Electronic data verification routing using artificial intelligence
Disclosed herein are systems and methods for identifying and transmitting electronic requests to a suitable service provider. In one method, a server receives, from a computing device, a request to verify data via at least one service provider; executes a first computer model to identify a likelihood of verification success of the data; responsive to the likelihood of verification success satisfying a threshold, executes a second computer model to determine a service provider to transmit the request based on a first attribute associated with the data, a type of verification associated with the request, and a second attribute associated with the set of service providers and an impact value associated with each service provider; and responsive to determining the service provider from the set of service providers, transmitting, by the processor via an application programming interface, the data to the service provider.
1 . A method of reducing latency in electronic verification systems by dynamically selecting a service provider computer of a set of service provider computers using an artificial intelligence computer model to improve routing efficiency across networked computing environments for sequential request routing techniques, the method comprising:
receiving, by a processor from a computing device, a request to verify data comprising an uploaded document via at least one service provider computer of the set of service provider computers;
executing, by the processor, a character recognition protocol to detect text of the uploaded document;
determining, by the processor, a document type associated with the uploaded document based on the detected text of the uploaded document;
generating, by the processor, a first attribute based on whether the document type matches a type of verification associated with the request to verify data;
executing, by the processor, a first computer model to identify a likelihood of verification success of the data based on the first attribute;
responsive to determining that verifying the data via the set of service provider computers will reduce latency of the request to verify data based on the likelihood of verification success satisfying a first threshold corresponding to a minimum acceptable likelihood of verification success and not satisfying a second threshold corresponding to a maximum acceptable likelihood of verification beyond which routing to at least one service provider would not improve latency:
executing, by the processor, the artificial intelligence computer model to determine a service provider computer from the set of service provider computers to transmit the request based on a respective score associated with each service provider computer, the artificial intelligence computer model being previously trained to identify a score for each service provider using historical verification data and to identify the service provider computer to which to transmit the request, each respective score corresponding to a type of verification associated with the request, the first attribute indicating whether the document type matches the type of verification, a latency value associated with the set of service provider computers, and an impact value associated with each service provider computer, wherein the artificial intelligence computer model is configured to reduce the latency of satisfying the request; and
identifying, by the processor, the service provider computer from the set of service provider computers with a respective score corresponding to a reduction in the latency associated with satisfying the request.
2 . The method of claim 1 , wherein the first computer model determines the likelihood of verification success of the data using at least one of:
an attribute of a user operating the computing device,
the first attribute associated with the data,
a timestamp associated with the request,
historical verification data associated with the user,
historical verification data associated with at least one service provider, or
the type of verification associated with the request.
3 . The method of claim 1 , further comprising:
executing, by the processor, an optical character recognition protocol to identify the first attribute.
4 . The method of claim 1 , wherein the artificial intelligence computer model further uses data associated with a previous request transmitted to one or more service providers.
5 . The method of claim 1 , wherein the impact value corresponds to a cost associated with verification of the request by each service provider.
6 . The method of claim 1 , further comprising:
responsive to the latency value of the service provider computer falling below a threshold, executing, by the processor, the artificial intelligence computer model to determine a second service provider computer among the set of service provider computers to transmit the request to; and
routing, by the processor via an application programming interface, the data to the second service provider computer.
7 . The method of claim 1 , wherein at least one of the first threshold or the second threshold is dynamically updated based on a performance metric of at least one service provider computer.
