Abstract: A home cost analysis server for executing a customized home search may include a processor programmed to define a user budget constraint, receive a list of available homes, and determine an initial monthly cost for each home. The processor may also identify one or more additional home costs based on historical insurance claim data. The processor may also display available homes that satisfy the user budget constraint.

Abstract: A home cost analysis server for executing a customized home search may include a processor programmed to define a user budget constraint, receive a list of available homes, and determine an initial monthly cost for each home. The processor may also identify one or more additional home costs based on historical insurance claim data. The processor may also display available homes that satisfy the user budget constraint.

Abstract: A home cost analysis server is configured to train a machine-learning program to identify features of homes, receive user input including a prospective home, and access a first database storing metadata and images associated with homes, including the prospective home, available for purchase. The server is also configured to input images of the prospective home to the trained machine-learning program, which outputs a feature of the prospective home, access a second database storing historical additional costs, and perform a lookup in the second database to retrieve comparable historical additional costs associated homes having a comparable feature to the output feature. The server is further configured to analyze the metadata associated with the prospective home, the output feature, and the comparable historical additional costs to determine additional home costs associated with the prospective home, and output the additional home costs and an overall monthly cost for the prospective home.

Abstract: A home cost analysis server is configured to train an image processing program to identify features of homes, receive user input including a prospective home, and access a first database storing metadata and images associated with homes, including the prospective home, available for purchase. The server is also configured to input images of the prospective home to the machine-learned image processing program, which outputs a feature of the prospective home, access a second database storing historical ancillary costs, and perform a lookup in the second database to retrieve comparable historical ancillary costs associated homes having a comparable feature to the outputted feature. The server is further configured to analyze the metadata associated with the prospective home, the outputted feature, and the comparable historical ancillary costs to determine ancillary home costs associated with the prospective home, and display the ancillary home costs and an overall monthly cost for the prospective home.

Abstract: A home cost analysis server is configured to train an image processing program to identify features of homes, receive user input including a prospective home, and access a first database storing metadata and images associated with homes, including the prospective home, available for purchase. The server is also configured to input images of the prospective home to the machine-learned image processing program, which outputs a feature of the prospective home, access a second database storing historical ancillary costs, and perform a lookup in the second database to retrieve comparable historical ancillary costs associated homes having a comparable feature to the outputted feature. The server is further configured to analyze the metadata associated with the prospective home, the outputted feature, and the comparable historical ancillary costs to determine ancillary home costs associated with the prospective home, and display the ancillary home costs and an overall monthly cost for the prospective home.

Abstract: A home cost analysis server for executing a customized home search may include a processor programmed to define a user budget constraint, receive a list of available homes, and determine an initial monthly cost for each home. The processor may also identify one or more additional home costs based on historical insurance claim data. The processor may also display available homes that satisfy the user budget constraint.

Abstract: A home cost analysis server for executing a customized home search may include a processor programmed to define a user's budget constraint and a level of flexibility thereof, including a threshold difference from the budget constraint, retrieve a list of homes and public listing information associated with each home, and determine a monthly cost associated with each home. The processor may also isolate a first subset of homes having a monthly cost that satisfies the budget constraint, and a second subset of homes having a monthly cost within the threshold difference of the budget constraint, and display the first and second subsets along with respective first and second graphical indicators, as well as a third graphical indicator of a first adjustable expense data element, the third graphical indicator recommending reducing the first adjustable data element to move at least one first home from the second subset into the first subset.

Abstract: A home cost analysis server is configured to train an image processing program to identify features of homes, receive user input including a prospective home, and access a first database storing metadata and images associated with homes, including the prospective home, available for purchase. The server is also configured to input images of the prospective home to the machine-learned image processing program, which outputs a feature of the prospective home, access a second database storing historical ancillary costs, and perform a lookup in the second database to retrieve comparable historical ancillary costs associated homes having a comparable feature to the outputted feature. The server is further configured to analyze the metadata associated with the prospective home, the outputted feature, and the comparable historical ancillary costs to determine ancillary home costs associated with the prospective home, and display the ancillary home costs and an overall monthly cost for the prospective home.

Abstract: A home cost analysis server is configured to train an image processing program to identify features of homes, receive user input including a prospective home, and access a first database storing metadata and images associated with homes, including the prospective home, available for purchase. The server is also configured to input images of the prospective home to the machine-learned image processing program, which outputs a feature of the prospective home, access a second database storing historical ancillary costs, and perform a lookup in the second database to retrieve comparable historical ancillary costs associated homes having a comparable feature to the outputted feature. The server is further configured to analyze the metadata associated with the prospective home, the outputted feature, and the comparable historical ancillary costs to determine ancillary home costs associated with the prospective home, and display the ancillary home costs and an overall monthly cost for the prospective home.

Abstract: A home cost analysis server for identifying one or more hidden home costs may include a processor programmed to receive user input including at least one prospective home. The processor may access a first external database storing metadata associated with a plurality of homes available for purchase, the plurality of homes including the prospective home, and access a second external database storing historical ancillary costs associated with a plurality of homes in a geographic area surrounding the prospective home. The processor may analyze metadata associated with the prospective home and the historical ancillary costs to determine ancillary home costs associated with the prospective home, and cause to be displayed the ancillary home costs at the user computing device using at least one graphical indicator. As a result, the prospective homebuyer may have additional education and insight into the potential costs of owning a home.

Abstract: A home cost analysis server for executing a customized home search may include a processor programmed to receive user input including a geographic area and a budget, and define a budget constraint. The processor may access an external database storing a list of available homes in the geographic area, and analyze metadata associated with each available home on the list to determine a monthly home cost associated with each available home. The processor may also determine a significant home maintenance cost associated with each available home based upon the metadata and the geographic area, and calculate a total cost associated with each available home. The processor may further isolate a subset of the available homes having the total cost associated therewith that satisfies the budget constraint, and cause to be displayed the subset of available homes along with a graphical indicator that associates the total cost with the budget constraint.