UNAUTHORIZED EVENT DETECTION USING AN APPLICATION PROGRAMMING INTERFACE (API)

1 . A computer-implemented method, comprising:

receiving, by a server system, event data generated by a platform system, the event data associated with a request;

determining, by the server system, a network type associated with the request, the network type indicating a network through which the event data associated with the request are sent from the platform system to the server system;

in response to determining the network type, computing, by the server computer system, feature data from a set of event data and outcome data associated with the network type;

generating, by the server system, one or more prediction datasets based on the computed feature data indicative of whether the request is fraudulent.

2 . The method of claim 1 , wherein the request comprises a request to perform a service, and the network type is determined based on whether the server computer system or a third-party system is to perform the service.

3 . The method of claim 2 , wherein the server computer system is to perform the service when the event data is transmitted in a first API message received through a first API endpoint of the server system, and the third-party system is to perform the service when the event data is transmitted in a second API message received through a second API endpoint of the server system.

4 . The method of claim 1 , further comprises:

storing, by the server system in a data store, the event data with a network key indicative of the determined network type;

receiving, by the server system from the platform system, outcome data associated with a result of a third-party system processing the request; and

storing the outcome data with the network key indicative of the determined network type.

5 . The method of claim 4 , wherein the outcome data comprises an indication that the request was rejected by the third-party system or accepted by the third-party system.

6 . The method of claim 1 , further comprising:

transmitting, by the server system, the one or more prediction datasets to the platform system when the network type indicates a first network; and

transmitting, by the server system, the one or more prediction datasets to service processing system of the server system when the network type indicates a second network.

7 . The method of claim 1 , wherein computing the feature data comprises:

in response to determining that the network type indicates a first network, invoking, by the server system, a first machine learning (ML) model or a first set of rules to compute first feature data for the event data from a set of event data and outcome data associated with the event data and having the same network type; and

in response to determining that the network type indicates a second network, invoking, by the server system, a second ML model or a second set of rules to compute second feature data for the event data from the set of event data and outcome data associated with the event data and having the same network type.

8 . The method of claim 7 , wherein generating the one or more prediction datasets comprises:

invoking, by the server system, a third ML model to generate a prediction dataset based on the computed first feature data and the computed second feature data.

9 . The method of claim 7 , wherein generating the one or more prediction datasets comprises:

invoking, by the server system, a third ML model to generate a first prediction dataset based on the computed first feature data;

invoking, by the server system, a fourth ML model to generate a second prediction dataset based on the computed second feature data; and

combining, by the server system, the first prediction dataset and the second prediction dataset into a final prediction dataset.

10 . One or more non-transitory computer readable storage media having instructions stored thereupon which, when executed by a server system having at least a processor and a memory therein, cause the server system to perform operations, the operations comprising:

receiving, by the server system, event data generated by a platform system, the event data associated with a request;

determining, by the server system, a network type associated with the request, the network type indicating a network through which the event data associated with the request are sent from the platform system to the server system;

in response to determining the network type, computing, by the server computer system, feature data from a set of event data and outcome data associated with the network type;

generating, by the server system, one or more prediction datasets based on the computed feature data indicative of whether the request is fraudulent.

11 . The non-transitory computer readable storage media of claim 10 , wherein the request comprises a request to perform a service, and the network type is determined based on whether the server computer system or a third-party system is to perform the service.

12 . The non-transitory computer readable storage media of claim 11 , wherein the server computer system is to perform the service when the event data is transmitted in a first API message received through a first API endpoint of the server system, and the third-party system is to perform the service when the event data is transmitted in a second API message received through a second API endpoint of the server system.

13 . The non-transitory computer readable storage media of claim 10 , wherein the operations further comprise:

storing, by the server system in a data store, the event data with a network key indicative of the determined network type;

receiving, by the server system from the platform system, outcome data associated with a result of a third-party system processing the request; and

storing the outcome data with the network key indicative of the determined network type.

14 . The non-transitory computer readable storage media of claim 10 , wherein the operations further comprise:

transmitting, by the server system, the one or more prediction datasets to the platform system when the network type indicates a first network; and

transmitting, by the server system, the one or more prediction datasets to service processing system of the server system when the network type indicates a second network.

15 . The non-transitory computer readable storage media of claim 10 , wherein the operations further comprise:

in response to determining that the network type indicates a first network, invoking, by the server system, a first machine learning (ML) model or a first set of rules to compute first feature data for the event data from a set of event data and outcome data associated with the event data and having the same network type; and

in response to determining that the network type indicates a second network, invoking, by the server system, a second ML model or a second set of rules to compute second feature data for the event data from the set of event data and outcome data associated with the event data and having the same network type.

16 . A server system, comprising:

a memory; and

a processor coupled with the memory configured to perform operations comprising:

receiving, by the server system, event data generated by a platform system, the event data associated with a request;

determining, by the server system, a network type associated with the request, the network type indicating a network through which the event data associated with the request are sent from the platform system to the server system;

in response to determining the network type, computing, by the server computer system, feature data from a set of event data and outcome data associated with the network type; and

generating, by the server system, one or more prediction datasets based on the computed feature data indicative of whether the request is fraudulent.

17 . The server system of claim 16 , wherein the request comprises a request to perform a service, and the network type is determined based on whether the server computer system or a third-party system is to perform the service.

18 . The server system of claim 16 , wherein the server computer system is to perform the service when the event data is transmitted in a first API message received through a first API endpoint of the server system, and the third-party system is to perform the service when the event data is transmitted in a second API message received through a second API endpoint of the server system.

19 . The server system of claim 16 , wherein the operations further comprise:

storing, by the server system in a data store, the event data with a network key indicative of the determined network type;

receiving, by the server system from the platform system, outcome data associated with a result of a third-party system processing the request; and

storing the outcome data with the network key indicative of the determined network type.

20 . The server system of claim 16 , wherein the operations further comprise:

transmitting, by the server system, the one or more prediction datasets to the platform system when the network type indicates a first network; and

transmitting, by the server system, the one or more prediction datasets to service processing system of the server system when the network type indicates a second network.