Abstract: A system may identify, using a machine learning model, a series of recurring events associated with an account and may generate, using the machine learning model, a prediction of a future date on which a predicted event, associated with the series of recurring events, is to occur. The system may determine that a condition associated with the account is satisfied and may determine that a current date is within a threshold number of days of the future date based on the prediction of the future date. The system may transmit, to a user device, a notification based on determining that the current date is within the threshold number of days of the future date and that the condition associated with the account is satisfied, wherein the notification includes information for presentation of an input element that enables an action to be performed in connection with the account.

Abstract: A system may identify, using a machine learning model, a series of recurring events associated with an account and may generate, using the machine learning model, a prediction of a future date on which a predicted event, associated with the series of recurring events, is to occur. The system may determine that a condition associated with the account is satisfied and may determine that a current date is within a threshold number of days of the future date based on the prediction of the future date. The system may transmit, to a user device, a notification based on determining that the current date is within the threshold number of days of the future date and that the condition associated with the account is satisfied, wherein the notification includes information for presentation of an input element that enables an action to be performed in connection with the account.

Abstract: A method is disclosed, comprising: aggregating a plurality of sets of transactions, each set of transactions comprising transactions related to an account-merchant pairing; determining variables characterizing a recurrence period based on transaction dates of the transactions in the each set; predicting the recurrence period for a transaction related to the account-merchant pairing for each customer of the plurality of customers; aggregating another set of transactions between the plurality of customers and the merchant; evaluating a distribution of the recurrence period for each customer within range of a distant point; and based on the evaluation of the distribution of the recurrence period for each customer, generating a probability of the merchant having a recurrent transaction with the customer. The account-merchant pairing may comprise a customer account and a merchant of a plurality of customers and merchants.