8 . A method for training an artificial intelligence computer model to dynamically select a service provider computer of a set of service provider computers for routing in electronic verification systems to improve routing efficiency across networked computing environments for sequential request routing techniques, the method comprising:
generating, by a processor, a training dataset by monitoring training data associated with a request routing processor configured to receive a request to verify data comprising an uploaded document and to transmit the data to at least one service provider from a set of service providers, the training dataset comprising:
a set of requests received by the request routing processor, each request comprising data to be verified;
a first attribute for each request within the training dataset, the first attribute generated based on executing a character recognition protocol to detect text of an uploaded document associated with each request, determining a document type of each uploaded document based on the detected text, and determining whether the document type matches a type of verification associated with each request within the training dataset;
a likelihood of verification success for each request within the training dataset, the likelihood of verification success generated based on the request routing processor executing a first computer model;
a score generated based on the request routing processor executing an artificial intelligence computer model that is configured to use a type of verification associated with each request, the first attribute indicating whether the document type matches the type of verification, a latency value associated with each service provider, and an impact value associated with each service provider to generate the score; and
a routing selection, by the request routing processor, to at least one service provider to perform the verification based on the score and the likelihood of verification success satisfying a first threshold corresponding to a minimum acceptable likelihood of verification success and not a second threshold corresponding to a maximum acceptable likelihood of verification beyond which routing to at least one service provider would not improve latency; and
training, by the processor, the artificial intelligence computer model using the training dataset, wherein the artificial intelligence computer model is configured to receive a new request to verify new data and determine a service provider computer from the set of service provider computers to transmit the request based on a respective score associated with each service provider computer, the artificial intelligence computer model being previously trained to identify a score for each service provider using historical verification data and to identify the service provider computer with a shortest verification time to which to transmit the request, each respective score corresponding to a type of verification associated with the request, a first attribute indicating whether the document type matches a type of verification, a latency value associated with the set of service provider computers, and an impact value associated with each service provider computer, wherein the artificial intelligence computer model is configured to reduce latency of satisfying the request.
9 . The method of claim 8 , wherein the processor and the request routing processor belong to a same organization.
10 . The method of claim 8 , wherein the artificial intelligence computer model is further configured to predict a likelihood of verification success for the new request.
11 . The method of claim 8 , wherein the artificial intelligence computer model is further configured to predict a score associated with at least one service provider verifying the new data.
12 . The method of claim 8 , wherein the impact value corresponds to a cost associated with verification of the request by each service provider.
13 . The method of claim 8 , wherein at least one of the first threshold or the second threshold is dynamically updated based on a performance metric of at least one service provider computer.
14 . A system for using an artificial intelligence computer model to improve routing efficiency of data verification requests among a set of service provider computers by reducing latency of data verification, the system comprising:
a non-transitory computer-readable medium having a set of instructions that when executed by a processor, cause the processor to:
receive, from a computing device, a request to verify data comprising an uploaded document via at least one service provider computer of the set of service provider computers;
execute a character recognition protocol to detect text of the uploaded document;
determine a document type associated with the uploaded document based on the detected text of the uploaded document;
generate a first attribute based on whether the document type matches a type of verification associated with the request to verify data;
execute, a first computer model to identify a likelihood of verification success of the data;
responsive to the likelihood of verification success satisfying a first threshold corresponding to a minimum acceptable likelihood of verification success and not satisfying a second threshold corresponding to a maximum acceptable likelihood of verification beyond which routing to at least one service provider would not improve latency:
execute the artificial intelligence computer model to determine a service provider computer from the set of service provider computers to transmit the request based on a respective score associated with each service provider computer, the artificial intelligence computer model being previously trained to identify a score for each service provider using historical verification data and to identify the service provider computer to which to transmit the request, each respective score corresponding to a type of verification associated with the request, the first attribute indicating whether the document type matches a type of verification, a latency value associated with the set of service provider computers, and an impact value associated with each service provider computer, wherein the artificial intelligence computer model is configured to reduce the latency of satisfying the request; and
determine the service provider computer from the set of service provider computers with a respective score corresponding to a reduction in the latency associated with satisfying the request.
15 . The system of claim 14 , wherein the first computer model determines the likelihood of verification success of the data using at least one of:
an attribute of a user operating the computing device,
the first attribute associated with the data,
a timestamp associated with the request,
historical verification data associated with the user,
historical verification data associated with at least one service provider, or
the type of verification associated with the request.
16 . The system of claim 14 , wherein the set of instructions further cause the processor to:
execute an optical character recognition protocol to identify the first attribute.
17 . The system of claim 14 , wherein the artificial intelligence computer model further uses data associated with a previous request transmitted to one or more service providers.
18 . The system of claim 14 , wherein the impact value corresponds to a cost associated with verification of the request by each service provider.
19 . The system of claim 14 , wherein at least one of the first threshold or the second threshold is dynamically updated based on a performance metric of at least one service provider computer.