Telematics Data Processing for Insurance Premium Determination
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Solution Overview
Problem
Existing methods for determining insurance premium amounts based on telematics data face challenges in efficiently processing and interpreting large volumes of data, as well as understanding the significance of various data points and their correlation with risk factors.
Innovation Solution
A computer-implemented method and system that utilizes machine learning algorithms, specifically a trained ensemble model, to process and interpret telematics data from Electronic Logging Devices (ELD) to determine insurance premium amounts. This method includes obtaining telematics data, extracting driving feature datasets, calculating a risk score indicative of collision probability, and determining the insurance premium amount based on the risk score.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional methods are used to process telematics data, then data processing is simpler, but processing speed and accuracy are insufficient for large volumes of data
Solution Approach 1:
The patent segments the telematics data processing into distinct modules: data collection from sensors, data preprocessing and cleaning, feature extraction, risk factor analysis, and premium calculation. This modular segmentation enables parallel processing of different data streams, improving processing speed while maintaining manageable system complexity through clear separation of concerns.
Solution Approach 2:
The patent introduces an intermediary processing layer that acts as a mediator between raw telematics data and premium calculation. This intermediary layer performs data validation, normalization, and feature extraction, transforming raw data into structured risk factors. This intermediary approach enhances processing accuracy and speed by pre-processing data before it reaches the premium calculation engine.
2Measurement precision
If comprehensive telematics data is collected to improve accuracy, then understanding of driving behavior improves, but data management and processing becomes more challenging
Solution Approach 1:
The patent extracts only the most relevant features from comprehensive telematics data for premium calculation. Instead of processing all collected data, the system identifies and extracts key driving behavior indicators such as acceleration patterns, braking events, cornering forces, and speed variations. This selective extraction maintains high assessment accuracy while significantly reducing data management complexity and processing requirements.
Solution Approach 2:
The patent applies different processing quality levels to different data elements based on their relevance. Critical driving behavior data points receive more rigorous validation and processing, while less relevant data undergoes simpler processing. This local quality approach ensures high accuracy for important metrics while reducing overall processing complexity through differentiated treatment of data elements.
Data Source
AI summary
A computer-implemented method is disclosed for determining an insurance premium amount. The computer-implemented method includes a step of obtaining, from a remote server, telematics data associated with operation of a vehicle corresponding to a time period. The computer-implemented method includes a step of extracting, based on the telematics data, a driving feature dataset comprising at least one of: a driving behavior dataset, an environmental condition dataset, or a combination thereof. The computer-implemented method includes a step of calculating, based on execution of a trained ensemble model on the extracted driving feature dataset, a risk score indicative of a probability of occurrence of a collision of the vehicle. The computer-implemented method includes a step of determining, based on the calculated risk score, the insurance premium amount. The computer-implemented method includes a step of storing the determined insurance premium amount in a database associated with an insurance service platform.