Aon has filed a patent for systems and methods to monitor insurance claims. The technology involves identifying claims for vulnerability detection processing, extracting vulnerability detection features from claim data files, and using a trained vulnerability detection data model to detect claim handling vulnerabilities. The system calculates vulnerability scores indicating the likelihood of claim leakage and presents them on a user interface screen. Claim 1 has been canceled. GlobalData’s report on Aon gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData, Aon's grant share as of September 2023 was 41%. Grant share is based on the ratio of number of grants to total number of patents.
Systems and methods for monitoring insurance claim handling vulnerabilities
A recently filed patent (Publication Number: US20230281723A1) describes a method and system for automating claims handling. The method involves obtaining historic claims data and training machine learning models to identify vulnerabilities in claims that are costly or difficult to resolve. The system includes a data store, machine learning models, and processing circuitry.
The method begins by obtaining historic claims data, which consists of documents corresponding to closed claims of an organization. Using this data, machine learning models are trained to identify vulnerabilities in claims that are likely to result in increased cost or difficulty of resolution.
Next, new claims data is accessed, which includes both unstructured and structured data documents corresponding to open claims. The processing circuitry analyzes the new claims data by extracting text portions from unstructured data documents and applying the trained machine learning models to identify vulnerabilities in the open claims. For each claim identified with vulnerabilities, a severity level is determined based on the exhibited vulnerabilities, indicating the likelihood of increased cost or difficulty of resolution.
If a claim has a severity level at or above a predetermined level, an alert is associated with the claim. The alert can be presented in a user interface screen, providing summary information about the vulnerabilities of the claim. Additionally, an alert summary can be presented at a user interface, providing information on multiple claims with vulnerabilities.
The system includes a non-transitory machine-readable data store to store open claims data, machine learning models to identify claim vulnerabilities, and processing circuitry to perform the operations. The machine learning models are trained using historic claims data, which includes both unstructured and structured data documents. The processing circuitry extracts text portions from unstructured data files and applies the machine learning models to identify vulnerabilities in the open claims. The severity level for each claim is determined based on the exhibited vulnerabilities, and alerts are associated with claims that meet the predetermined severity level.
Overall, this patent describes a method and system that automates claims handling by using machine learning models to identify vulnerabilities in claims and associate alerts with claims that pose a higher risk of increased cost or difficulty of resolution. This can help organizations streamline their claims handling process and prioritize resources effectively.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
