Adaptive Call Flow Hopping for Faster Claim Processing
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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 users and call center representatives, leading to frustration and delays.
Innovation Solution
A computing system that utilizes artificial intelligence and machine learning to optimize claim processes by generating AI prompts, performing guided content capture, and facilitating adaptive content flows, enabling efficient information gathering and automated negotiation, while reducing computing power and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual procedures are used for claim processing, then flexibility and human judgment are maintained, but processing time increases and productivity decreases
Solution Approach 1:
The system enables automated self-service claim processing where the claim processing system automatically retrieves data from external systems, performs validation, and updates statuses without manual intervention. The system independently manages the entire claim workflow from initiation to resolution, eliminating dependency on manual procedures while maintaining processing flexibility through configurable rules and automated decision-making algorithms.
2Ease of operation
If traditional communication methods are used between users and call center representatives, then simplicity is maintained, but user engagement and information gathering efficiency deteriorate
Solution Approach 1:
The system introduces an automated communication intermediary that facilitates interactions between users and call center representatives. This intermediary automatically retrieves claim information, prepares relevant data, and presents it to representatives in real-time during calls. The system acts as a mediator that pre-processes information, enabling representatives to engage users more effectively without manual information gathering, thus reducing communication time while enhancing user engagement through personalized, informed interactions.
3Reliability
If comprehensive claim information is collected through manual processes, then data completeness is achieved, but processing time and energy consumption increase
Solution Approach 1:
The system performs preliminary automated actions by proactively retrieving claim information from external systems before claims are formally submitted. The system pre-fetches data from insurance databases, weather services, and other external sources, validating and storing this information in advance. This preliminary action ensures data completeness is achieved automatically without requiring intensive computing resources during the actual claim processing, as the heavy data gathering and validation work is completed beforehand when resources are more readily available.
Data Source
AI summary
Based on an initial set of claim data for a claim event of a user, a computing system can generate an initial script and a content flow that includes the initial script for a call representative to utilize in a call session with the user, the content flow comprising a plurality of sub-flow groupings. Based on the user initiating a topic corresponding to a respective sub-flow grouping from the plurality of sub-flow groupings, the system can update the content flow to enable the call representative to hop to the respective sub-flow grouping within the content flow.


