Computer-based systems configured to dynamically generate authentication steps to perform an ameliorative action and methods of use thereof

A computer-implemented method comprising:

• obtaining, by at least one processor, a permission from a particular user to monitor a plurality of activities executed within the mobile device;
• continually monitoring, by the at least one processor, the plurality of activities executed within the mobile device for a predetermined period of time;
• receiving, by the at least one processor, input data from at least two external data sources of a plurality of external data sources, wherein the external data source is a mobile network operator;
• utilizing, by the at least one processor, a trained machine learning algorithm to identify at least one data signal within the input data, wherein the at least one data signal is associated with a particular interaction parameter associated with the particular user;
• automatically verifying, by the at least one processor, the identity of the at least one data signal based on a comparison to a repository of telecommunication data associated with the particular interaction parameter, wherein the repository of telecommunication data is generated by a plurality of data servers compiling information;
• utilizing, by the at least one processor, an initiation protocol-specific backbone engine to determine that the at least one data signal fails to match the comparison of the repository of telecommunication data associated with the particular interaction parameter;
• automatically updating, by the at least one processor, the repository of telecommunication data associated with the particular interaction parameter with a failure to match associated with the at least one digital signal;
• utilizing, by the at least one processor, the trained machine learning algorithm to calculate at least one confidence score associated with at least one factor of risk of a plurality of factors of risk, wherein the at least one factor of risk is associated with the at least one external data source;
• dynamically aggregating, by the at least one processor, each confidence score to calculate an overall confidence score associated with the at least one digital signal;
• dynamically generating, by the at least one processor, at least one authentication step to be performed by the particular user requesting a high-risk activity associated with the at least one digital signal based on the overall confidence score meeting or exceeding a predetermined threshold of risk;
• automatically blocking, by the at least one processor, an initiation to an interaction session associated with the at least one digital signal in response to a failure by the particular user to complete the at least one authentication step;
• and
• transmitting, by the at least one processor, via at least one graphical user interface (GUI) having at least one GUI programmable element within a computing device a request for at least one unique identifier associated with the particular user, wherein the request for the at least one unique identifier is at least one authentication step.

A system may include:

• a non-transient computer memory, storing software instructions;
• and
• at least one processor of a first computing device associated with a user;
• wherein, when the at least one processor executes the software instructions, the first computing device is programmed to:
• receive, by the at least one processor, input data from at least two external data sources of a plurality of external data sources;
• utilize, by the at least one processor, a trained machine learning algorithm to identify at least one data signal within the input data;
• automatically verify, by the at least one processor, the identity of the at least one data signal based on a comparison to a repository of telecommunication data associated with the particular interaction parameter;
• utilize, by the at least one processor, an initiation protocol-specific backbone engine to determine that the at least one data signal fails to match the comparison of the repository of telecommunication data associated with the particular interaction parameter;
• automatically update, by the at least one processor, the repository of telecommunication data associated with the particular interaction parameter with a failure to match associated with the at least one digital signal;
• utilize, by the at least one processor, the trained machine learning algorithm to calculate at least one confidence score associated with at least one factor of risk of a plurality of factors of risk;
• dynamically aggregate, by the at least one processor, each confidence score to calculate an overall confidence score associated with the at least one digital signal;
• dynamically generate, by the at least one processor, at least one authentication step to be performed by the particular user requesting a high-risk activity associated with the at least one digital signal based on the overall confidence score meeting or exceeding a predetermined threshold of risk;
• and
• automatically block, by the at least one processor, an initiation to an interaction session associated with the at least one digital signal in response to a failure by the particular user to complete the at least one authentication step.