Methods, systems and computer readable media for determining criminal propensities in a geographic location based on purchase card transaction data

A system for determining criminal propensities in a geographic location based on purchase card transaction data, the system comprising:

• a criminal offense data repository configured to store criminal activity data;
• a purchase card transaction data repository configured to store purchase card transaction data;
• and
• a processing server configured to:
• obtain, from the purchase card transaction data repository, purchase card transaction data associated with purchase card transactions conducted during a designated time period to determine a plurality of first normalized regional expenditure indices corresponding to a plurality of industry categories for a first geographic location,
• generate an algorithmic model based on correlations between each of the first normalized regional expenditure indices and a plurality of criminal offense types committed during the designated time period, wherein the plurality of criminal offense types is included in the criminal activity data obtained from the criminal offense data repository, and
• apply the algorithmic model to each of a plurality of second normalized regional expenditure indices corresponding to the plurality of industry categories associated with a second geographic location in order to determine a criminal propensity indicator in the second geographic location for each of the plurality of criminal offense types.

A non-transitory computer readable medium having stored thereon executable instructions for controlling a computer to perform steps comprising:

• utilizing purchase card transaction data associated with purchase card transactions conducted during a designated time period to determine a plurality of first normalized regional expenditure indices corresponding to a plurality of industry categories for a first geographic location;
• generating an algorithmic model based on correlations between each of the first normalized regional expenditure indices and a plurality of criminal offense types committed during the designated time period;
• and
• applying the algorithmic model to each of a plurality of second normalized regional expenditure indices corresponding to the plurality of industry categories associated with a second geographic location in order to determine a criminal propensity indicator in the second geographic location for each of the plurality of criminal offense types.