House Image Underwriting With AI Damage Assessment Feedback
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Solution Overview
Problem
Current housing insurance underwriting and claiming processes face challenges such as cumbersome and time-consuming manual inspections, subjectivity and inconsistency in risk assessments, low efficiency in data collection and processing, and issues with image quality from consumer-grade UAV and mobile phone photography.
Innovation Solution
A method and system utilizing artificial intelligence for real-time detection and determination during house photo taking, including UAV and mobile phone photography, followed by cloud-based measurement and damage assessment to generate underwriting or claiming reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection by professionals is used, then inspection thoroughness is improved, but inspection time and labor costs increase significantly
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated system combining UAV aerial photography, ground-based photography, and AI image analysis. The system captures roof and house images automatically and uses computer vision algorithms to identify damage, substituting human labor with automated technological processes while maintaining inspection quality.
Solution Approach 2:
The patent creates visual copies of the physical inspection target through photography. Multiple images (aerial views, ground views, close-up views) are captured and processed to form a comprehensive digital representation of the house condition, allowing remote analysis without physical presence of inspectors.
2Reliability
If manual inspection by multiple loss adjusters is used, then comprehensive assessment is improved, but subjectivity and inconsistency in risk assessment increase
Solution Approach 1:
The patent replaces human judgment with AI-based image analysis algorithms. The system objectively identifies damage types, locations, and severity from images using computer vision and deep learning models, eliminating subjective variations between different loss adjusters while maintaining comprehensive assessment capabilities.
Solution Approach 2:
The inspection system performs self-assessment through automated image analysis. The AI model independently evaluates house conditions, identifies risks, and generates assessment reports without requiring human intervention for judgment, ensuring consistent and reproducible results across different cases.
3Measurement precision
If traditional data collection methods are used, then data accuracy is maintained, but data collection efficiency and processing speed decrease
Solution Approach 1:
The patent replaces manual data collection and processing with automated systems. UAVs and ground devices automatically capture images, and AI algorithms automatically analyze images to extract data about house conditions, damage, and risks. This automated pipeline dramatically increases data collection efficiency while maintaining accuracy through systematic processing.
Solution Approach 2:
The patent implements continuous automated data collection and processing. The system continuously captures images during UAV flight and ground inspection, and continuously processes these images through AI algorithms in real-time or near-real-time, eliminating the batch processing delays inherent in manual methods.
4Ease of manufacture
If consumer grade UAV and mobile phones are used for photography, then equipment cost is reduced, but image quality and shooting standardization deteriorate
Solution Approach 1:
The patent incorporates real-time feedback mechanisms where the AI system analyzes captured images immediately and provides guidance on whether images meet quality standards. The system identifies poor-quality images (blurry, incorrect angles, missing key features) and prompts operators to retake photos, ensuring standardized quality without requiring expensive professional equipment.
Solution Approach 2:
The patent performs preliminary quality assessment of images at the point of capture using AI algorithms. The system evaluates image quality metrics (sharpness, lighting, composition, completeness) before the images are fully processed, allowing immediate correction of issues and preventing propagation of poor-quality data through the workflow.
Data Source
AI summary
The present application relates to a method for insurance underwriting and claiming using house images, which includes: performing artificial intelligence detection and determination in real time during a process of taking house photos, and uploading taken house photos to a cloud end; wherein the house photos include a roof photo and/or photos of inside and outside of the house; performing artificial intelligence measurement and damage assessment based on the uploaded house photos, and generating an underwriting or claiming report. The present application further relates to a system for insurance underwriting and claiming using house images. The present application realizes high-efficiency and accurate collection and analysis for house images, and provides more comprehensive and reliable data support for insurance underwriting and claiming.