Credit Decisioning Using Activity Based Costing and Compartmental Modeling
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Solution Overview
Problem
The existing credit scoring process in banking is deterministic and subjective, leading to arbitrary cutoff scores that do not maximize profitability, as they are often based on business conditions and updated infrequently, resulting in suboptimal loan decisioning.
Innovation Solution
A method using compartmental workflow modeling, activity-based costing, and regression analysis to determine a cutoff score that maximizes profitability by analyzing pass and bad rates, transfer coefficients, and occupancy values, allowing for quick adjustments when costs change.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a deterministic credit scoring method with fixed cutoff scores is used, then the credit decisioning process is simple and fast, but the profitability is not maximized due to arbitrary and infrequently updated cutoff scores
Solution Approach 1:
The patent transforms the static, fixed cutoff score system into a dynamic one where cutoff scores are continuously optimized based on real-time workflow data, pass rates, bad rates, and activity-based costing. The system automatically adjusts cutoff scores as business conditions change, eliminating the need for manual updates while maintaining profitability optimization.
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously monitors workflow data, pass rates, bad rates, and cost information, then uses this feedback to recalculate and optimize cutoff scores. This closed-loop system ensures that cutoff scores remain aligned with current business conditions and profitability goals without manual intervention.
2Ease of operation
If subjective business understanding is used to determine cutoff scores, then the process is easy to implement, but the scores are arbitrary and do not reliably maximize profit
Solution Approach 1:
The patent replaces the subjective, manual process of determining cutoff scores based on business understanding with an automated computational system. The system uses objective data from workflows, scorecards, and costing models to calculate optimal cutoff scores, eliminating human subjectivity while maintaining ease of operation through automated processing.
Solution Approach 2:
The patent enables the system to automatically determine and update its own cutoff scores without requiring external expert input or manual adjustment. The automated system uses its own workflow data and business parameters to self-optimize cutoff scores, making the process both easy to operate and precisely aligned with profitability goals.
3Reliability
If comprehensive workflow analysis and activity based costing are implemented, then profitability optimization is achieved, but the initial setup complexity increases
Solution Approach 1:
The patent performs comprehensive workflow analysis, compartmental modeling, and activity-based costing during the initial setup phase to establish the optimization framework. Once configured, the system automatically uses this pre-established model to continuously optimize cutoff scores without requiring repeated complex analysis, thus achieving high reliability while managing setup complexity through one-time configuration.
4Ease of operation
If traditional credit scorecards are used with fixed pass and bad rates, then the scoring process is straightforward, but the rates do not reflect current business conditions
Solution Approach 1:
The patent transforms the static pass and bad rates in traditional scorecards into dynamic rates that are continuously updated based on current workflow data and business conditions. The system automatically recalculates these rates as new data becomes available, maintaining both the simplicity of using scorecard-based scoring and the adaptability to reflect current business conditions.
Data Source
AI summary
Method and system for credit decisioning using activity based costing and compartmental modeling. Credit product profitability for a financial institution using credit scorecards is improved by providing an analysis that results in a recommended credit cutoff score for a particular loan product. The selected cutoff score is determined with input including pass and bad rate parameters for the pertinent scorecard, workflow analysis for the loan process, compartmental modeling of the workflow, and activity based costing (ABC) for the workflow. In some embodiments, data related to portions of the analysis for a particular scorecard is saved for re-use, so that a new cutoff score for a particular type of loan can be determined relatively quickly and easily if only the financial institution's costs have changed.


