Claim Information Gathering With Personalized Reminder Strategies

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Solution Overview

Problem

Existing Software as a Service (SaaS) providers face inefficiencies in claim processing, particularly in insurance claims, due to time-consuming manual procedures and suboptimal communication with policy holders, leading to frustration and delays.

Innovation Solution

A computing system that utilizes artificial intelligence and machine learning to optimize information gathering processes, including dynamic scripting, guided content capture, and adaptive communication strategies to streamline claim handling, leveraging large language models for summarization and automated negotiation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual procedures are used for claim processing, then communication with policy holders can be personalized, but processing time is excessive and efficiency is low

Engineering Contradiction:

Improveclaim processing speedVSAvoidtime spent on manual procedures

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system implements automated self-service capabilities where AI agents independently communicate with policy holders, gather information, and process claims without requiring manual human intervention for each interaction. The AI system serves itself by autonomously navigating the claims process while maintaining personalized communication.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical procedures are replaced with an AI-based automated system that uses machine learning models and natural language processing to handle claim processing. The mechanical manual workflow is substituted with an intelligent automated workflow that maintains personalization while dramatically improving speed and efficiency.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated systems are implemented, then processing efficiency improves, but communication personalization may be reduced

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidcommunication quality with policy holders

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The AI system dynamically adjusts communication parameters such as tone, language style, and level of detail based on the specific policy holder and situation. This allows automated communication to maintain personalization by changing communication parameters rather than following a rigid template.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system incorporates feedback loops where AI agents monitor policy holder responses and adjust their communication strategy in real-time. This feedback mechanism enables the automated system to adapt to individual preferences and maintain high-quality personalized communication while processing claims efficiently.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20260050928A1Implementing first contact and personalized reminder strategies for information gathering processes

Publication Date: 2026.02.19 ASSURED INSURANCE TECH INC

AI summary

A computing system can induce a network effect for an information gathering process by receiving information from a computing device of a user, the information identifying one or more individuals to provide additional information for a claim process of the user. The system can initiate first contact through communications with a computing device of each of the one or more individuals to receive information pertaining to the claim process. Based on a set of response data from each individual of the one or more individuals, the system can generate an optimized reminder strategy to provide reminders to each individual to complete a content flow corresponding to the claim process.