SYSTEMS AND METHODS FOR DETERMINING RISK OF IDENTITY FRAUD BASED ON MULTIPLE FRAUD DETECTION MODELS
A fraud risk determination system that provides a comprehensive approach to multiple different types of fraud that outputs a single identity fraud risk score based on dynamically combining several independent fraud component models which employ various analytical techniques.
1 . A fraud risk determination system comprising:
a processor; and
a memory device that stores a plurality of instructions that, when executed by the processor responsive to an initiated transaction, cause the processor to:
receive transaction data associated with an entity,
for each of a plurality of different fraud component models, determine, based on at least a portion of the received transaction data, an individual fraud predictor associated with that fraud component model, wherein each individual fraud predictor is determined independent of each of the other individual fraud predictors,
determine, based on a dynamic weighting of each of the determined individual fraud predictors associated with each of the fraud component models, a single identity fraud risk score associated with the entity, and
cause a display, by a display device, of the determined single identity fraud score associated with the entity.
2 . The fraud risk determination system of claim 1 , wherein the transaction data associated with the entity comprises personal identifying information associated with the entity.
3 . The fraud risk determination system of claim 1 , wherein the transaction data associated with the entity comprises inquiry data associated with the entity.
4 . The fraud risk determination system of claim 1 , wherein the transaction data associated with the entity comprises population segment data associated with the entity.
5 . The fraud risk determination system of claim 1 , wherein at least one of the fraud component models comprises a true name fraud component model.
6 . The fraud risk determination system of claim 1 , wherein at least one of the fraud component models comprises a synthetic fraud component model.
7 . The fraud risk determination system of claim 1 , wherein at least one of the fraud component models comprises a fraud rules optimization fraud component model.
8 . The fraud risk determination system of claim 1 , wherein at least one of the fraud component models comprises a fraud susceptibility fraud component model.
9 . The fraud risk determination system of claim 1 , wherein the dynamic weighting of each of the determined individual fraud predictors associated with each of the fraud component models comprises weighting a first individual fraud predictor determined for a first of the fraud component models more than a second, different individual fraud predictor determined for a second, different of the fraud component models.
10 . The fraud risk determination system of claim 9 , wherein the first individual fraud predictor is associated with a greater probability of a fraud being committed than the second, different individual fraud predictor.
11 . A method of operating a fraud risk determination system responsive to an initiated transaction, the method comprising:
receiving transaction data associated with an entity,
for each of a plurality of different fraud component models, determining, by a processor and based on at least a portion of the received transaction data, an individual fraud predictor associated with that fraud component model, wherein each individual fraud predictor is determined independent of each of the other individual fraud predictors,
determining, by the processor and based on a dynamic weighting of each of the determined individual fraud predictors associated with each of the fraud component models, a single identity fraud risk score associated with the entity, and
displaying, by a display device, the determined single identity fraud score associated with the entity.
12 . The method of claim 11 , wherein the transaction data associated with the entity comprises personal identifying information associated with the entity.
13 . The method of claim 11 , wherein the transaction data associated with the entity comprises inquiry data associated with the entity.
14 . The method of claim 11 , wherein the transaction data associated with the entity comprises population segment data associated with the entity.
15 . The method of claim 11 , wherein at least one of the fraud component models comprises a true name fraud component model.
16 . The method of claim 11 , wherein at least one of the fraud component models comprises a synthetic fraud component model.
17 . The method of claim 11 , wherein at least one of the fraud component models comprises a fraud rules optimization fraud component model.
18 . The method of claim 11 , wherein at least one of the fraud component models comprises a fraud susceptibility fraud component model.
19 . The method of claim 11 , wherein the dynamic weighting of each of the determined individual fraud predictors associated with each of the fraud component models comprises weighting, by the processor, a first individual fraud predictor determined for a first of the fraud component models more than a second, different individual fraud predictor determined for a second, different of the fraud component models.
20 . The method of claim 19 , wherein the first individual fraud predictor is associated with a greater probability of a fraud being committed than the second, different individual fraud predictor.
21 . The fraud risk determination system of claim 1 , wherein a first determined single identity fraud score associated with the entity is displayed as a first color and a second, different determined single identity fraud score associated with the entity is displayed as a second, different color.
22 . The fraud risk determination system of claim 1 , wherein the memory device stores a plurality of further instructions that, when executed by the processor responsive to a receipt of data associated with an input to display at least one of the determined individual fraud predictors, cause the processor to cause a display, by the display device, of that at least one of the determined individual fraud predictors.
23 . The method of claim 11 , wherein a first determined single identity fraud score associated with the entity is displayed as a first color and a second, different determined single identity fraud score associated with the entity is displayed as a second, different color.
24 . The method of claim 11 , further comprising, responsive to a receipt of data associated with an input to display at least one of the determined individual fraud predictors, displaying, by the display device, that at least one of the determined individual fraud predictors.