Systems and methods for debt management with spending recommendation

A computer system for providing a debt management recommendation, the computer system comprising:

• a memory having processor-readable instructions stored therein;
• and
• at least one processor configured to access the memory and execute the processor-readable instructions, which when executed by the processor configures the processor to perform a plurality of functions, including functions for:
• receiving financial information regarding a user;
• categorizing transaction information of the user based on the financial information;
• displaying via a user interface of a user device associated with the user, the categorized transaction information of the user;
• receiving information regarding at least one financial preference and at least one transaction preference of the user via the user device;
• training a machine learning engine based on the at least one financial preference and at least one transaction preference of the user to determine one or more activities available to the user;
• calculating for each of the one or more activities available to the user, an estimated influence on the at least one financial preference;
• displaying via the user interface of the user device, the estimated influence on the at least one financial preference based on a user selected one of the one or more activities available to the user;
• filtering the one or more activities available to the user with a positive estimated influence to the at least one financial preference;
• and
• presenting on the user interface of the user device, a recommendation of action relating to the one of the one or more activities available to the user, wherein the recommendation of action relating to the one of the one or more activities available to the user is presented by at least one of voice notification, application notification, tactile notification, or graphic notification.

A computer-implemented method for providing a debt management recommendation, the method comprising:

• receiving, by one or more processors, financial information regarding a user;
• categorizing, by the one or more processors, a transaction information of the user based on the financial information;
• displaying, by the one or more processors, on a display of a user device, the categorized transaction information of the user;
• requesting, by the one or more processors, the user to enter information regarding at least one financial preference and at least one transaction preference using the user device;
• receiving, by the one or more processors, information regarding the at least one financial preference from the user;
• receiving, by the one or more processors, information regarding the at least one transaction preference from the user;
• assigning, by the one or more processors, an expected value to the at least one transaction preference;
• training, by the one or more processors, a machine learning engine based on the at least one financial preference and at least one transaction preference of the user to determine one or more activities available to the user;
• calculating, by the one or more processors, for each of the one or more activities available to the user, an estimated influence on the at least one financial preference;
• filtering, by the one or more processors, the one or more activities available to the user with a positive estimated influence on the at least one financial preference;
• calculating, by the one or more processors, a value of satisfaction based on a monetary cost of the one or more activities available to the user with positive estimated influence and the expected value;
• ranking, by the one or more processors, the one or more activities available to the user with positive estimated influence based on the value of satisfaction;
• displaying, by the one or more processors, via the display of the user device, the one or more activities available to the user with positive estimated influence;
• and
• recommending, by the one or more processors, one of the one or more activities available to the user with positive estimated influence based on the ranking, wherein the recommendation is presented by at least one of a voice notification, application notification, tactile notification, or graphic notification.