Vehicle Sensor Data Risk Assessment for Insurance Ratings
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Solution Overview
Problem
Insurance providers face challenges in accurately determining insurance policy premiums due to limited access to driving behavior information, as current methods rely on self-reported data and are unable to assess all relevant risk factors effectively.
Innovation Solution
A system that collects and processes data from onboard vehicle sensors, including cameras, lidar, and GPS, to generate virtual models of events and determine risk indicators, allowing for real-time assessment of driving behavior and environmental factors to inform insurance ratings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If self-reported driving behavior data is used for insurance rating, then data collection is simple and low-cost, but measurement precision and reliability of risk assessment deteriorate
Solution Approach 1:
The patent replaces manual self-reporting mechanisms with automated electronic sensor systems. Sensors mounted in the vehicle automatically detect and record driving behaviors such as acceleration patterns, braking events, steering movements, and speed variations, eliminating the need for driver self-reporting while providing objective, precise measurements of actual driving behavior.
Solution Approach 2:
The patent introduces an intermediary data collection system consisting of sensors, processors, and communication devices that mediate between the driver's actual behavior and the insurance provider's risk assessment. This intermediary system captures raw sensor data, processes it into meaningful risk indicators, and transmits it to the insurance provider, bridging the gap between simple data collection and accurate risk measurement.
2Device complexity
If limited driving behavior information is used, then data processing complexity is reduced, but risk assessment accuracy deteriorates
Solution Approach 1:
The patent segments the risk assessment process into multiple independent components: sensor data acquisition, raw data processing, risk indicator calculation, and premium determination. Each segment handles specific aspects of the data flow, allowing complex multi-parameter risk assessment to be managed through modular, manageable stages rather than requiring simultaneous processing of all data elements.
Solution Approach 2:
The patent implements partial action by selectively monitoring and processing only the most relevant driving behavior parameters that have been predetermined to correlate with insurance risk. Rather than analyzing every possible driving parameter, the system focuses on key indicators such as hard braking events, excessive speed occurrences, and nighttime driving patterns, achieving accurate risk assessment without overwhelming processing complexity.
3Measurement precision
If real-time sensor data collection is implemented, then risk assessment accuracy improves, but device complexity and data processing requirements increase
Solution Approach 1:
The patent employs universal sensor platforms that serve multiple functions simultaneously. The same sensor system that monitors driving behavior for risk assessment also tracks vehicle operational parameters, detects accidents, and provides data for various insurance products. This multi-functionality reduces overall system complexity by consolidating data collection capabilities rather than requiring separate specialized systems for each function.
Solution Approach 2:
The patent implements self-service through automated sensor systems that independently collect, process, and transmit risk data without requiring manual intervention from drivers or insurance adjusters. The system automatically calibrates sensors, filters relevant data from noise, calculates risk indicators, and communicates results to the insurance provider, reducing operational complexity despite the advanced technology involved.
Data Source
AI summary
A method includes receiving vehicle sensor data from a second vehicle via one or more wireless signals. The vehicle sensor data is collected by a sensor that is located on or in the second vehicle and configured to sense an environment external to the second vehicle. The vehicle sensor data is received at an electronic processing system, and stored in a memory. A set of one or more characteristics of the environment external to the first vehicle is determined by processing the stored vehicle sensor data, and a risk indicator is determined based on the set of one or more characteristics, a risk indicator. An insurance rating for an insurance policy associated with the first vehicle is determined based on the risk indicator.