Predictive Water Loss Mitigation Messaging
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Solution Overview
Problem
Conventional methods for mitigating water loss in homeowner insurance policies are inefficient, as they do not effectively target high-risk policyholders, leading to wasteful distribution of mitigation efforts.
Innovation Solution
A system and method utilizing predictive modeling to identify high-risk policyholders by collecting and analyzing data on past water loss claims, home characteristics, and policyholder information, allowing for targeted mitigation strategies to be directed towards those most likely to benefit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional methods are used to message all policyholders for water loss mitigation, then mitigation efforts are broadly distributed, but the efficiency and effectiveness of these efforts deteriorate due to inability to target high-risk policyholders
Solution Approach 1:
The patent segments the policyholder population into different risk categories (high-risk, moderate-risk, low-risk) based on predictive modeling of water loss probability. This segmentation allows the system to apply different mitigation strategies to different segments, improving overall efficiency by concentrating resources on the segment most likely to benefit (high-risk policyholders).
Solution Approach 2:
The patent applies local quality by tailoring mitigation messaging and strategies to specific local conditions and individual policyholder risk profiles. Instead of uniform messaging, the system customizes mitigation recommendations based on local water loss patterns, property characteristics, and predicted risk, thereby improving effectiveness where it matters most.
2Reliability
If mitigation strategies are targeted at high-risk policyholders only, then effectiveness increases, but the system complexity increases due to need for predictive modeling and risk assessment
Solution Approach 1:
The patent implements preliminary action by performing risk assessment and predictive modeling in advance, before water loss events occur. The system pre-calculates risk probabilities and prepares customized mitigation strategies beforehand, so that when water loss events happen, the system can quickly execute pre-planned responses, reducing operational complexity during critical events.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously monitors actual water loss experiences and compares them against predicted risks. This feedback loop allows the predictive modeling to be refined and updated over time, improving accuracy while maintaining manageable system complexity through iterative improvement rather than requiring overly complex initial designs.
3Adaptability or versatility
If all policyholders receive mitigation messaging, then coverage is comprehensive, but resource waste increases due to inability to concentrate efforts on highest-risk individuals
Solution Approach 1:
The patent applies partial action by providing mitigation messaging and strategies selectively to policyholders based on their risk profile rather than universally to all policyholders. The system identifies and targets the partial subset of high-risk policyholders who are most likely to benefit from mitigation efforts, thereby reducing resource waste while maintaining adequate coverage for the critical segment.
Data Source
AI summary
A computer-implemented method, includes identifying, a set of insurance policyholders that have experienced water loss and a second set of insurance policyholders that have not experienced water loss. The method also includes determining an attribute indicative of increased likelihood of future water loss using a predictive model using a percentage of the first set of insurance policyholders defining a first sample size of the first set of insurance policyholders that is smaller relative to a percentage of the second set of insurance policyholders defining the second sample size of the second set of insurance policyholders. Further, the method includes identifying at least one targeted insurance policyholder having an increased likelihood of water loss, based upon the attribute and providing a water loss mitigation strategy to the at least one targeted insurance policyholder.