Sensor-Based Risk Scoring for Insurance Quotation
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Solution Overview
Problem
Current insurance quote systems provide one-time offers based on specific pre-quotation characteristic information, failing to aggregate risk data from multiple customers to offer competitive and risk-adjusted quotes.
Innovation Solution
A system that collects sensor data and geographically-related information to calculate a risk rating or score, using unsupervised learning models to analyze operational states and produce sequences, which are then used to generate a quotation score that can be aggregated with other scores for more sophisticated risk analysis and competitive quoting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If insurance companies use traditional one-time quote systems based on pre-quotation characteristic information, then individual customer quotes can be generated quickly, but the ability to aggregate risk data across multiple customers and provide competitive risk-adjusted quotes is lost
Solution Approach 1:
The system performs preliminary risk assessment by continuously collecting and analyzing sensor data from multiple customers before the actual quoting process. Risk scores are pre-calculated based on aggregated sensor information from the risk pool, enabling faster individual quote generation while maintaining aggregated risk analysis capabilities
Solution Approach 2:
An intermediary risk pool is introduced that aggregates sensor data from multiple customers. This risk pool serves as a mediator between individual customer sensor data and the final quote generation process, enabling both individual quick quoting and aggregated risk analysis through the centralized risk pool
2Measurement precision
If sensor data is collected and analyzed from multiple customers to create a risk pool, then more sophisticated risk analysis and competitive quotes can be provided, but system complexity increases
Solution Approach 1:
The system merges sensor data from multiple customers into a unified risk pool, combining individual risk assessments into a collective dataset. This merging enables sophisticated risk analysis through aggregation while using standardized processing methods to manage system complexity
Solution Approach 2:
The system transforms raw sensor data into standardized risk scores through parameter changes. By converting diverse sensor inputs into a common risk score metric, the system enables sophisticated comparison and aggregation across customers while simplifying the overall system architecture through parameter standardization
3Device complexity
If individual customer quotes are generated independently without aggregation, then quoting process remains simple, but risk pool formation and competitive rate optimization are prevented
Solution Approach 1:
The system performs preliminary risk assessment and aggregation in advance, calculating risk scores based on aggregated sensor data before the actual quoting process. This preliminary action enables simple individual quoting while maintaining risk pool aggregation capabilities, as the aggregation work is completed beforehand
Solution Approach 2:
The risk pool automatically aggregates sensor data and calculates risk scores through self-service mechanisms. Individual customers' sensor data is automatically incorporated into the risk pool without manual intervention, maintaining process simplicity while enabling risk pool formation and competitive rate optimization
Data Source
AI summary
Described are techniques for determining a quotation score that would be applicable across lines of insurance and/or carriers, and which involves the collection in real time of sensor information from plural groups of sensors deployed in a specific premises and associated with intrusion detection, access control, burglar, fire alarm systems and surveillance systems and/or other systems that monitor for physical/chemical/biological conditions. The techniques execute unsupervised learning models to continually analyze the collected sensor information to produce sequences of state transitions that are assign scores and from which a quotation score is produced.