Abstract: Systems, methods and products for determining a consumer-facing price using a demand model that is generated based on historical transactional data. One embodiment comprises a method implemented in a pricing module of an automotive data processing system. Data that identifies a consumer (or consumer group) and a vehicle type are received and the demand model is accessed to generate a payment corresponding to the attributes of the consumer and the attributes of the vehicle type. The demand model may be implemented in a machine learning engine that maintains a set of weights ? used in a predictive demand function. The weights are adjusted by the machine learning engine to minimize a loss function which measures deviation of demand estimated by the predictive demand function from the demand indicated by a set of historical transaction data.

Abstract: Systems, methods and products for determining a consumer-facing price using a demand model that is generated based on historical transactional data. One embodiment comprises a method implemented in a pricing module of an automotive data processing system. Data that identifies a consumer (or consumer group) and a vehicle type are received and the demand model is accessed to generate a payment corresponding to the attributes of the consumer and the attributes of the vehicle type. The demand model may be implemented in a machine learning engine that maintains a set of weights ? used in a predictive demand function. The weights are adjusted by the machine learning engine to minimize a loss function which measures deviation of demand estimated by the predictive demand function from the demand indicated by a set of historical transaction data.

Abstract: Systems, methods and products for one embodiment comprises a method including providing a demand model which generates a payment in response to receiving input identifying a consumer profile and a vehicle type. A cashflow model is provided, and in response to receiving the payment output by the demand model and a desired return on a converted vehicle transaction, the cashflow model generates an acquisition price as an output. A comparison engine is provided which, in response to receiving the acquisition price output by the cashflow model, retrieves vehicle inventory records and compares a corresponding purchase price to the acquisition price to determine whether the corresponding vehicle is qualified. A list of qualified vehicles for a given consumer profile and vehicle type is stored and used to generate real time displays of qualified vehicles (with no unqualified vehicles) in response to a request from a specific consumer having this profile.

Abstract: Systems, methods and products for determining a consumer-facing price using a demand model that is generated based on historical transactional data. One embodiment comprises a method implemented in a pricing module of an automotive data processing system. Data that identifies a consumer (or consumer group) and a vehicle type are received and the demand model is accessed to generate a payment corresponding to the attributes of the consumer and the attributes of the vehicle type. The demand model may be implemented in a machine learning engine that maintains a set of weights ? used in a predictive demand function. The weights are adjusted by the machine learning engine to minimize a loss function which measures deviation of demand estimated by the predictive demand function from the demand indicated by a set of historical transaction data.