Changepoint Calculation for Policy Entitlements
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Solution Overview
Problem
Existing systems that rely on loop-based code for complex calculations in policy environments are inefficient, as they test outcomes at every possible data point, even when only a small segment of data is of interest, leading to unnecessary computations and inefficiencies in determining entitlements and obligations.
Innovation Solution
A computer-implemented system and method that calculates and displays changepoints using time-based values and changepoint values, allowing for simplified and reliable calculations by combining time-based parameters with changepoint values, and generating reports in plain language, thereby reducing unnecessary computations and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If loop-based code tests outcomes at every possible data point, then comprehensive coverage of all data points is achieved, but computational efficiency deteriorates due to unnecessary calculations
Solution Approach 1:
The patent segments the continuous data range into discrete intervals defined by changepoints. Instead of processing every possible data point, the system identifies critical boundary points where policy rules change and segments the data accordingly. This allows the system to process only relevant segments rather than iterating through all possible values, resolving the contradiction between comprehensive coverage and computational efficiency.
Solution Approach 2:
The system performs preliminary identification of changepoints before executing the main calculation logic. By pre-calculating and storing the dates when policy rules change (changepoints), the system avoids the need to test every data point during entitlement calculations. This preliminary action enables the system to jump directly to relevant calculation points, maintaining comprehensive coverage while dramatically improving efficiency.
2Reliability
If loop-based code calculates values at every possible data point, then complete calculation coverage is achieved, but processing time increases significantly
Solution Approach 1:
The patent extracts and isolates the critical information (changepoints) from the vast set of all possible data points. By separating the essential boundary points where policy changes occur from the irrelevant intermediate points, the system maintains calculation completeness while eliminating unnecessary processing. The extraction of changepoints allows the system to focus computational resources only on dates that actually affect entitlement outcomes.
Solution Approach 2:
The system changes the parameter from continuous data points to discrete changepoint values. Instead of iterating through every possible date in a time range, the system transforms the problem into processing a limited set of discrete parameter values (changepoints) where policy rules actually change. This parameter transformation maintains reliability by capturing all rule change points while reducing processing time by eliminating iterations over unchanged periods.
3Measurement precision
If complex calculations are performed on all data points, then accurate entitlement determination is achieved, but system complexity increases
Solution Approach 1:
The patent segments the complex calculation space into manageable intervals bounded by changepoints. By dividing the continuous time range into discrete segments where policy rules remain constant, the system simplifies the calculation process. Within each segment, the same policy rules apply, allowing the system to perform accurate entitlement determinations without repeatedly evaluating all policy rules at every data point, thus reducing system complexity while maintaining accuracy.
Solution Approach 2:
The system performs preliminary identification and storage of changepoints before the main entitlement calculation process. This preliminary action organizes the complex policy rules into a structured format where change points are pre-marked, allowing the calculation engine to efficiently navigate through relevant periods. This pre-organization reduces system complexity by providing a clear framework for processing, eliminating the need for complex nested loops that would otherwise be required to handle all policy rule interactions at every data point.
Data Source
AI summary
A computer implemented method and system for calculating changepoints in a rule-based environment. At least one time-based value is created from at least one date value, and combined with at least one changepoint value to calculate changepoints. The changepoints are then formatted, and a report is generated and output for display to the user in plain language. In another aspect, a value is assigned to a time-based parameter and combined with a changepoint value to calculate changepoints.