| CPC G06Q 30/0631 (2013.01) [G06N 3/04 (2013.01); G06N 5/04 (2013.01)] | 16 Claims |

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1. A method comprising:
generating, by a server, a training dataset comprising historical monetary data associated with a set of accounts comprising account activity of each account indicating whether each account within the set of accounts included a negative cash flow, a depth of the negative cash flow, and a duration of the negative cash flow;
training, by the server, an artificial intelligence model using the training dataset;
retrieving, by the server, a monetary attribute associated with an account of a user;
executing, by the server, the artificial intelligence model to predict a first value indicating a negative cash flow in the account of the user, a second value indicating a depth of the negative cash flow, and a third value indicating a duration of the negative cash flow;
identifying, by the server, the first value, the second value, or the third value as correct predictions;
training, by the server, the artificial intelligence model based on the correct predictions; and
transmitting, by the server, an indication that at least one of the first value, the second value, or the third value satisfies a threshold.
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