Insight Report: Quantifying the Accuracy of Rep Line vs. Loan Level Data for Cashflow Generation

23 October 2017

Data Science at dv01: Data Pipelines and the Spark Query Plan as a Source of Data


Cashflow projection and analysis is a critical process for investing in fixed-income markets. In this new Insights report, we use dv01’s cashflow engine to study the accuracy and efficiency of cashflow generation methods at different degrees of granularity, from a single loan rep line, to rep lines across multiple attributes, to loan level data.

Our analysis shows that the rolled balance rep line methodology widely used for securitization deals can create significant inaccuracy for cashflow projections, resulting in cashflow errors as high as 2.9% only two months after the closing of the deal.

For more details on this analysis and suggestions on how to quickly generate accurate cashflows using loan level collateral data, download the Insights report below.

Click here to download the full report.


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