Computer-based systems configured to automatically program a plurality of controls to modify a communication session associated with a transaction and methods of use thereof
In some embodiments, the present disclosure provides an exemplary method that may include steps of accessing a set of data records; receiving an instruction to perform an action; determining input data associated with the instruction; verifying the input data; identifying a pattern of behavior associated with each type of data; converting verified input data of a particular data type into a uniform secure data state; dynamically enabling a communication session between at least two security modules; orchestrating a delay within the communication session; and automatically programming a plurality of controls to modify the communication session.
1 . A computer implemented method comprising:
accessing, by at least one processor, a set of data records associated with a computing device;
receiving, by the at least one processor, an instruction to perform an action via the computing device;
utilizing, by the at least one processor, a processing module to determine input data associated with the instruction to perform the action;
identifying, by the at least one processor and in response to verifying the input data, via a trained machine learning module, a pattern of behavior associated with each type of data over a predetermined period of time;
converting, by the at least one processor, the input data of a particular data type into a uniform secure data state based on an established baseline associated with the pattern of behavior to form a converted input data;
dynamically modifying, by the at least one processor, the converted input data to match output data based on the established baseline associated with the pattern of behavior via a rules engine to form a modified input data;
dynamically enabling, by the at least one processor, a communication session between at least two security modules of a plurality of security modules associated with a plurality of entities based on a dynamic bus architecture associated with each security module;
orchestrating, by the at least one processor, a delay within the communication session between the at least two security modules based on the modified input data and a plurality of thresholds associated with the pattern of behavior associated with each type of data, the delay comprising at least one pause in transmissions of the communication session for a period of time in which the modified input data meets at least one predetermined threshold of the plurality of thresholds based at least in part on the pattern of behavior of each type of data;
automatically programming, by the at least one processor, a plurality of controls to modify the communication sessions based on the delay associated with the at least one predetermined threshold,
wherein the plurality of controls comprise at least one control associated with a time of the type of data and at least one control associated with a value of the type of data,
wherein the at least one predetermined threshold is based on a respective type of data and a respective value of data associated with the modified input data;
automatically executing, by the at least one processor, the communication session based on the delay in relation to the trained machine learning module; and
displaying, by the at least one processor, the communication session between the at least two security modules via a graphical user interface housed on a computing device associated with a user.
2 . The method of claim 1 , wherein the processing module comprises determining a plurality of types of data and respective values in real-time for each type of data.
3 . The method of claim 1 , wherein a first security module of the plurality of security modules transmits a data packet associated with the uniform secure data state to a second security module of the plurality of security modules.
4 . The method of claim 1 , wherein the plurality of controls comprise at least one control associated with a time of the type of data and at least one control associated with a value of the type of data.
5 . The method of claim 1 , wherein the plurality of thresholds are based on the respective type and value of data associated with the input data.
6 . The method of claim 1 , further comprising:
generating, by the at least one processor, a notification detailing a conversion displayed via a graphic user interface housed on the computing device associated with the user;
utilizing, by the at least one processor, an operations console device to instruct subsequent transactions based on the conversion of the verified input data;
receiving, by the at least one processor, a second instruction via the computing device;
utilizing, by the at least one processor, a rules engine to collect market input to modify the converted input data to match market output data based on an established baseline associated with the output of the previous transaction; and
generating, by the at least one processor, a printed notification detailed modified input data based on the market output data.
7 . The method of claim 6 , wherein a service works engine generates the notification detailing the conversion.
8 . A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by a device, perform a method comprising:
accessing, by at least one processor, a set of data records associated with a computing device;
receiving, by the at least one processor, an instruction to perform an action via the computing device;
utilizing, by the at least one processor, a processing module to determine input data associated with the instruction to perform the action;
identifying, by the at least one processor and in response to verifying the input data, via a trained machine learning module, a pattern of behavior associated with each type of data over a predetermined period of time;
converting, by the at least one processor, the input data of a particular data type into a uniform secure data state based on an established baseline associated with the pattern of behavior to form a converted input data;
dynamically modifying, by the at least one processor, the converted input data to match output data based on the established baseline associated with the pattern of behavior via a rules engine to form a modified input data;
dynamically enabling, by the at least one processor, a communication session between at least two security modules of a plurality of security modules associated with a plurality of entities based on a dynamic bus architecture associated with each security module;
orchestrating, by the at least one processor, a delay within the communication session between the at least two security modules based on the modified input data and a plurality of thresholds associated with pattern of behavior associated with each type of data, the delay comprising at least one pause in transmissions of the communication session for a period of time in which the modified input data meets a predetermined threshold;
automatically programming, by the at least one processor, a plurality of controls to modify the communication sessions based on the delay associated with the at least one predetermined threshold;
automatically executing, by the at least one processor, the communication session based on the delay in relation to the trained machine learning module; and
displaying, by the at least one processor, the communication session between the at least two security modules via a graphical user interface housed on a computing device associated with a user.
