Artificial intelligence payment timing models

A device for modifying an obligation of a debtor based upon a predicted payment date, the device comprising:

• a hardware processor;
• a memory, storing instructions, which when executed by the hardware processor, causes the hardware processor to perform operations comprising:
• training a prediction model using a gradient boosted tree machine-learning algorithm based on a training data set comprising a plurality of features including past payment history of a plurality of debtors on debt accounts and information about non-debt accounts of the plurality of debtors, the training data including at least one non-numerical feature, the training comprising converting the non-numerical features into a binary vector with each position of the binary vector representing a possible value of the non-numerical features, the prediction model comprising one or more data structures;
• determining past payment history information of the debtor;
• determining account history of a non-debt account of the debtor;
• determining the predicted payment date using the past payment history information and the account history of the non-debt account of the debtor as inputs to the prediction model;
• and
• automatically causing a modification to a debtor payment schedule related to the debt, the modification based upon the predicted payment date, the modification changing a timing of future payments due to align with the predicted payment date.

A non-transitory machine-readable medium, storing instructions for modifying an obligation of a debtor based upon a predicted payment date, the instructions, which when executed by a machine, causes the machine to perform operations comprising:

• training a prediction model using a gradient boosted tree machine-learning algorithm based on a training data set comprising a plurality of features including past payment history of a plurality of debtors on debt accounts and information about non-debt accounts of the plurality of debtors, the training data including at least one non-numerical feature, the training comprising converting the non-numerical features into a binary vector with each position of the binary vector representing a possible value of the non-numerical features, the prediction model comprising one or more data structures;
• determining past payment history information of the debtor;
• determining account history of a non-debt account of the debtor;
• determining the predicted payment date using the past payment history information and the account history of the non-debt account of the debtor as inputs to the prediction model;
• and
• automatically causing a modification to a debtor payment schedule related to the debt, the modification based upon the predicted payment date, the modification changing a timing of future payments due to align with the predicted payment date.