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Risk Modeling Case Study
The Quantrix LoanDynamics™ Interface
Terms such as "crisis" and "meltdown" are frequently used to describe the current state of the mortgage industry. The risks inherent in credit-sensitive mortgages and related securities have the market clamoring to better understand delinquency, default, and loss severity, as well as prepayment on mortgage loans. The absence of an effective means for analyzing risk was the catalyst for risk analytics and consulting firm, Andrew Davidson & Co., to develop the LoanDynamics™ Model. The model extends current prepayment model subroutines to address the needs of those who are exposed to these risks. For issuers and investors, the LoanDynamics™ Model produces required performance metrics such as CPR (prepayment), CDR (default), 60+ delinquency and loss severity, given loan characteristics and a scenario for interest rate and house price indices.
Andrew Davidson partnered with Quantrix to develop an interface between the LoanDynamics model and Quantrix Modeler. Quantrix Modeler is an integral part of the solution because of the facility it provides to quickly and easily populate the Model with the large volume of required loan level data. Quantrix Modeler then displays the rich set of analytical outputs in an easy-to-digest, multi-dimensional format.
One of many charts showing Quantrix Modeler data visualization capability.
This chart illustrates Cumulative Loss by Month
Quantrix offers capabilities for modeling and analysis of loan data that are unmatched by spreadsheets and two-dimensional modeling tools. The advantages and insights gained with Quantrix can mean the difference between success and failure in industries that are highly sensitive to economic, political, market, and other forces. In this specific case, Quantrix and QLDI deliver success to the mortgage industry with the following benefits:
Key Benefits of the Quantrix LoanDynamics™ Interface (QLDI)
Quick and efficient way to analyze a pool of loans. An intuitive set of menu choices walks analysts through the process of choosing a loan data file, validating the data format, viewing/adjusting/adding Rate and HPI scenarios, running the LDM model and outputting RMP files for Intex bond analysis.
Multi-dimensional Credit Risk Modeling
Multi-dimensional framework allows analysts to model Loan by Loan Attribute by HPI Scenario by Rate Scenario by Period.
Loan Inputs Stratification
Loan Inputs are immediately stratified providing summary analysis by payment status, FICO, Lein, LTV, Documentation, Purpose, Occupancy, Loan Balance and State.
Rate and HPI scenarios can now be modeled independently, allowing the analyst to compare and contrast various combinations of each. Auto-generated charts allow you to visualize scenario choices.
Loan Level or Pool Level
Option to run, model and analyze results at the Loan or aggregated Pool Level.
Output from the LoanDynamics™ Model is returned as a multi-dimensional model with monthly and/or life time results.
Model output is immediately stratified to provide initial loan input analysis plus Expected Loss and Default , and Weighted Average Length in years. Post run stratification can be pivoted to analyze various combinations of key factors, such as Expected Loss, by HPI and Rate Scenarions.
Analyze output vectors such as CDR, CPR and CumLoss in multi-dimensional charts allowing you to visualize the impact of HPI and Rate scenarios.
Quantrix Modeler offers a robust, flexible and transparent modeling environment for follow-on analysis of LoanDynamics™ output.
The LoanDynamics™ Model and Quantrix LoanDynamics Interface have received considerable attention within the Mortgage-Backed and Asset-Backed Securities industries. Leading institutions are adopting the solution to navigate through market turmoil. This case study provides one example of how Quantrix addresses complex risk modeling and analytics challenges.
Click to download the Quantrix LoanDynamics™ Interface datasheet.
For information on how Quantrix can assist your company with its risk modeling challenges, please contact us.