User authentication based on account transaction information in text field

A computing device comprising:

• one or more processors;
• and
• memory storing instructions that, when executed by the one or more processors, cause the computing device to:
• receive, from a user device, a request for access to an account;
• determine, based on a geographical location associated with the user device, training data indicating a plurality of merchants and popularity of each of the plurality of merchants in the geographical location;
• generate, based on the training data, a trained machine learning model by training a machine learning model implemented using an artificial neural network comprising a plurality of nodes to predict a guessability of an input merchant, wherein the training the machine learning model comprises adjusting, based on the training data, one or more weights corresponding to one or more of the plurality of nodes of the artificial neural network;
• receive transaction data associated with the account, wherein the transaction data indicates a plurality of transactions, and wherein each transaction of the plurality of transactions is associated with a merchant;
• present, via a user interface of the user device, an authentication question that prompts a user to identify one or more merchants indicated by the transaction data;
• receive, via the user interface of the user device and in response to the authentication question, a user response comprising text data;
• process the text data to identify at least one merchant;
• and
• based on determining that at least one transaction of the plurality of transactions is associated with the at least one merchant:
• provide, to the trained machine learning model, input data indicating the at least one merchant;
• receive, from the trained machine learning model and in response to the input data, output data indicating a guessability of the at least one merchant;
• generate, based on the output data, an authentication score;
• and
• provide, to the user device and based on the authentication score, access to the account.

One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause a computing device to:

• receive, from a user device, a request for access to an account;
• determine, based on a geographical location associated with the user device, training data indicating a plurality of merchants and popularity of each of the plurality of merchants in the geographical location;
• generate, based on the training data, a trained machine learning model by training a machine learning model implemented using an artificial neural network comprising a plurality of nodes to predict a guessability of an input merchant, wherein the training the machine learning model comprises adjusting, based on the training data, one or more weights corresponding to one or more of the plurality of nodes of the artificial neural network;
• receive transaction data associated with the account, wherein the transaction data indicated a plurality of transactions, and wherein each transaction of the plurality of transactions is associated with a merchant;
• present, via a user interface of the user device, an authentication questions that prompts a user to identify one or more merchants indicated by the transaction data;
• process the text data to identify at least one merchant;
• and
• based on determining that at least one transaction of the plurality of transactions is associated with the at least one merchant:
• provide, to the trained machine learning model, input data indicating the at least one merchant;
• receive, from the trained machine learning model and in response to the input data, output data indicating a guessability of the at least one merchant;
• generate, based on the output data, an authentication score;
• and
• provide, to the user device and based on the authentication score, access to the account.