Dynamic Insurance Premium Calculation via Telematics Monitoring
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Solution Overview
Problem
Traditional insurance premium calculations are often based on broad statistical classes and fixed periods, leading to premiums that may not accurately reflect individual risk, resulting in lost profits for insurance companies or overpayment by policyholders.
Innovation Solution
A system and method that monitor the time a vehicle operator is in active control and the time the vehicle operates autonomously, calculating insurance rates based on these metrics to provide dynamic premiums.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If insurance premiums are calculated based on broad statistical classes and fixed periods, then the calculation process is simple and efficient, but the premiums do not accurately reflect individual risk
Solution Approach 1:
The patent segments the insurance risk assessment by dividing it into multiple dimensions: traditional factors (age, location, vehicle type) and telematics factors (acceleration, braking, cornering, mileage). This segmentation allows the system to maintain simple calculation methods while incorporating granular risk data from multiple sources, thereby improving measurement precision without proportionally increasing complexity.
Solution Approach 2:
The patent implements dynamic premium adjustment by transitioning from fixed-period premiums to continuously updated assessments based on real-time telematics data. The system dynamically recalculates risk scores as new driving behavior data becomes available, allowing premiums to adapt to changing risk profiles while using standardized calculation algorithms that prevent complexity from escalating.
2Adaptability or versatility
If insurance premiums are fixed for the length of a policy, then administrative processing is simplified, but premiums may not match the actual risk over time
Solution Approach 1:
The patent establishes a feedback loop where telematics data from policyholders' vehicles is continuously collected, analyzed, and fed back into the premium calculation system. This feedback mechanism enables automatic premium adjustments based on actual driving behavior without requiring manual policy reviews, thereby achieving adaptability while maintaining operational simplicity through automated processing.
Solution Approach 2:
The system enables self-service premium adjustment by automatically processing telematics data and recalculating premiums without requiring policyholder intervention or insurer manual review. The automated system serves itself by collecting data, assessing risk, and adjusting premiums through programmed algorithms, thus maintaining ease of operation while achieving continuous adaptability.
3Measurement precision
If telematics data is collected and analyzed for premium calculation, then risk assessment precision is improved, but data processing requirements increase
Solution Approach 1:
The patent applies partial action by selecting and monitoring only the most relevant telematics parameters (acceleration, braking, cornering, mileage) rather than processing all possible vehicle data. This selective approach captures sufficient individual risk differentiation while avoiding the computational overhead of analyzing excessive data points, thereby maintaining high measurement precision with efficient processing.
Data Source
AI summary
Systems and methods monitor at least one of a first amount of time a vehicle operator is in active control of a vehicle during a period and a second amount of time that the vehicle operates autonomously during the period. The systems and methods further calculate an insurance rate based on the first amount of time and the second amount of time.