Systems and methods relate to an automated teller machine (ATM) associated with a provider institution computer system. The ATM system includes a processor and a memory having instructions thereon that cause the processor to: receive, via an input device and in a first instance, a first user input from a user of the ATM regarding a first transaction; identify at least: one or more factors associated with the user, and user account data; in a second instance subsequent to the first instance, provide a second transaction including one or more products, the products determined based on at least the factors associated with the user and the user account data; and cause a graphical user interface (GUI) of the ATM to display the products. The ATM may also include a storage repository to store non-monetary media and a card preparation apparatus to convert the non-monetary media into a transaction media.

Predictive analysis for potential future security events may be performed using machine learning and an artificial intelligence model. Machine learning may be based on historical security event data, and analyzed on micro and macro levels to determine possible future events and a likelihood that those future events may occur. Further, machine learning and artificial intelligence models may be used to determine mitigation strategies to address possible future events.

Having an option for credit card users, at the time of sale, when paying with credit or debit card, to have the store receipt included with, their monthly statement and/or emailed to the email address(es) attached to their financial institution account, the method is comprised of a point-of-sale system that registers goods and/or services, comprising a receipt, and the credit card number of user, the point of sale systems sends data to the credit approval system, upon approval the point of sales information is either sent immediately to the server associated with the credit card, or is sent to who a local server who later sends the data to appropriate credit card server, the credit card server sends the data to the credit card's financial institution who saves the receipt under the credit card user's account, and then includes the receipt in the credit card users statements.

Predictive analysis for potential future security events may be performed using machine learning and an artificial intelligence model. Machine learning may be based on historical security event data, and analyzed on micro and macro levels to determine possible future events and a likelihood that those future events may occur. Further, machine learning and artificial intelligence models may be used to determine mitigation strategies to address possible future events.