Abstract: The disclosure provides embodiments for potentially reducing and/or preventing head trauma. Headgear apparatuses comprise a head-protection component configured to be worn over a head and to protect the head from an external force. In certain embodiments, the headgear apparatus has an effective mass of at least 5 kg. In other embodiments, the head-protection component is a form-fitting structure, wherein a maximum distance the head-protection component extends from an exterior surface of the head is less than 5 cm. The head-protection component may be interconnected with a neck support and a body support, wherein the head-protection component, the neck support, and the body support comprise a single structure made of a semi-flexible foam material coated in a latex or vinyl composition.

Abstract: The disclosure provides embodiments for potentially reducing and/or preventing head trauma. Headgear apparatuses comprise a head-protection component configured to be worn over a head and to protect the head from an external force. In certain embodiments, the headgear apparatus has an effective mass of at least 5 kg. In other embodiments, the head-protection component is a form-fitting structure, wherein a maximum distance the head-protection component extends from an exterior surface of the head is less than 5 cm. The head-protection component may be interconnected with a neck support and a body support, wherein the head-protection component, the neck support, and the body support comprise a single structure made of a semi-flexible foam material coated in a latex or vinyl composition.

Abstract: Disclosed is a system for reducing computational costs associated with predicting demand for products. The system typically includes a network comprising a processor and a memory storing a pricing database, a prediction rules module, a server, and a dynamic cannibalization module. The system identifies a first financial product and a plurality of competing financial products, groups the first financial product with one or more of the competing financial products based on business constraints and cannibalization analysis, and then determines an ideal price point for the first financial product based on the group of competing financial products. The invention retains the accuracy of an exhaustive system while significantly reducing the computational costs associated with such an exhaustive system.

Abstract: According to one embodiment of the present invention, a system stores a plurality of matrices. The system determines each relationship between a customer and an enterprise, wherein the enterprise comprises a plurality of customers having at least one relationship with the enterprise. The system generates a relationship flow matrix that includes customer relationship transitions with the enterprise during a first time period. The system calculates a probability of a change in the customer relationship with the enterprise according to a plurality of snapshots of the relationship flow matrices. The system generates a transition probability matrix based on the probability of the change in the customer relationship occurring. The system determines a current number of customers in each relationship with the enterprise. The system generates a current distribution matrix based on the current number of customers in each relationship with the enterprise.

Abstract: Disclosed is a customer centric system for predicting the demand for purchase loan products. The system typically includes a customer profile database storing a plurality of customer profiles reflecting a plurality of hypothetical shopping customers, a purchase loan product profile database storing a plurality of competing purchase loan product profiles reflecting a plurality of hypothetical competing purchase loan products, and a prediction rules module storing a plurality of rules for determining how each hypothetical shopping customer makes a purchase loan decision. The system also typically includes a prediction module configured for predicting the demand volume of shopping customers for a purchase loan product during a predetermined period of time by simulating the purchase loan decision of each hypothetical shopping customer and predicting the demand volume of non-shopping customers for the purchase loan product during the predetermined period of time.

Abstract: Embodiments of the present invention relate to apparatuses, systems, methods, and computer program products for determining an optimal price recommendation. In one embodiment, a system comprises a processor configured to: (a) predict one or more values of relative strength index based on one or more price changes; (b) determine a curve for predicted relative strength index as a function of price change; (c) use elasticity models to determine values of market share based on the predicted values of relative strength index to thereby determine a market share as a function of price change curve; (d) determine a curve for total revenue as a function of price change curve; (e) determine an optimal price or an optimal price change for the entity based at least partially on a value associated with a peak of the curve for total revenue as the function of price change.

Abstract: Embodiments of the present invention relate to apparatuses, systems, methods, and computer program products for determining competitor prices. In one embodiment, a system comprises a processor configured to: (a) receive information identifying pricing strategy for each of the plurality of entities, where the pricing strategy comprises at least one variable for a price selection method; (b) randomly generate initial values for the at least one variable for the price selection method to thereby generate a plurality of pricing strategies; (c) determine a value of fitness for each of the plurality of pricing strategies; (d) select pricing strategies from among the plurality of pricing strategies having a value of fitness that satisfy a predetermined criteria; (e) use a genetic algorithm to randomly modify a portion of the initial values for the at least one price selection method; and (f) determine that the plurality of pricing strategies is satisfactory.

Abstract: Disclosed is a customer centric system for predicting the demand for loan refinancing products. The system typically includes a customer profile database storing a plurality of customer profiles reflecting a plurality of hypothetical shopping customers, a loan refinancing product profile database storing a plurality of competing loan refinancing product profiles reflecting a plurality of hypothetical competing loan refinancing products, and a prediction rules module storing a plurality of rules for determining how each hypothetical shopping customer makes a loan refinancing decision. The system also typically includes a prediction module configured for predicting the demand volume of shopping customers for a loan refinancing product during a predetermined period of time by simulating the loan refinancing decision of each hypothetical shopping customer and predicting the demand volume of non-shopping customers for the loan refinancing product during the predetermined period of time.

Abstract: Embodiments of the present invention relate to apparatuses, systems, methods, and computer program products for determining a competitor's pricing strategy. In one embodiment, a system comprises a processor configured to: (a) receive information identifying pricing strategy for each of the plurality of entities, where the pricing strategy comprises at least one variable for a price selection method; (b) randomly generate initial values for the at least one variable for the price selection method to thereby generate a plurality of pricing strategies; (c) determine a value of fitness for each of the plurality of pricing strategies; (d) select pricing strategies from among the plurality of pricing strategies having a value of fitness that satisfy a predetermined criteria; (e) use a genetic algorithm to randomly modify a portion of the initial values for the at least one price selection method; and (f) determine that the plurality of pricing strategies is satisfactory.

Abstract: A method evaluates a prediction set of financial product applications. The method builds a multi-dimensional observation grid of observation grid points, each corresponding to at least one past financial product application in an observation set and each populated with the one or more variable values and the observation result value associated with the past financial product application. The method includes building a multi-dimensional prediction grid comprising a plurality of prediction grid points, each corresponding to a present financial product application in the prediction set and populated with one or more variable values of the present financial product application, each also corresponding to an observation grid point and assigning a prediction result value for each prediction grid point.

Abstract: A method evaluates a prediction set of financial product applications. The method builds a multi-dimensional observation grid of observation grid points, each corresponding to at least one past financial product application in an observation set and each populated with the one or more variable values and the observation result value associated with the past financial product application. The method includes building a multi-dimensional prediction grid comprising a plurality of prediction grid points, each corresponding to a present financial product application in the prediction set and populated with one or more variable values of the present financial product application, each also corresponding to an observation grid point and assigning a prediction result value for each prediction grid point.