Adaptive Claim Intake Flow for Call Representative Guidance
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Solution Overview
Problem
Existing SaaS providers face inefficiencies in claim processing, particularly in insurance claims, due to time-consuming manual procedures and suboptimal use of computational resources, leading to frustration for policy holders and inefficiencies for providers.
Innovation Solution
A computing system that utilizes artificial intelligence and machine learning to optimize claim processing by generating AI prompts for large language models, performing guided content capture, and implementing dynamic scripting and engagement monitoring to streamline information gathering, automate negotiations, and reduce computing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual procedures are used for claim processing, then representatives can handle complex cases with human judgment, but processing time is excessive and productivity is low
Solution Approach 1:
The system enables automated self-service claim processing where the AI agent independently gathers information, processes claims, and communicates with policyholders without requiring constant human intervention. This allows routine claims to be handled automatically while freeing representatives to focus on complex cases.
Solution Approach 2:
The system performs preliminary actions by pre-generating AI prompts, pre-capturing necessary content, and pre-adapting content flows before claims are fully processed. This preparation work is done in advance to accelerate the actual claim processing when representatives need to intervene.
2Adaptability or versatility
If traditional static content flows are used, then system complexity is low, but adaptability to different user needs and claim types is insufficient
Solution Approach 1:
The content flows are made dynamic and adaptable rather than static. The system dynamically adjusts content flows based on user engagement levels, claim types, and individual policyholder needs. This allows the same system to handle diverse claim scenarios effectively without requiring separate rigid workflows for each case type.
Solution Approach 2:
The system changes parameters of content flows in real-time based on user responses and engagement metrics. By adjusting content parameters dynamically rather than maintaining fixed content structures, the system achieves high adaptability while managing complexity through parameterized templates rather than multiple hard-coded workflows.
3Reliability
If comprehensive information gathering is performed, then claim accuracy and completeness improve, but the number of interaction steps increases and user frustration grows
Solution Approach 1:
The system implements continuous feedback loops where user engagement is monitored in real-time and information gathering is adjusted based on this feedback. When users show signs of frustration or disengagement, the system reduces information requests or changes the approach, ensuring claim accuracy is maintained while preserving user experience through adaptive feedback mechanisms.
Data Source
AI summary
A computing system can generate a customized user interface comprising an initial content flow for the call representative to communicate with the user over one or more call sessions to complete an information gather process pertaining to a claim event. Based on inputs provided by the call representative on the customized user interface, the system can dynamically update the customized user interface to reflect responses from the user, and dynamically adapt the initial content flow based on the responses from the user.