Life-Time Value Financial Processing in Relational Database
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Solution Overview
Problem
Businesses face challenges in calculating long-term profitability and growth, as existing tools are limited in integrating current financials with future metrics, attrition rates, and growth values to determine the life-time value of customers and business facets.
Innovation Solution
A Life-Time Value (LTV) system that uses a data-driven computer-facilitated financial model, integrated with a Relational Database Management System (RDBMS), performs Net Present Value (NPV) and Future Value (FV) processing, applying growth, attrition, and propensity values to provide accurate profitability projections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional profit and loss statements and current value measurements are used, then current financial performance is tracked, but long-term profitability and life-time value cannot be calculated
Solution Approach 1:
The patent segments the life-time value calculation into distinct components: current period profit components, forecast period definitions, growth values, attrition values, and propensity values. Each component is stored as separate data structures in the RDBMS, allowing precise calculation while maintaining adaptability to modify individual segments without affecting the entire system.
Solution Approach 2:
The patent adds a temporal dimension by introducing forecast periods that extend beyond current financial data. The system creates multiple time dimensions (current period vs. forecast periods) and applies attrition and growth values across these dimensions, enabling life-time value calculation that spans multiple time horizons while integrating future metrics.
2Measurement precision
If comprehensive financial data processing is performed, then accurate life-time value projections are achieved, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary layer between the RDBMS and the life-time value calculation engine. This intermediary consists of standardized data structures and interfaces that simplify complex financial data processing. The system uses intermediate tables to store calculated values (attrition, growth, propensity) that can be reused across multiple calculations, reducing overall system complexity while maintaining accuracy.
Solution Approach 2:
The patent manages complexity by parameterizing the calculation system. Instead of hardcoding complex processing logic, the system uses configurable parameters such as forecast period definitions, attrition rates, growth values, and propensity values. These parameters can be adjusted without changing the underlying system architecture, allowing accurate projections while keeping the system manageable.
3Measurement precision
If multiple forecast periods and methodologies are defined, then future value calculations become more accurate, but data processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing attrition values, growth values, and propensity values in the RDBMS before they are needed for life-time value calculations. Forecast periods and methodologies are predefined and stored as configuration data. This preprocessing eliminates the need for complex real-time calculations, reducing processing time while maintaining accuracy.
Solution Approach 2:
The patent enables continuous useful action by implementing a system where forecast data, attrition rates, and growth values can be updated and reused across multiple calculations. Once data is loaded into the RDBMS, it can be continuously queried and used for various life-time value analyses without reprocessing, maintaining accuracy while minimizing processing time for subsequent queries.
Data Source
AI summary
A Life-Time Value (LTV) system is a data-driven computer-facilitated financial model that provides accurate and consistent profitability projections using current period account level profitability data stored in a Relational Database Management System (RDBMS). The Life-Time Value system performs Net Present Value (NPV) and Future Value (FV) processing using business-rule and data-driven applications that embrace the current period profit components, defines forecast periods, parameters and methodologies, and applies appropriate growth values, attrition values and propensity values to an object of future value interest.