Systems and methods for detecting fraudulent requests on client accounts
A method for detecting a fraud attempt in a communication session may include receiving, via at least one processor, a set of data associated with a communication session between a representative of an organization and a user, tagging, via the at least one processor, one or more items of the set of data as one or more tagged data items, applying, via the at least one processor, a fraud detecting algorithm to the one or more tagged data items to determine a percent likelihood of the user attempting to defraud the representative, generating, via the at least one processor, a visualization based on the percent likelihood, and displaying, via the at least one processor, the visualization via an electronic display during the communication session.
1. A non-transitory computer-readable medium comprising computer-executable instructions, when executed, are configured to cause at least one processor to:
receive a notification indicative of suspicious activity occurring in a communication that is currently being conducted between a representative associated with an organization and an individual contacting the organization concerning an account;
analyze the communication currently being conducted with respect to expected web traffic data associated with the individual;
determine whether the communication is associated with a fraud method based on the analysis;
determine a lifecycle stage of the fraud method being used to access the account based on mobile application hit data associated with an additional individual authorized to access the account, email traffic data associated with the additional individual, a password reset being performed for the additional individual, a number of questions asked during the communication, or a combination thereof, wherein a stage in the lifecycle stage comprises no attack in progress, an attack has been initiated, the attack is advancing, the attack being nearly complete, the account is taken over, or the account is damaged; and
send an alert indicative of the fraud method and the lifecycle stage of the fraud method to a computing device associated with the additional individual authorized to access the account.
2. The non-transitory computer-readable medium of claim 1 , wherein the expected web traffic data is indicative of how the individual accessed the representative.
3. The non-transitory computer-readable medium of claim 1 , wherein the computer-executable instructions, when executed, are configured to determine whether the communication is associated with the fraud based on comparing the communication to the expected web traffic data.
4. The non-transitory computer-readable medium of claim 1 , wherein the expected web traffic data comprises a list of one or more websites, one or more social media links, or both.
5. The non-transitory computer-readable medium of claim 1 , wherein the expected web traffic data comprises a list of one or more organizations that are affiliated with the organization.
6. The non-transitory computer-readable medium of claim 5 , wherein the one or more organizations are affiliated with the organization based on one or more geographical properties, one or more industry-related properties, one or more global properties, one or more national properties, one or more local properties, one or more regional properties, one or more news-related properties, one or more social segments, or any combination thereof.
7. The non-transitory computer-readable medium of claim 1 , wherein the computer-executable instructions, when executed, are configured to cause the at least one processor to determine the lifecycle stage of the fraud method based on information provided in a historical fraudulent activity database.
8. A method for detecting a fraud attempt in a communication session, comprising:
receiving, via a computing system, a notification indicative of suspicious activity occurring in a communication that is currently being conducted between a representative associated with an organization and an individual contacting the organization concerning an account;
analyzing, via the computing system, the communication currently being conducted with respect to expected web traffic data associated with the individual;
determining, via the computing system, whether the communication is associated with a fraud method based on the analysis;
determining, via the computing system, a lifecycle stage of the fraud method being used to access the account based on mobile application hit data associated with an additional individual authorized to access the account, email traffic data associated with the additional individual, a password reset being performed for the additional individual, a number of questions asked during the communication, or a combination thereof, wherein a stage in the lifecycle stage comprises no attack in progress, an attack has been initiated, the attack advancing, the attack being nearly complete, the account is taken over, or the account is damaged; and
sending, via the computing system, an alert indicative of the fraud method and the lifecycle stage of the fraud method to a computing device associated with the additional individual authorized to access the account.
9. The method of claim 8 , wherein the expected web traffic data is indicative of how the individual accessed the representative.
10. The method of claim 8 , wherein the communication associated with the fraud method is determined based on comparing the communication to the expected web traffic data.
11. The method of claim 10 , wherein the expected web traffic data comprises a list of one or more websites, one or more social media links, or both.
12. The method of claim 10 , wherein the expected web traffic data comprises a list of one or more organizations that are affiliated with the organization.
13. The method of claim 12 , wherein the one or more organizations are affiliated with the organization based on one or more geographical properties, one or more industry-related properties, one or more global properties, one or more national properties, one or more local properties, one or more regional properties, one or more news-related properties, one or more social segments, or any combination thereof.
14. The method of claim 8 , wherein the lifecycle stage of the fraud method is determined based on information provided in a historical fraudulent activity database.
15. A fraud detection system, comprising:
one or more databases comprising a plurality of transaction datasets associated with a plurality of financial accounts; and
a processor configured to:
receive a notification indicative of suspicious activity occurring in a communication that is currently being conducted between a representative associated with an organization and an individual contacting the organization concerning an account;
analyze the communication currently being conducted with respect to expected web traffic data associated with the individual;
determine whether the communication is associated with a fraud method based on the analysis;
determine a lifecycle stage of the fraud method being used to access the account based on mobile application hit data associated with an additional individual authorized to access the account, email traffic data associated with the additional individual, a password reset being performed for the additional individual, a number of questions asked during the communication, or a combination thereof, wherein a stage in the lifecycle stage comprises no attack in progress, an attack has been initiated, the attack advancing, the attack being nearly complete, the account is taken over, or the account is damaged; and
send an alert indicative of the fraud method and the lifecycle stage of the fraud method to a computing device associated with the additional individual authorized to access the account.
16. The fraud detection system of claim 15 , wherein the expected web traffic data is indicative of how the individual accessed the representative.
17. The fraud detection system of claim 15 , wherein the communication associated with the fraud method is determined based on comparing the communication to the expected web traffic data.
18. The fraud detection system of claim 17 , wherein the expected web traffic data comprises a list of one or more websites, one or more social media links, or both.
19. The fraud detection system of claim 17 , wherein the expected web traffic data comprises a list of one or more organizations that are affiliated with organization.
20. The fraud detection system of claim 15 , wherein the lifecycle stage of the fraud method is determined based on information provided in a historical fraudulent activity database.