Abstract: Systems, methods, and computer program products are provided for customer loan lifecycle modeling using discrete event simulation methodology. Discrete Event Simulation (DES) allows for modeling to occur at the customer and/or account level, such that the process captures customer-specific or loan-specific attributes/exposure factors, such as, but not limited to, credit score(s), House Price Index (HPI), loan product type, unemployment rates, interest rates and the like. Such modeling takes into the account that loan events occur at random paces and are typically dependent on ancillary factors, such as, availability of financial resources, market demand, customer attributes and the like, which all tend to be stochastic by nature.

Abstract: A method, system and program product comprises registering a provider where the registration comprises an identity, an advertisement, a location for displaying the advertisement, and a time period for an advertising event. Funds are deposited into an account for the advertising event. At least one marketer is registered where the registration comprises an identity, an identity of at least one display and control device in possession of the marketer, a location for the display and control device, and an available time period for displaying advertisement. Notification of a match of a marketer to present advertisement content of a provider is received, in which the provider's advertisement is communicated to the marketer's display and control device. Tracking information for the display and control device determines a value of funds. The value of funds is transferred from the account for the advertising event to an account for the marketer.

Abstract: Systems, methods, and computer program products are provided for customer loan lifecycle modeling using discrete event simulation methodology. Discrete Event Simulation (DES) allows for modeling to occur at the customer and/or account level, such that the process captures customer-specific or loan-specific attributes/risk factors, such as, but not limited to, credit score(s), House Price Index (HPI), loan product type, unemployment rates, interest rates and the like. Such modeling takes into the account that loan events occur at random paces and are typically dependent on ancillary factors, such as, availability of financial resources, market demand, customer attributes and the like, which all tend to be stochastic by nature.