Customer Data Analytics Engine for Insurance Trend Identification
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Solution Overview
Problem
Identifying trends in business processes, particularly those involving customer interactions, is a time-consuming and expensive task due to the large number of individual actions that need to be manually reviewed, and requires consideration of specific business contexts such as changes in regulations.
Innovation Solution
A system and method that utilizes a customer data analytics engine to receive and analyze point of service customer interaction data in conjunction with external third-party information, systematically identifying trends and mapping them to specific business process actions, and outputting recommendations for changes to improve business processes efficiently and accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review of individual customer interactions is performed to identify trends, then measurement precision is improved, but loss of time and productivity deteriorate
Solution Approach 1:
The patent replaces manual mechanical review of customer interactions with an automated computer-based system that uses natural language processing, machine learning, and data analytics to systematically analyze customer interaction data, identify trends, and generate insights without human intervention
Solution Approach 2:
The system creates digital copies and representations of customer interaction data, transforming unstructured text and audio data into structured formats that can be systematically processed and analyzed by computational algorithms to identify patterns and trends
2Measurement precision
If manual review of individual customer interactions is performed to identify trends, then measurement precision is improved, but productivity deteriorates
Solution Approach 1:
The patent replaces manual mechanical review of customer interactions with an automated computer-based system that uses natural language processing, machine learning, and data analytics to systematically analyze customer interaction data, identify trends, and generate insights without human intervention
Solution Approach 2:
The system enables continuous automated analysis of customer interaction data as it is generated, allowing for real-time or near-real-time trend identification and continuous generation of business insights without the interruptions and limitations of manual review processes
3Measurement precision
If comprehensive analysis of customer interactions with business context is performed, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex analysis task into distinct modular components including data collection modules, natural language processing modules, trend identification modules, and reporting modules, allowing each component to handle specific aspects of the analysis independently
Solution Approach 2:
The system introduces intermediary processing layers including natural language processing intermediaries that translate unstructured customer interaction data into structured formats, and analytical intermediaries that bridge raw data with business context to generate meaningful insights
Data Source
AI summary
According to some embodiments, an insurance business process may have a series of business process actions. Moreover, point of service customer interaction data associated with the insurance business process may be received along with external third-party information associated with a context of the insurance business process. Based on the external third-party data, the point of service customer interaction data may be systematically analyzed to identify a trend. The trend may be analytically mapped to a first business process action in the insurance business process. An indication of a recommended change to the first business process action may then be output based at least in part on the identified trend.