Policyholder Retention Scoring via Automated Value Engines
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Solution Overview
Problem
Determining the value of policyholders for insurance companies is a labor-intensive and time-consuming process, especially when dealing with potential policy lapses, as it involves assessing the retention value and financial distress of customers.
Innovation Solution
A triaging system comprising a Value Engine, an Analytical Engine, and a Scoring Engine that determines cash flows, builds underwriting models, and calculates client scores to assess the retention value of policyholders, facilitating re-underwriting and predicting the likelihood of policy lapses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual assessment methods are used to determine policyholder value, then accuracy of evaluation may be maintained, but labor intensity and time consumption increase significantly
Solution Approach 1:
The patent replaces manual mechanical assessment processes with an automated computer-based system that uses machine learning models and algorithms to calculate policyholder retention values, thereby reducing time consumption while maintaining or improving assessment accuracy through consistent application of standardized criteria
Solution Approach 2:
The system enables self-service by automatically gathering policyholder data, performing retention value calculations, and generating assessments without requiring manual intervention, allowing the system to serve itself in processing and evaluating policyholder information efficiently
2Reliability
If comprehensive data analysis is performed to assess policyholder retention value, then decision quality improves, but system complexity increases
Solution Approach 1:
The patent segments the complex analysis system into distinct functional modules including data collection components, machine learning model processing units, and output generation systems, allowing each segment to handle specific aspects of the analysis independently while contributing to the overall reliable decision-making process
Solution Approach 2:
The system introduces intermediary elements such as standardized data processing protocols and intermediate calculation layers that bridge raw data and final retention value assessments, simplifying the overall system architecture while maintaining comprehensive analysis capabilities through structured intermediate steps
3Productivity
If automated scoring systems are implemented, then processing efficiency increases, but nuance in individual case evaluation may be lost
Solution Approach 1:
The patent implements dynamic scoring models that can adapt and adjust weights of different factors based on individual policyholder characteristics and circumstances, allowing the automated system to maintain processing efficiency while capturing nuances in individual cases through flexible, non-rigid evaluation criteria
Data Source
AI summary
Disclosed here is a triaging system, including a value engine, an analytical engine, a scoring engine, and databases storing internal, external, and retention value data. A value engine may be configured to receive information and determine a value associated with a policy; an analytical engine may be configured to receive information related to one or more factors associated with a policyholder, as well as actuarial relationships between the one or more factors; and a scoring engine may be configured to receive information associated with a policyholder from one or more value engines and analytical engines, and may output a scalar score associated with the retention value of the policyholder. The system may determine the value of retention associated with the policyholder and use this value to build and store a client score, where the client score may be a scalar representation of the value of retaining business with the policyholder.