Geolocation-Based Asset Reconciliation for Disaster Market Rates
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Solution Overview
Problem
The high demand for remediation services during disasters leads to increased costs due to scarcity of high-value assets and inefficiencies in determining market rates, as insurance carriers struggle to assess accurate market rates amidst volatile conditions and lack of historical asset deployment logs.
Innovation Solution
A data processing system that receives and analyzes geolocation data of assets to determine accurate market rates by selecting suitable assets for tasks based on real-time geolocation parameters, generating candidate task allocations, and providing task comparisons to third parties, ensuring accurate market rate determination and real-time asset allocation adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If assets are deployed to high-demand areas during disasters, then service availability in affected areas improves, but asset scarcity in other areas increases driving up rates
Solution Approach 1:
The system implements real-time feedback by continuously monitoring asset locations, task allocations, and market rates across different service areas. This feedback loop enables dynamic adjustment of asset deployment strategies, allowing the system to respond to changing demand conditions and prevent both over-concentration and under-utilization of assets in any given area.
Solution Approach 2:
The system performs preliminary actions by proactively identifying emerging demand patterns and potential asset shortages before they fully materialize. By analyzing historical data and real-time conditions, the system can pre-position assets or prepare allocation strategies in advance, preventing service disruptions and rate volatility.
2Measurement precision
If market rates are determined after work is performed, then payment accuracy improves, but time to determine rates increases significantly
Solution Approach 1:
The system performs preliminary actions by pre-establishing market rate benchmarks and asset allocation patterns before disaster events occur. Historical data is analyzed and stored in advance, creating a ready-reference framework that enables rapid rate determination during high-volume claim periods without sacrificing accuracy.
Solution Approach 2:
The system implements dynamic rate determination that adapts to changing market conditions in real-time. Rather than using static post-event analysis, the system continuously updates market rates based on current asset availability, demand patterns, and geographic conditions, enabling accurate pricing even during rapidly evolving disaster scenarios.
3Device complexity
If historical logs of asset deployment are not maintained, then system complexity decreases, but ability to determine actual market rates deteriorates
Solution Approach 1:
The system implements a multi-functional data collection framework where the same infrastructure serves multiple purposes: tracking asset locations for allocation decisions, maintaining historical logs for market rate analysis, and providing real-time visibility for both providers and insurers. This universal approach eliminates the need for separate specialized systems.
Solution Approach 2:
The system enables self-service by automatically collecting, storing, and analyzing asset deployment data without requiring manual intervention. Providers and insurers can independently access historical logs and market rate information through the platform, eliminating the need for complex manual data reconciliation processes.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for reconciling assets based on geolocation. In one aspect, a method includes selecting assets having geolocation parameter data satisfied by the first location, and using these selected assets as a basis for a task comparison summary.