System, method and computer program product for assessing risk of identity theft
In one embodiment, this invention analyzes demographic data that is associated with a specific street address when presented as an address change on an existing account or an address included on a new account application when that address is different from the reference address (e.g., a credit bureau type header data). The old or reference address and the new address, the new account application address or fulfillment address demographic attributes are gathered, analyzed, compared for divergence and scaled to reflect the relative fraud risk.
1. A computerized method for a client to assess a risk of fraud, comprising: receiving at a server information relating to a first address of one of an account holder or an applicant; receiving at the server information relating to a second address of the account holder or applicant, the server comprising a processor and a memory to store the first address information and the second address information as computer readable media, wherein the processor is configured by an algorithm to: access one or more third party databases to determine data related to each of the first address and the second address, the data comprising at least one of demographic data, United States Postal Service (USPS) data, previous history file data, warm address data, address velocity data and known fraud address data; append the determined data to the first address and the second address; compare the determined data for the first address with the determined data for the second address to determine one or more difference variables; assign a weight to each of the one or more difference variables and calculate a score based on the assigned weight to each of the one or more difference variables using artificial intelligence technology; predict the risk of fraud and calculate a level of risk of fraud based on the calculated score for each of the one or more difference variables; and communicate the level of risk of fraud to the client through (the) a software application user interface by one or more notifications in substantially real time.
2. The method of claim 1 , wherein the score is calculated for each of the one or more difference variables by using a mathematical model comprising one or more pre-defined weighing factors for each of the one or more difference variables.
3. A computer-implemented method for a client to assess a risk of identity theft fraud with respect to new applications, comprising: receiving at a server information for a first address corresponding to the new application of an applicant for an account, the server comprising a processor and a memory to store the first address information as computer readable media, wherein the processor is configured by an algorithm to: obtain a reference address from a third party database; assess one or more databases to determine data related to each of the first address and the reference address, the data comprising at least one of demographic data, United States Postal Service (USPS) data, previous history file data, warm address data, address velocity data, high risk address data and known fraud address data; append the determined data to the first address and the reference address; compare the determined data for the first address with the determined data for the reference address to determine one or more difference variables; assign a weight to each of the one or more difference variables and calculate a score based on the assigned weight to each of the one or more difference variables using artificial intelligence technology; predict the risk of fraud and calculates a level of risk of fraud based on the calculated score for each of the one or more difference variables; and communicate the level of risk of fraud to the client through (the) a software application user interface by one or more notifications sent in substantially real time.
4. The method of claim 3 , wherein the third party database is a credit bureau database.
5. The method of claim 3 , wherein the processor further analyzes a negative data for the first address at an assessment stage.
6. The method of claim 5 , wherein the assessment stage includes assessing the risk of the identity theft fraud based on the score and analysis of the negative data.
7. The method of claim 3 , wherein the at least one demographic data comprises a demographic data related to income, a demographic census data, a demographic data relating to housing characteristics and a data related to household membership characteristics.
8. The method of claim 3 , wherein the high risk address data includes addresses of mail receiving agents, jails, prisons, hotels and motels are the warm address data.
9. The method of claim 3 , wherein the one or more difference variables are determined by at least one of:
comparing financial make-ups of the first address and the reference address to determine a financial make-up variable;
identifying a third party record that matches the first address with a name of the applicant to determine a third party variable;
comparing a home values of the first address and the reference address to determine a home value variable;
determining a distance between the first address and the reference address to determine a distance variable;
comparing a types of housing of the first address and the reference address to determine a housing type variable;
comparing the first address and the reference address to a warm address file to determine a warm address variable;
comparing an Internet usage data for the first address and the reference address to determine an Internet usage variable; and
determining a length of residence for the reference address to determine a length of residence variable.