Abstract: Systems and techniques are disclosed for accessing accounts associated with a user and estimating a value of an attribute associated with the user based upon the retrieved account information. Transaction data associated with an account at an external user account system is received. The transactions are categorized into transaction groups. For each transaction group, a confidence value that the group is associated with the attribute is estimated, based at least in part upon a distribution of transaction amounts for the transactions of the group over a time period associated with the group. An attribute value is estimated for each group, based at least in part upon the transaction amounts of the transaction of the group. In addition a value of the attribute for a future time period may be predicted based upon the transaction groups.

Abstract: Systems and techniques are disclosed for accessing accounts associated with a user and estimating a value of an attribute associated with the user based upon the retrieved account information. Transaction data associated with an account at an external user account system is received. The transactions are categorized into transaction groups. For each transaction group, a confidence value that the group is associated with the attribute is estimated, based at least in part upon a distribution of transaction amounts for the transactions of the group over a time period associated with the group. An attribute value is estimated for each group, based at least in part upon the transaction amounts of the transaction of the group. In addition a value of the attribute for a future time period may be predicted based upon the transaction groups.

Abstract: A user account evaluation system is disclosed for evaluating risk associated with a user account. The system may obtain user account data associated with many user accounts, select a statistically significant subset of the user accounts, and then process (e.g., to determine types of the user accounts, etc.) and analyze the subset of user accounts to generate a plurality of evaluation models. When a new user account is accessed by the system, user account data may be obtained for the new user account, and the new user account may be evaluated based on the plurality of evaluation models. Accordingly, a plurality of evaluation parameter scores may be generated for the new user account, each of which may indicate an amount of risk associated with the user account. Some embodiments of the present disclosure may include machine learning and/or artificial intelligence methods to improve evaluation of the user accounts.

Abstract: Systems and techniques are disclosed for accessing accounts associated with a user and estimating a value of an attribute associated with the user based upon the retrieved account information. Transaction data associated with an account at an external user account system is received. The transactions are categorized into transaction groups. For each transaction group, a confidence value that the group is associated with the attribute is estimated, based at least in part upon a distribution of transaction amounts for the transactions of the group over a time period associated with the group. An attribute value is estimated for each group, based at least in part upon the transaction amounts of the transaction of the group. In addition a value of the attribute for a future time period may be predicted based upon the transaction groups.

Abstract: Systems and techniques are disclosed for accessing accounts associated with a user and estimating a value of an attribute associated with the user based upon the retrieved account information. Transaction data associated with an account at an external user account system is received. The transactions are categorized into transaction groups. For each transaction group, a confidence value that the group is associated with the attribute is estimated, based at least in part upon a distribution of transaction amounts for the transactions of the group over a time period associated with the group. An attribute value is estimated for each group, based at least in part upon the transaction amounts of the transaction of the group. In addition a value of the attribute for a future time period may be predicted based upon the transaction groups.

Abstract: A user account evaluation system is disclosed for evaluating risk associated with a user account. The system may obtain user account data associated with many user accounts, select a statistically significant subset of the user accounts, and then process (e.g., to determine types of the user accounts, etc.) and analyze the subset of user accounts to generate a plurality of evaluation models. When a new user account is accessed by the system, user account data may be obtained for the new user account, and the new user account may be evaluated based on the plurality of evaluation models. Accordingly, a plurality of evaluation parameter scores may be generated for the new user account, each of which may indicate an amount of risk associated with the user account. Some embodiments of the present disclosure may include machine learning and/or artificial intelligence methods to improve evaluation of the user accounts.