Vehicle Image Analysis for Real-Time Financing Quotes
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Solution Overview
Problem
Current auto financing methods are lengthy, manual, and often provide inaccurate quotes, limiting customers' ability to change vehicle choices during the financing process, as actual vehicle information may not be available at the time of financing and pre-qualification methods can be inaccurate.
Innovation Solution
The use of machine learning systems to process images of vehicles, identify attributes, and generate real-time financing quotes, which can be displayed via augmented reality on user devices, streamlining the financing process and providing accurate quotes based on vehicle specifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional manual credit application processes are used, then financing approval can be obtained, but the process is lengthy and complex requiring multiple steps including filling out lengthy applications and providing extensive personal information
Solution Approach 1:
The system performs preliminary image processing and vehicle identification before the financing decision is needed. By capturing and analyzing vehicle images in advance using machine learning algorithms to extract features and determine make/model, the system prepares financing quotes ready when needed, eliminating the need for time-consuming manual applications at the dealership.
Solution Approach 2:
The patent replaces the manual mechanical process of filling out credit applications and providing personal information with an automated machine learning system that processes vehicle images and generates financing quotes algorithmically, substituting human manual operations with automated computational processes.
2Adaptability or versatility
If pre-qualification methods are used to obtain financing estimates, then customers can get financing approval before vehicle selection, but the quotes are inaccurate and may not reflect actual vehicle pricing
Solution Approach 1:
The system performs preliminary vehicle identification through image processing before generating financing quotes. By using machine learning to accurately determine vehicle make, model, and attributes from images, the system creates precise financing estimates in advance that remain valid when customers select specific vehicles, maintaining both accuracy and flexibility.
Solution Approach 2:
The system creates accurate digital representations (copies) of the actual vehicle through image processing and feature extraction. By analyzing visual features and comparing them against known vehicle patterns, the system generates a precise digital model that enables accurate financing quotes without requiring physical inspection or manual data entry.
3Measurement precision
If customers select a specific vehicle before seeking financing to obtain accurate pricing, then precise quotes can be received, but the customer's ability to change their mind is limited and they may need to reapply for financing
Solution Approach 1:
The machine learning system is designed to handle multiple vehicle types and scenarios universally. By processing vehicle images and generating financing quotes that can apply to multiple vehicles within a make/model family, the system provides accurate pricing that remains valid even when customers change their specific vehicle selection, eliminating the need to reapply.
Solution Approach 2:
The system performs preliminary vehicle identification and financing calculation before the customer makes a final selection. This advance preparation creates flexible financing quotes that can accommodate changes in vehicle choice while maintaining pricing accuracy, as the core vehicle attributes have already been identified through image processing.
4Reliability
If manual credit application processes are used at the dealership, then financing can be completed, but customers must endure a lengthy multi-step process including filling out applications and providing personal information
Solution Approach 1:
The patent replaces the manual mechanical process of filling out credit applications and providing personal information with an automated machine learning system that processes vehicle images and generates financing quotes algorithmically, substituting human manual operations with automated computational processes that are more convenient for customers.
Solution Approach 2:
The system enables customers to obtain financing quotes by simply providing vehicle images through their mobile devices. The machine learning algorithm automatically processes these images, extracts relevant features, and generates financing information without requiring customers to manually fill out applications or provide extensive personal details, making the process self-service oriented and much more convenient.
Data Source
AI summary
The present disclosure relates to systems and methods for generating real-time quotes using machine learning algorithms. The system may include a processor in communication with a client device, and a storage medium storing instructions that, when executed, cause the processor to perform operations including: receiving an image of a vehicle from the client device, extracting one or more features from the image, based on the extracted features and using a machine learning algorithm, identifying one or more attributes of the vehicle, based on the identified attributes of the vehicle, determining a make and a model of the vehicle, obtaining comparison information based at least in part on the determined make and model, estimating a quote for the vehicle based on the comparison information; and transmitting the estimated quote for display on the client device.