor variables to determine common factors. The system iteratively adjusts the neural network so that (i) a monotonic relationship exists between each common factor and the risk indicator and (ii) a respective variance inflation factor for each common factor is sufficiently low. Each variance inflation factor indicates multicollinearity among a subset of the predictor variables corresponding to a common factor.

Abstract: Certain aspects involve building and debugging models for generating source code executed on data-processing platforms. A target data-processing platform is identified that requires bin ranges for modeling coefficients and reason codes for input attributes. A processor outputs source code, which is generated from a modeling code, in a programming language used by the target data-processing platform.

Abstract: Systems and methods are provided for providing data security. Credit-related data provided by a credit database can be received. The credit-related data can include records. Each record can include a social security number and a name associated with the social security number. Each record can be transformed to generate transformed data using a hashing algorithm. An electronic communication comprising content can be received. Transformed content can be generated by transforming the content. The transformed content can be compared to the transformed data. The transformed content can be determined to match at least one of the transformed records. The electronic communication can be prevented from being transmitted to a network.

Abstract: Computer-implemented systems and methods for networks that transmit credit, non-credit or identity related alert messages or other identity related messages relating to a secondary person, minor, or other person to a primary person's device. According to certain embodiments, two or more consenting adults, such as, for example, spouses, can have identity related messages relating to their credit status, and in some cases minors' credit status, transmitted to the device of the other person or persons as well as their own device. Each individual's device is able to communicate with the system in order to control what identity related messages the system transmits to their devices, as well as to devices of the other adult. In some embodiments, the system automatically terminates transmitting messages if a fraud event occurs. Each individual's device is also able to terminate transmission of such messages to devices of the other adult.

Abstract: Aspects and examples are disclosed for providing compressed risk assessment messages for real-time transmission to online services. For example, a request for a compressed risk assessment message about an entity is received from an online service. The compressed risk assessment message is generated by executing a risk assessment algorithm with at least some data about the entity. The compressed risk assessment message indicates a risk associated with the entity. The risk is indicated using less data than a detailed risk assessment generated by the risk assessment system, which may include an explanation indicating how the risk is determined. The compressed risk assessment message is transmitted to an online service that requests the compressed risk assessment. In some aspects, a detailed risk assessment is generating using the risk assessment algorithm, and, subsequent to transmitting the compressed risk assessment message, is transmitted to the online service.

Abstract: Certain embodiments involve generating or optimizing a neural network for risk assessment. The neural network can be generated using a relationship between various predictor variables and an outcome (e.g., a condition's presence or absence). The neural network can be used to determine a relationship between each of the predictor variables and a risk indicator. The neural network can be optimized by iteratively adjusting the neural network such that a monotonic relationship exists between each of the predictor variables and the risk indicator. The optimized neural network can be used both for accurately determining risk indicators using predictor variables and determining adverse action codes for the predictor variables, which indicate an effect or an amount of impact that a given predictor variable has on the risk indicator. The neural network can be used to generate adverse action codes upon which consumer behavior can be modified to improve the risk indicator score.

Abstract: Aspects and examples are disclosed for facilitating mobile commerce. In one example, a processing device receives a data network identifier or other identifier from a commerce application. The data network identifier or other identifier can be associated with a mobile device conducting a transaction with the commerce application. The processing device can also obtain a credential associated with the mobile device using the data network identifier. The processing device can additionally retrieve identification information from a credit file associated with the credential. The identification information can be useable for completing the transaction. The processing device can further transmit the identification information to a computing device executing the commerce application.

Abstract: Aspects and examples are disclosed for facilitating and signaling market transactions between providers of products or services and clients that consume or otherwise use the products and services. In one example, a processing device of a server system receives, via a data network, data from a computing system describing attributes of a client that uses the computing system. The processing device can verify at least some of the received data to generate a client profile for the client. Based on verifying the data in the client profile, the processing device can notify one or more providers of a product or service that the client is interested in the product or service. Notifications to providers of the product or service can maintain the anonymity of the client. Notifications to the providers can also identify a client type, the client's propensity to purchase or access certain products or services, etc.

Abstract: Certain aspects involve facilitating the integration of sensitive data from a data provider into an instance of a web-based, third-party application. For example, a data provider service can receive an authentication API call from a third-party system. The authentication API call can include a user identifier and a request for an access token usable by a web-based interface of the third-party system. The data provider service can generate an access token for the third-party system from which the authentication API call is received. The data provider service can subsequently receive, from the user device, a feature API call including the access token and a feature request for sensitive data. The data provider service can generate output data specific to the user identified by the access token included in the feature API call. The data provider service can provide the output to the user device via the web-based interface.

Abstract: Reducing risks associated with network usage is provided. Variable information is extracted from network activity log data that includes a request from a user in an organization for content from a network content source. The variable information includes a number of times that the network content source has been requested, a volume of organization users that have made a request from the network content source, and a period of time for which traffic with respect to the network content source has been detected. The variable information is scored to generate a risk score. An access control level is determined for the network content source based on the risk score and a content access policy for the organization. Access of the user in the organization to the network content source is controlled according to the access control level.

Abstract: Computer-implemented systems and methods for networks that transmit credit, non-credit or identity related alert messages or other identity related messages relating to a secondary person, minor, or other person to a primary person's device. According to certain embodiments, two or more consenting adults, such as, for example, spouses, can have identity related messages relating to their credit status, and in some cases minors' credit status, transmitted to the device of the other person or persons as well as their own device. Each individual's device is able to communicate with the system in order to control what identity related messages the system transmits to their devices, as well as to devices of the other adult. The system automatically terminates transmitting messages if a fraud event occurs. Each individual's device is also able to terminate transmission of such messages to devices of the other adult.