摘要:
Automatically rating appraisal quality and evaluating comparables listed on the appraisal. A comparable selection model selects control comparables using transaction data and property characteristics relative to a subject from a database. An evaluation model compares the control comparables to the listed comparables to generate a quality rating for the appraisal based on category scores that result from an appraisal evaluation over a set of categories.
摘要:
Modeling appropriate comparable properties for a condo property includes accessing property data, and identifying candidate condo properties in the accessed property data to produce condo property data. A regression is performed using the property data, with the regression modeling the relationship between price and explanatory variables, and the explanatory variables including at least one variable that is specific to condo property assessment. The regression accommodates a modeling of comparable properties, such that a subject condo property and comparable properties may be identified and displayed.
摘要:
Automatically assigning confidence ratings to properties valued by an automated valuation model. A value confidence model determines a set of typical property characteristics for properties in a geographic area, automatically determines a deviation from the set of typical property characteristics for a candidate comparable property, and assigns a confidence factor to an automated valuation of the candidate comparable property based upon the deviation.
摘要:
A valuation model accounts for traffic features associated with modeled properties, generates listings of model-chosen comparables, and evaluates property appraisals and appraisal-chosen comparables accordingly. In one embodiment, traffic features of homes are used in automated electronic appraising and in the electronic review of appraisals. It first uses GIS techniques to convert traffic features associated with a property into a numeric variable, allowing hedonic price models to measure the price impact of traffic features. This allows traffic features to be used in the automated selection of comparable properties and in the adjusting of comp prices in appraisals. It also allows automated review of appraisals to determine if they fairly accounted for the traffic dimension in the selection of comps and in making any price adjustments. In one example, the automatic valuation uses a regression that models the relationship between price and explanatory variables, with the explanatory variables including traffic feature variables.
摘要:
Modeling comparable properties and rendering map images with automatic valuation of properties bordering specified geographic features. A valuation model identifies and accounts for the proximity of properties to geographic features. For example, estimating property value includes accessing property data corresponding to a geographic area and performing a regression based upon the property data. The regression models the relationship between price and explanatory variables, with the explanatory variables including proximity to geographic features. Proximity may be a categorical variable wherein properties bordering the geographic feature are determined to possess the proximity characteristic. Alternative explanatory variables may incorporate different degrees of proximity.
摘要:
Automatically rating comparable properties by accessing property data and comparable assessment information, in which a regression is performed, on to model the relationship between the comparable-appropriateness of the property data and explanatory variables. A set of comparable-appropriateness values for each of the plurality of comparable properties based upon differences in the explanatory variables between the subject property and each of the plurality of comparable properties are chosen and an assessment is outputted.
摘要:
Modeling appropriate comparable properties for a condo property includes accessing property data, and identifying candidate condo properties in the accessed property data to produce condo property data. A regression is performed using the property data, with the regression modeling the relationship between price and explanatory variables, and the explanatory variables including at least one variable that is specific to condo property assessment. The regression accommodates a modeling of comparable properties, such that a subject condo property and comparable properties may be identified and displayed.
摘要:
A method for automatic detection of inconsistencies in an appraisal by extracting data from the appraisal to create component data arranged into a predetermined set of categories and selecting a control identifier to trigger a generation of comparison data. Further, through a comparison between the comparison data and the component data, inconsistencies within the appraisal are identified.
摘要:
Indexing and adjusting for property condition in an automated valuation model. Property data corresponding to a geographical area is accessed, and a regression is performed based upon the property data. The regression models the relationship between a dependent variable, such as price, and property-characteristic explanatory variables. Further regression is then performed and models or further explains the relationship between the dependent variable and property condition explanatory variables. Specifically, further regression may model the relationship between the residual from the first regression and the property condition variables. Optional examples of these variables are those based upon the presence of predetermined remarks in associated property listings, the number of photos in such listings, and a categorical year built variable. The regression is used to determine a property-condition index for the geographical area. The property-condition index identifies a predicted condition that is used to make adjustments to comparable properties in automated valuation modeling.
摘要:
Automated valuation model with customizable neighborhood determination. A map image is displayed corresponding to a geographical area, and then user input accommodates definition of a particularly defined geographic area to provide custom identification of a neighborhood to be subject to automated valuation. Once the defined geographic area is established, the automated valuation model is applied to property data corresponding to properties within the defined geographic area. A subject property and corresponding properties within the defined geographic area are then displayed on a map image, preferably with articulation of the defined geographic area as the neighborhood of interest. The neighborhood may be defined by, among other criteria, inclusion within a user-defined shape, as well as exclusion of a user-defined shape from a displayed geographic area.