Customizable intermediary platform for connecting entities

A system for dynamic selection of systems when routing electronic requests to reduce latencies, the system comprising:

• one or more processors;
• a non-transitory computer-readable medium storing instructions that, when executed by at least one processor among the one or more processors, cause the at least one processor to perform operations comprising:
• receiving, from a first entity, an electronic request corresponding to a request for information stored by a first institution;
• identifying a routing context associated with the electronic request, the routing context corresponding to aspects of the request that are involved in determining routing choices;
• determining a plurality of service provider devices that have an association with the first institution based on the routing context;
• identifying a plurality of network operation events generated within a period of time in response to a plurality of electronic requests processed by the plurality of devices during the period of time;
• aggregating the plurality of events into a plurality of time windows associated with the period of time, where each network operation event is aggregated with a respective time window of the plurality of time windows based on a time of occurrence of each network operation;
• executing a machine learning model to determine a data protection attribute by providing profile data associated with a user profile to the machine learning model to cause the machine learning model to generate an output indicating the data protection attribute and an importance level of data protection associated with the user profile;
• calculating a performance metric for each device of the plurality of devices corresponding to the service providers in each of the plurality of time windows, the performance metric representing a weighted sum that is based on at least one weighted performance factor, the weighted performance factor representing data of the service providers communicated by the plurality of service provider devices when executing the plurality of electronic requests within the plurality of time windows, and at least one weighted preference factor, the weighted preference factor representing the data protection attribute weighted according to the importance level of data protection;
• determining one time window of the plurality of time windows associated with the electronic request based on a time of receipt associated with the electronic request;
• and
• responsive to determining a routing choice that optimizes execution of the electronic request within the one time window of the plurality of time windows, based at least on the performance metric, the routing choice indicating a device of a first service provider of the plurality of service providers that satisfies the at least one weighted performance factor and the data protection attribute weighted according to the importance level of data protection, routing the electronic request to the device of a first service provider based on a current time, the routing context, and the routing choice.

A non-transitory machine-readable medium comprising instructions which, when read by a machine, cause the machine to perform operations for dynamic selection of systems when routing electronic requests to reduce latencies, the operations comprising:

• receiving, from a first entity, an electronic request from a device of a first entity, the electronic request corresponding to a request for information stored by a first institution;
• identifying a routing context associated with the electronic request, the routing context corresponding to aspects of the request that are involved in determining routing choices;
• determining a plurality of service provider devices that have an association with the first institution based on the routing context;
• identifying a plurality of network operation events generated within a period of time in response to a plurality of electronic requests processed by the plurality of devices during the period of time;
• aggregating the plurality of events into a plurality of time windows associated with the period of time, where each network operation event is aggregated with a respective time window of the plurality of time windows based on a time of occurrence of each network operation;
• executing a machine learning model to determine a data protection attribute by providing profile data associated with a user profile to the machine learning model to cause the machine learning model to generate an output indicating the data protection attribute and an importance level of data protection associated with the user profile;
• calculating a performance metric for each service provider in each of the plurality of time windows, the performance metric representing a weighted sum that is based on at least one weighted performance factor, the weighted performance factor representing data of the service providers communicated by the plurality of service provider devices when executing the plurality of electronic requests within the plurality of time windows, and at least one weighted preference factor, the weighted preference factor representing the data protection attribute weighted according to the importance level of data protection;
• determining one time window of the plurality of time windows associated with the electronic request based on a time of receipt associated with the electronic request;
• and
• responsive to determining a routing choice that optimizes execution of the electronic request within the one time window of the plurality of time windows based at least on the performance metric, the routing choice indicating a device of a first service provider of the plurality of service providers that satisfies the at least one weighted performance factor and the data protection attribute weighted according to the importance level of data protection, routing the electronic request to the device of the first service provider based on a current time, the routing context, and the routing choice.