Abstract: A system and method for automatically accessing property data corresponding to properties within the geographic area and displaying on a display device a map corresponding to said geographic area. Applying a comparable selection model based on a subject to the property data to generate a set of comparable properties, altering the set of comparable properties based on a variation command to generate an altered comparable property set, and displaying on the display device the map with the altered comparable property information.

Abstract: An automated valuation model that uses condition and quality variables. In response to user queries, the model ranks and displays comparables for a subject property. The comparables are selected based on their similarity to the subject. Data on quality and condition of properties is incorporated into the model and corresponding comparable assessments. For example, the quality and condition inputs may be used in a hedonic adjustment factor model, comparable selection exclusion rules, economic distance calculations, and adjustments for differences between the subject and comparables at comparable selection stage. The comparables may be displayed in ranked order based on the calculated similarities between the properties, with indications of the quality and condition categories, to provide an overall assessment of the comparables as well as displayable indications of the underlying quality and condition categories and related information.

Abstract: 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.

Abstract: Automatically rendering a new valuation for a subject based on real-time property characteristic alterations or manipulations using a comparable selection model. A user alters one or more property characteristics for the subject and the comparable selection model determines a ranked listing of comparable properties for the subject in a given geographical area based on those alterations. The comparables are then displayed in a ranked order that reflects the alterations based on prior data point changes.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Automated valuation model with customizable neighborhood determination, including spatial exclusion conditions. 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Model-based property value estimation with that implements a categorical location variable providing a neighborhood proxy. A regression models the relationship between sale price and a set of explanatory variables. These explanatory variables include a location variable that is defined at a level of granularity such that the location variable acts as a proxy for location within a neighborhood. An infill process remedies the effects of insufficient amounts of location variable data.

Abstract: Ranking and displaying comparable properties entails receiving appraisal information comprising a subject property and appraiser-chosen comparable properties corresponding to the subject property. Property data corresponding to a geographical area is accessed, in support of determining model-chosen comparable properties based upon the appropriateness of each of the comparable properties as comparables for the subject property. A map image is displayed for the geographical area, along with indicators on the map image indicative of the subject property, at least one of the appraiser-chosen comparable properties, and at least one of the model-chosen comparable properties.

Abstract: Modeling and mapping appropriate comparable properties comprises accessing property data corresponding to a geographical area, and then weighting comparable properties based upon the appropriateness of each of the plurality of comparable properties as comparables for a subject property. For example, the weighting may be based upon economic distance from the subject property, geographic distance from the subject property, and age of transaction. Using this information, a map image of the geographical area is displayed, with indicators on the map image indicative of the subject property and at least one of the comparable properties.

Abstract: A system and method of detecting potential fraud in connection with mortgage loan lending, where a first group made up of a plurality of mortgage loans is utilized to calculate a representative value associated with a loan-related event. A second group also made up of a plurality of mortgage loans is utilized to calculate a predicted representative value associated with the same loan-related event. The actual and predicted representative values are compared to determine a deviation value. If the deviation exceeds a predetermined threshold, an output indicating potential fraud is generated.