Collateral Selection System for Mortgage Pool Optimization
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Solution Overview
Problem
The random selection process for creating sub-pools of loans in the mortgage market does not account for internal value assessments, leading to potential mismatches between a company's credit risk evaluation and market valuations, and fails to optimize return on equity, thereby limiting a company's ability to competitively bid on guarantees and maintain market presence.
Innovation Solution
A system and method that utilize both external and internal value assessments to create sub-pools, allowing for informed decisions on which loans to guarantee and which to sell, by identifying differences between market and internal credit risk evaluations, thereby optimizing return on equity and maintaining market presence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a random selection process is used to create sub-pools of loans, then the process is simple and fast, but it does not optimize return on equity and creates mismatches between internal and market credit risk evaluations
Solution Approach 1:
The patent segments the loan pool into multiple sub-pools based on different criteria (credit risk, liquidity, yield) rather than random selection. This allows the system to create specialized sub-pools that align with internal value assessments and market conditions, resolving the contradiction between speed and precision by structuring the selection process systematically rather than randomly.
Solution Approach 2:
The patent implements a dynamic collateral selection system that continuously adjusts sub-pool compositions based on changing market conditions and internal assessments. The system can rebalance sub-pools in response to market movements, ensuring ongoing alignment between internal and market credit risk evaluations while maintaining operational efficiency through automated rules-based management.
2Reliability
If a company uses internal value assessments to select collateral, then it can optimize return on equity, but it increases complexity in the selection process
Solution Approach 1:
The patent replaces manual, complex selection processes with an automated computer-based system that applies predefined rules and algorithms. The system automatically compares internal and market credit risk evaluations, identifies mismatches, and executes collateral selection and sub-pool creation without manual intervention, thereby reducing operational complexity while maintaining optimization capabilities.
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously monitors market conditions, internal assessments, and portfolio performance. This feedback loop allows the system to learn from past selections, adjust selection criteria, and improve return on equity over time while maintaining consistent application of selection rules, thereby managing complexity through systematic learning rather than ad-hoc decision-making.
3Productivity
If a company wants to maintain consistent market presence through competitive bidding, then it needs to make informed decisions quickly, but this requires complex real-time analysis of multiple factors
Solution Approach 1:
The patent prepares collateral selection criteria, sub-pool structures, and evaluation frameworks in advance before bidding opportunities arise. The system pre-establishes rules for comparing internal and market assessments, so when a bidding opportunity occurs, the company can quickly apply these pre-prepared frameworks to make informed decisions without conducting complex real-time analysis from scratch.
Solution Approach 2:
The patent uses an automated computer-based system to perform real-time analysis of multiple factors including credit risk, liquidity, yield, and market conditions. The system rapidly processes and compares multiple data points using algorithms that would be impossible to execute manually in real-time, enabling the company to make competitive bidding decisions quickly while maintaining analytical depth.
Data Source
AI summary
Systems, methods, and computer program products are provided for increasing the return from a pool of loans for a company involved in the guarantee and securitization of such loans. In one exemplary embodiment, a computer-implemented method comprises creating a plurality of sub-pools in which to place loans from the pool of loans; determining, using one or more processors, an external value assessment for one or more loans from the pool and an internal value assessment for the one or more loans; identifying a difference between the external and internal value assessments; and selecting a sub-pool from the plurality of sub-pools to place the one or more loans based upon the identified difference.


