Motor Vehicle Collision Fault Routing via NLP Decision Trees
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Solution Overview
Problem
The complexity of fault-determination rules in motor vehicle collisions makes it impractical for insurance claim handlers to assess fault accurately and efficiently, especially in unusual circumstances, requiring significant training and often necessitating consultation with specialized experts.
Innovation Solution
A computer system employing natural language processing and a decision tree to evaluate unstructured text descriptions of collisions, mapping intent to fault-determination rules, and providing recommendations on fault determination without the need for human experts, allowing for efficient assessment even in complex scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fault-determination rules are applied manually by insurance claim handlers, then accuracy in determining fault can be maintained through expert knowledge, but the process becomes time-consuming and requires significant training
Solution Approach 1:
The patent introduces an automated computer system as an intermediary between the collision data and fault determination rules. This system processes unstructured text descriptions of collisions, maps them to decision tree nodes, and navigates through fault-determination rules automatically, eliminating the need for human experts to manually apply complex rules while maintaining accuracy and reducing time loss
Solution Approach 2:
The patent replaces the mechanical system of human experts manually applying fault-determination rules with an automated computer-based system. The system uses natural language processing and decision tree algorithms to automatically evaluate collision circumstances and determine fault, substituting human cognitive processes with automated computational processes that are both accurate and efficient
2Adaptability or versatility
If comprehensive fault-determination rules are implemented to cover all possible collision scenarios, then accuracy in unusual circumstances improves, but system complexity increases making it impractical for manual assessment
Solution Approach 1:
The patent segments the comprehensive fault-determination rules into a structured decision tree with multiple nodes, each representing a specific question or condition. This segmentation allows the system to handle complex scenarios by breaking them down into manageable, sequential decisions, making the comprehensive rule set practical for automated processing while maintaining coverage of all collision scenarios
Solution Approach 2:
The automated computer system acts as an intermediary that manages the complexity of comprehensive fault-determination rules. By automatically navigating the decision tree and applying the appropriate rules based on parsed collision descriptions, the system handles the complexity internally while presenting a simplified interface to users, enabling comprehensive scenario coverage without making the system impractical to operate
3Productivity
If automated systems are used to determine fault, then processing speed and efficiency improve, but the ability to handle complex and unusual collision circumstances may be compromised
Solution Approach 1:
The patent replaces human expert judgment with automated computer processing that can consistently and rapidly evaluate all aspects of a collision. The system uses natural language processing to parse unstructured text descriptions and applies comprehensive fault-determination rules algorithmically, achieving both high processing speed and reliable accuracy in complex scenarios by eliminating human limitations such as fatigue, bias, and inconsistent application of rules
Solution Approach 2:
The automated system serves as an intermediary that bridges the gap between simple automated processing and complex expert judgment. By implementing a decision tree structure that systematically evaluates all relevant factors in collision scenarios, the system maintains reliability in complex situations while achieving automated processing speed, acting as a mediator between the extremes of manual expert assessment and simple automated rules
Data Source
AI summary
A computer-implemented method of providing a recommendation as to a fault determination for a motor vehicle collision is disclosed. The method may include receiving unstructured text describing the circumstances of the collision. The unstructured text is evaluated an associated intent related to the circumstances of the motor vehicle collision is identified. The intent is mapped to an internal node of a decision tree corresponding to a set of fault-determination rules. The computer then successively prompts and receive input responsive to the prompting that corresponds to details of the circumstances of the collision. The computer may identify, based on the received input, a path through the decision tree ending at a leaf node that corresponds to a fault-determination rule governing motor vehicle collisions that matches the circumstances of the motor vehicle collision. The recommendation is then provided based on that rule. Related systems and computer-readable media are also disclosed.