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 device including a memory with an automated collateral fraud and risk detection application installed thereon, wherein the application determines whether a final appraised value of an appraisal was correctly reconciled from comparable properties listed on the appraisal by extracting reconciliation information from the appraisal, the reconciliation information including adjusted sale prices for each comparable property listed on the appraisal and the final appraised value; applying a rule set to the reconciliation information to generate sub-scores; applying a heuristic to the sub-scores to generate a reconciliation score; and outputting a scorecard for the appraisal based on the reconciliation score.

Abstract: A system comprises a device including a memory with an automated collateral fraud and risk detection application installed thereon, wherein the application evaluates risk in an acquisition in support of end user decisions by accessing at least one database to retrieve documentation corresponding to the acquisition and secondary information corresponding to the documentation, the documentation and secondary information each including data fields; compares the documentation data fields with corresponding secondary information data fields to identify acquisition defects; applies risk heuristics on the acquisition defects to generate a probability estimation for each acquisition defect; and outputs a risk evaluation for the acquisition including a confidence metric based on an aggregation of the probability estimations.

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.