9 . The non-transitory computer-readable storage medium of claim 8 , wherein the processing module comprises determining a plurality of types of data and respective values in real-time for each type of data.
10 . The non-transitory computer-readable storage medium of claim 8 , wherein a first security module of the plurality of security modules transmits a data packet associated with the uniform secure data state to a second security module of the plurality of security modules.
11 . The non-transitory computer-readable storage medium of claim 8 , wherein the plurality of controls comprise at least one control associated with a time of the type of data and at least one control associated with a value of the type of data.
12 . The non-transitory computer-readable storage medium of claim 8 , wherein the plurality of thresholds are based on the respective type and value of data associated with the input data.
13 . The non-transitory computer-readable storage medium of claim 8 , further comprising:
generating, by the at least one processor, a notification detailing a conversion displayed via a graphic user interface housed on the computing device associated with the user;
utilizing, by the at least one processor, an operations console device to instruct subsequent transactions based on the conversion of the verified input data;
receiving, by the at least one processor, a second instruction via the computing device;
utilizing, by the at least one processor, a rules engine to collect market input to modify the converted input data to match market output data based on an established baseline associated with the output of the previous transaction; and
generating, by the at least one processor, a printed notification detailed modified input data based on the market output data.
14 . The non-transitory computer-readable storage medium of claim 13 , wherein a service works engine generates the notification detailing the conversion.
15 . A system comprising:
a non-transient computer memory, storing software instructions;
at least one processor of a computing device associated with a user;
wherein, when the at least one processor executes the software instructions, the computing device is programmed to:
access a set of data records associated with the computing device;
receive an instruction to perform an action via the computing device;
utilize a processing module to determine input data associated with the instruction to perform the action;
identify, in response to verifying the input data, via a trained machine learning module, a pattern of behavior associated with each type of data over a predetermined period of time;
convert the input data of a particular data type into a uniform secure data state based on an established baseline associated with the pattern of behavior to form a converted input data;
dynamically modify the converted input data to match output data based on the established baseline associated with the pattern of behavior via a rules engine to form a modified input data;
dynamically enable a communication session between at least two security modules of a plurality of security modules associated with a plurality of entities based on a dynamic bus architecture associated with each security module;
orchestrate a delay within the communication session between the at least two security modules based on the modified input data and a plurality of thresholds associated with the pattern of behavior associated with each type of data, the delay comprising at least one pause in transmissions of the communication session for a period of time in which the modified input data meets at least one predetermined threshold of the plurality of thresholds based at least in part on the pattern of behavior of each type of data;
automatically program a plurality of controls to modify the communication sessions based on the delay associated with the at least one predetermined threshold of the plurality of thresholds,
wherein the plurality of controls comprise at least one control associated with a time of the type of data and at least one control associated with a value of the type of data,
wherein the at least one predetermined threshold is based on a respective type of data and a respective value of data associated with the modified input data;
automatically execute the communication session based on the delay in relation to the trained machine learning module; and
display the communication session between the at least two security modules via a graphical user interface housed on a computing device associated with a user.
16 . The system of claim 15 , wherein the processing module comprises determining a plurality of types of data and respective values in real-time for each type of data.
17 . The system of claim 15 , wherein a first security module of the plurality of security modules transmits a data packet associated with the uniform secure data state to a second security module of the plurality of security modules.
18 . The system of claim 15 , wherein the plurality of controls comprise at least one control associated with a time of the type of data and at least one control associated with a value of the type of data.
19 . The system of claim 15 , wherein the plurality of thresholds are based on the respective type and value of data associated with the input data.
20 . The system of claim 15 , wherein the software instructions further comprise:
generate a notification detailing a conversion displayed via a graphic user interface housed on the computing device associated with the user;
utilize an operations console device to instruct subsequent transactions based on the conversion of the verified input data;
receive a second instruction via the computing device;
utilize a rules engine to collect market input to modify the converted input data to match market output data based on an established baseline associated with the output of the previous transaction; and
generate a printed notification detailed modified input data based on the market output data.