Systems and methods for proactive fraudster exposure in a customer service channel

1. A computerized method for improved fraudster detection in a call center, the method comprising:

receiving, via a computing device, a plurality of voiceprints from a plurality of interactions between callers and agents at the call center;

determining, via the computer, a subset of the plurality of voiceprints;

determining, via the computer, for each of the plurality of voiceprints, a kth order moment score based on the subset of the plurality of voiceprints;

sorting, via the computer, the plurality of voiceprints by their corresponding kth order moment score to obtain a sorted list of voiceprints;

determining, via the computer, for each of the sorted plurality of voiceprints that are nearby in the sorted list, a clustered voiceprint pair for each pair of nearby voiceprints having a difference between their corresponding kth order moment score within a predetermined tolerance and adding the respective clustered voiceprint pair to a clustered voiceprint pair list;

performing, by the computing device, a first search on the clustered voiceprint pair list to obtain a plurality of connected component voiceprints;

determining, by the computing device, for each of the plurality of connected component voiceprints substantially in parallel, additional voiceprints that are filtered from the respective connected component voiceprint; and

performing, by the computing device, a second search on the clustered voiceprint pair list to obtain a final plurality of connected component voiceprints, wherein each of the final plurality of connected components is an output that represents one or more voiceprints for use in fraud detection.

2. The computerized method of claim 1 wherein the kth order moment score is a mean score and a standard deviation score.

3. The computerized method of claim 2 wherein the sorting is based on the mean score.

4. The computerized method of claim 2 wherein voiceprints that are nearby are voiceprints that are within a fixed window, neighbors, or any combination thereof.

5. The computerized method of claim 2 wherein a clustered voiceprint pair has a difference between corresponding mean score within a mean score threshold.

6. The computerized method of claim 2 further comprising for each of the clustered voiceprint pairs in the clustered voiceprint pair list, if a difference between the corresponding standard deviation scores are above a predetermined threshold, removing, by the computing device, the respective clustered voiceprint pair.

7. The computerized method of claim 1 wherein the first search or the second search is a breadth-first-search, depth-first-search, or any combination thereof.

8. The computerized method of claim 1 wherein the subset of the plurality of voiceprints is based on an input value.

9. The computerized method of claim 1 wherein receiving the plurality of voiceprints further comprises recording calls received at the call center between the callers and agents in an audio file.

10. A non-transitory computer program product comprising instructions which, when the program is executed cause the computer to:

receive a plurality of voiceprints from a plurality of interactions between callers and agents at the call center;

determine a subset of the plurality of voiceprints;

determine for each of the plurality of voiceprints, a kth order moment score based on the subset of the plurality of voiceprints;

sort the plurality of voiceprints by their corresponding kth order moment score to obtain a sorted list of voiceprints;

determine for each of the sorted plurality of voiceprints that are nearby in the sorted list, a clustered voiceprint pair for each pair of nearby voiceprints having a difference between their corresponding kth order moment score within a predetermined tolerance and adding the respective clustered voiceprint pair to a clustered voiceprint pair list;

perform a first search on the clustered voiceprint pair list to obtain a plurality of connected component voiceprints;

determine for each of the plurality of connected component voiceprints substantially in parallel, additional voiceprints that are filtered from the respective connected component voiceprint; and

perform a second search on the clustered voiceprint pair list to obtain a final plurality of connected component voiceprints, wherein each of the final plurality of connected components is an output that represents one or more voiceprints for use in fraud detection.

11. The computer program product of claim 10 wherein the kth order moment score is a mean score and a standard deviation score.

12. The computer program product of claim 11 wherein the sorting is based on the mean score.

13. The computer program product of claim 11 wherein voiceprints that are nearby are voiceprints that are within a fixed window, neighbors, or any combination thereof.

14. The computer program product of claim 11 wherein a clustered voiceprint pair has a difference between corresponding mean score within a mean score threshold.

15. The computer program product of claim 11 further comprising for each of the clustered voiceprint pairs in the clustered voiceprint pair list, if a difference between the corresponding standard deviation scores are above a predetermined threshold, removing, by the computing device, the respective clustered voiceprint pair.

16. The computer program product of claim 10 wherein the first search or the second search is a breadth-first-search, depth-first-search, or any combination thereof.

17. The computer program product of claim 10 wherein the subset of the plurality of voiceprints is based on an input value.

18. The computer program product of claim 10 wherein receiving the plurality of voiceprints further comprises recording calls received at the call center between the callers and agents in an audio file.