Systems and methods for tracking consumer electronic spend behavior to predict attrition

A system of tracking consumer spend behavior to predict attrition, comprising a data storage device storing instructions for tracking consumer spend behavior to predict attrition;

• and a processor configured to execute the instructions to perform a method including:
• receiving, in a database associated with a profiler computing system, environmental and/or behavioral data associated with transaction data of a consumer;
• generating, by a processor of the profiler computing system, a spend behavior model of the consumer based on an analysis of the environmental and/or behavioral data associated with the transaction data of the consumer;
• receiving, in the database associated with the profiler computing system by way of a networked user device, transaction data of one or more current payment transactions of the consumer;
• generating, by an electronic transaction processor, payment tokens based on the transaction data of one or more current payment transactions of the consumer;
• affiliating, by the electronic transaction processor, the one or more current payment transactions of the consumer to one or more of the payment tokens;
• determining, by the processor of the profiler computing system, based on the spend behavior model, a current spend behavior of the consumer, the current spend behavior including habitually purchasing from a merchant and/or group of merchants;
• identifying, by the processor of the profiler computing system, based on the spend behavior model and the payment tokens, one or more anomalous transactions among the one or more current payment transactions associated with one or more of the payment tokens;
• determining a missed payment transaction that is otherwise predicted to occur based on the spend behavior model by comparing the current spend behavior with the spend behavior model;
• and
• determining, by the processor of the profiler computing system, based on the missed payment transaction, a likelihood of an attrition of the current spend behavior.

A non-transitory machine-readable medium stores instructions that, when executed by profiler computing system, causes the profiler computing system to perform a method for tracking consumer spend behavior to predict attrition, the method comprising:

• receiving, in a database associated with a profiler computing system, environmental and/or behavioral data associated with transaction data of a consumer;
• generating, by a processor of the profiler computing system, a spend behavior model of the consumer based on an analysis of the environmental and/or behavioral data associated with the transaction data of the consumer;
• receiving, in the database associated with the profiler computing system by way of a networked user device, transaction data of one or more current payment transactions of the consumer;
• generating, by an electronic transaction processor, payment tokens based on the transaction data of one or more current payment transactions of the consumer;
• affiliating, by the electronic transaction processor, the one or more current payment transactions of the consumer to one or more of the payment tokens;
• determining, by the processor of the profiler computing system, based on the spend behavior model, a current spend behavior of the consumer, the current spend behavior including habitually purchasing from a merchant and/or group of merchants;
• identifying, by the processor of the profiler computing system, based on the spend behavior model and the payment tokens, one or more anomalous transactions among the one or more current payment transactions associated with one or more of the payment tokens;
• determining a missed payment transaction that is otherwise predicted to occur based on the spend behavior model by comparing the current spend behavior with the spend behavior model;
• and
• determining, by the processor of the profiler computing system, based on the missed payment transaction, a likelihood of an attrition of the current spend behavior.