Method, system, and computer program product for applying deep learning analysis to financial device usage

A computer-implemented method for applying deep learning analysis to predict and automatically respond to predicted changes in financial device primacy for a financial device holder, the method comprising:

• receiving, with at least one processor, transaction data representative of a plurality of transactions between the financial device holder and at least one merchant over a first time interval;
• generating, with at least one processor, time series data based on the transaction data, the time series data comprising:
• (i) a plurality of subintervals over the first time interval;
• and (ii) a set of generated statistical parameters for each of the plurality of subintervals, the set of statistical parameters based at least partially on at least one of the following:
• transaction count;
• transaction amount;
• transaction date;
• transaction day of week;
• transaction time of day;
• transaction merchant type;
• or any combination thereof;
• generating, with at least one processor, a predictive convolutional neural network (CNN) model configured to:
• (i) receive an input of time-interval-based transaction data;
• and (ii) output a probability of primary financial device primacy change, wherein the predictive CNN model is trained based on historic transaction data, wherein a financial device with primacy is used more frequently than other financial devices of the financial device holder, and wherein a primacy change comprises one of the following events:
• the financial device holder has a financial device with primacy in the first time interval and has no financial device with primacy in a second time interval;
• the financial device holder has no financial device with primacy in the first time interval and has a financial device with primacy in the second time interval;
• or the financial device holder has a financial device with primacy in the first time interval and has a different financial device with primacy in the second time interval;
• determining, with at least one processor, a probability of primary financial device primacy change for the financial device holder by applying the predictive CNN model to the time series data, wherein applying the predictive CNN model to the time series data comprises using at least one input layer of the predictive CNN model comprising at least part of the time series data associated with the financial device holder for the plurality of subintervals;
• in response to determining that the probability of primary financial device primacy change satisfies a threshold, generating, with at least one processor and based at least partially on the probability of primary financial device primacy change for the financial device holder, at least one communication to at least one issuer and/or the financial device holder;
• receiving, with at least one processor, new transaction data representative of a plurality of transactions between the financial device holder and the at least one merchant over the second time interval;
• generating, with at least one processor, new time series data based on the new transaction data, the new time series data comprising a plurality of subintervals over the second time interval;
• determining, with at least one processor, a new probability of primary financial device primacy change for the financial device holder by applying an updated version of the predictive CNN model to the new time series data, wherein the predictive CNN model is updated in the second time interval at least partially based on at least one prior probability prediction determined from application of the predictive CNN model to prior-generated time series data in the first time interval;
• and
• transmitting, with at least one processor and based at least partially on the new probability of primary financial device primacy change for the financial device holder, at least one of the following:
• (i) the at least one communication to the at least one issuer indicating a likelihood of the financial device holder changing their primary financial device;
• (ii) the at least one communication to the financial device holder to discourage the financial device holder from changing their primary financial device or encourage the financial device holder to change their primary financial device;
• or (iii) any combination thereof.