Property Risk Scoring Using External Data for Remote Assessment
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Solution Overview
Problem
Conventional methods for evaluating real property for risk assessment are often expensive and time-consuming, and traditional virtual models lack detailed views necessary for efficient evaluation, particularly at side angles, making it difficult to assess properties without in-person inspections.
Innovation Solution
A computer-implemented method using predictive analytics that compares external data from a prospective property with a reference property's characteristics to determine a predicted risk score, allowing virtual evaluation and generation of tailored virtual models for further assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If in-person assessments by subject matter experts are used, then measurement precision and reliability are improved, but loss of time and productivity worsen
Solution Approach 1:
The system performs preliminary automated assessments using external data sources (aerial imagery, property records, environmental data) before subject matter experts conduct in-person evaluations. This preliminary action filters properties and prepares assessment packages, reducing the time experts need to spend on-site while maintaining assessment quality.
Solution Approach 2:
The patent introduces an automated predictive analytics system as an intermediary between the property being assessed and the subject matter expert. This intermediary processes external data, generates risk scores, and provides recommendations, allowing experts to focus their time on critical evaluations rather than data collection.
2Measurement precision
If in-person assessments by subject matter experts are used, then measurement precision is improved, but productivity worsens
Solution Approach 1:
Automated preliminary assessments process multiple properties simultaneously using external data sources, preparing comprehensive evaluation packages before experts begin in-person inspections. This increases the number of properties that can be assessed within the same time frame while maintaining expert involvement for quality control.
Solution Approach 2:
The system enables self-service automated assessment capabilities that operate independently of expert intervention. External data is automatically collected, processed, and analyzed to generate initial risk scores and recommendations, freeing experts to focus on complex cases and thereby increasing overall productivity.
3Measurement precision
If detailed virtual models with side angle views are generated, then measurement precision and ease of operation are improved, but device complexity and cost worsen
Solution Approach 1:
The system generates detailed virtual models with side angle views selectively for specific properties or assessment scenarios rather than universally. By applying detailed modeling only where needed (local quality), the system achieves high measurement precision for critical properties while avoiding the complexity and cost of generating such models for all properties.
Solution Approach 2:
The automated system performs preliminary analysis of external data to identify properties that require detailed virtual models. This preliminary action determines which properties need the additional complexity of side angle views, ensuring that detailed modeling resources are allocated efficiently based on assessment needs rather than being applied uniformly.
Data Source
AI summary
Methods and systems for assessing property based on predictive analytics techniques that use external data are described herein. A server may identify a reference set of information for a reference property evaluated with a reference risk score in accordance with a risk score rule that meets a predetermined threshold. The server may obtain an external data file from an external data source, wherein the external data file includes an external set of information for a prospective property. The server may compare the reference set of information with the external set of information to identify a common feature, condition, or attribute, and if identified, may evaluate the prospective property by determining a predicted risk score based on the external set of information in accordance with the risk score rule. If the predicted risk score is determined to meet the threshold, the server may indicate the prospective property as pre-approved.