SECURE EXECUTION OF AN EXCHANGE ITEM ACQUISITION REQUEST

1 . A method for execution by one or more servers of an exchange item marketplace network, the method comprises:

receiving, from a computing device of the exchange item marketplace network, an acquisition request regarding an exchange item of a plurality of exchange items of the exchange item marketplace network;

obtaining user information associated with the computing device and device information associated with the computing device;

selecting a fraud determination approach of a plurality of fraud determination approaches based on the user information and the device information, wherein the selected fraud determination approach includes a traversing nodes of a fraud decision tree;

performing a decision tree analysis function on the fraud decision tree to produce a predicted fraud level for the acquisition request;

determining whether the predicted fraud level compares favorably to a fraud threshold; and

when the predicted fraud level compares favorably to the fraud threshold, facilitating execution of the acquisition request.

2 . The method of claim 1 , wherein the fraud decision tree further comprises:

a plurality of nodes organized in a decision tree structure, wherein the plurality of nodes includes one or more question nodes and one or more end nodes.

3 . The method of claim 2 , wherein the decision tree analysis function traverses through two or more nodes of the plurality of nodes to arrive at an end node of the one or more end nodes, wherein the end node identifies the predicted fraud level.

4 . The method of claim 2 , wherein the decision tree analysis function traverses through two or more nodes of the plurality of nodes to arrive at an end node of the one or more end nodes, wherein each end node of the one or more end nodes is associated with a scoring result.

5 . The method of claim 4 further comprises:

generating a composite fraud score based on summing the scoring result associated with each traversed node of the fraud decision tree; and

determining the predicted fraud level based on the composite fraud score.

6 . The method of claim 2 ,wherein the decision tree analysis function traverses through two or more nodes of the plurality of nodes to arrive at an end node of the one or more end nodes, wherein each node of the plurality of nodes is associated with a pass indication or a fail indication.

7 . The method of claim 6 further comprises:

when a majority of indications are the pass indication, determining the predicted fraud level compares favorably to the fraud threshold.

8 . The method of claim 6 further comprises:

when all indications are the pass indication, determining the predicted fraud level compares favorably to the fraud threshold.

9 . The method of claim 2 , wherein a question node of the one or more question nodes determines whether an IP address associated with the computing device is unique to the computing device.

10 . The method of claim 2 , wherein a question node of the one or more question nodes determines whether an email address age compares favorably to an email age threshold.

11 . The method of claim 2 , wherein a question node of the one or more question nodes determines whether a payment instrument associated with the acquisition request is included in an approved list of payment instruments.

12 . The method of claim 2 , wherein a question node of the one or more question nodes determines whether a transaction amount associated with the acquisition request compares favorably to a transaction threshold.

13 . The method of claim 1 further comprises:

removing the exchange item from a digital marketplace of the exchange item marketplace network; and

adding the exchange item to a digital wallet associated with the computing device.

14 . The method of claim 1 further comprises:

determining to modify a structure of the fraud decision tree based on feedback regarding the executed acquisition request.

15 . The method of claim 14 , wherein the modifying the structure comprises:

substitution of a question node of the nodes of the fraud decision tree.

16 . The method of claim 14 , wherein the modifying the structure comprises:

changing a threshold level for a node of the nodes of the fraud decision tree.

17 . The method of claim 1 , wherein the selecting the fraud determination approach further comprises:

determining the fraud determination approach based on a type of the exchange item.

18 . The method of claim 1 , wherein the selecting the fraud determination approach further comprises:

determining the fraud determination approach based on a risk level associated with a user of the computing device.

19 . The method of claim 1 further comprises:

when the predicted fraud level compares unfavorably to the fraud threshold:

determining whether the predicted fraud level compares favorably to a conditional threshold level; and

when the predicted fraud level compares favorably to a conditional threshold level, issuing a conditional approval of the acquisition request, wherein the conditional approval includes one or more conditions to be met before the execution of the acquisition request is allowed.

20 . The method of claim 1 further comprises:

when the predicted fraud level compares unfavorably to the fraud threshold, denying the acquisition request.