The “KAIL Fault Ratio” service—a tool for analyzing fault ratios in traffic accidents developed by the LegalVision AI Lab at Kookmin University (President Jeong Seung Ryul; led by Professor Shin Hong Kyun of the College of Law)—has passed OpenAI’s official review and will be available as a ChatGPT plugin.
 
“KAIL Fault Ratio” is a service designed to allow users to easily check fault ratios in traffic accidents via ChatGPT. When a user enters the specific circumstances and facts of a traffic accident into the ChatGPT chat window, the service provides the liability ratio for that accident based on the traffic accident liability ratio chart provided by the General Insurance Association of Korea. Additionally, if the user requests relevant case law, the service also provides details of court rulings on similar accidents along with liability ratio information.
 
Using the service is simple. Enter “traffic accident” in the ChatGPT plugin search bar to view the “KAIL Fault Ratio” service; select it to begin using it in the chat. Users can check information on traffic accident fault ratios directly in their regular ChatGPT chat window without any complicated procedures.
 
Generally, ChatGPT plugin services are provided after undergoing OpenAI’s official review process. It is understood that the review process comprehensively evaluates the proper operation of the MCP server, the level of feature implementation, privacy protection and security, the service’s completeness, and its practical value that differentiates it from ChatGPT’s basic functions.
 
The newly launched “KAIL Liability Ratio” service is also significant in that it was developed with support as an Innovation Startup Lab through the government’s “Laboratory-Specialized Startup Leading University” initiative. The university has transformed its research achievements into an AI service applicable to everyday life and is now making it available to the general public via the ChatGPT platform.

Kookmin University expects that this service will allow parties involved in traffic accidents to access information regarding fault ratios more easily and conveniently. Furthermore, it is anticipated to serve as a model for how the university’s AI research achievements can be expanded into practical services that enhance the quality of life for the public.