Mortgage Data Processing System for Error Correction
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Solution Overview
Problem
The current mortgage-backed security (MBS) market faces challenges in data reporting efficiency, with discrepancies between servicer and purchaser data often leading to errors and delayed resolution, which can result in inaccurate payment data and undesirable financial consequences, such as unpaid interest being paid by the servicer.
Innovation Solution
A data processing system that generates payment projections, modifies loan characteristic data to correct errors, and allows for near-real-time processing and reporting of payment data, enabling servicers to report closer to the MBS reporting deadline while facilitating faster discrepancy resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If servicers report servicing data closer to the MBS reporting deadline to improve timing efficiency, then reporting timeliness is improved, but data accuracy deteriorates due to insufficient time for error detection and resolution
Solution Approach 1:
The system performs preliminary actions by generating payment projections in advance of the reporting deadline and comparing them with actual payment data as it becomes available. This allows error detection to begin early in the reporting cycle, enabling sufficient time for discrepancy resolution even when reporting close to the deadline.
Solution Approach 2:
The system implements continuous feedback mechanisms by comparing actual payment data against projected payment data throughout the reporting cycle. When discrepancies are detected, the system provides feedback to identify the nature and source of errors, enabling rapid correction and improving data accuracy without sacrificing reporting timeliness.
2Measurement precision
If more time is allocated for error detection and resolution to improve data accuracy, then data accuracy is improved, but reporting efficiency deteriorates due to delayed reporting
Solution Approach 1:
The system maintains continuous useful action by constantly comparing actual payment data against projections throughout the reporting cycle rather than performing a single batch check at the end. This continuous monitoring enables early detection and resolution of discrepancies, maintaining high data accuracy while enabling timely final reporting.
Solution Approach 2:
The system replaces manual, labor-intensive error detection and resolution processes with automated computational methods. The computer system automatically generates projections, compares them with actual data, identifies discrepancies, and facilitates resolution, dramatically improving both data accuracy and reporting efficiency simultaneously.
3Measurement precision
If manual error detection and resolution processes are used to ensure thorough data verification, then data accuracy is improved, but processing time increases and efficiency deteriorates
Solution Approach 1:
The system substitutes manual mechanical processes with automated electronic computation. The computer system automatically generates payment projections using stored loan data, compares these projections with actual payment data received from servicers, identifies discrepancies, and facilitates resolution. This automation maintains thorough verification while reducing processing time from days or weeks to hours or minutes.
Solution Approach 2:
The system enables self-service error detection and resolution by providing automated comparison tools and discrepancy identification that allow servicers and purchasers to quickly identify and correct errors without extensive manual intervention. The system serves itself by automatically performing tasks that would otherwise require significant human effort.
Data Source
AI summary
A method of processing data in connection with a security is provided. The security is collateralized by a plurality of home mortgage loans or by portions of the plurality of home mortgage loans. The method comprises generating payment projections regarding principal and interest payment projections for the plurality of home mortgage loans; determining that the payment projections have errors; and modifying loan characteristic data to eliminate errors in the loan characteristic data that cause errors in the payment projections. According to another embodiment, a method comprises receiving payment data regarding the plurality of loans a plurality of times separated by a plurality of days during the reporting cycle. Each time the payment data is received, the payment data is processed and the opportunity to make corrections is provided.