New Century Data Tool
IP RECOVERY, INC. PRESENTS AN EXTRAORDINARY DATA TOOL FOR VALUING MORTGAGE-BACKED SECURITIES, REVISING CREDIT, PRICING AND DEFAULT MODELS, AND INITIATING AND DEFENDING AGAINST SUBPRIME MORTGAGE-RELATED LITIGATION
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As part of the NEW CENTURY FINANCIAL CORPORATION bankruptcy proceedings, IP Recovery, Inc. purchased from the New Century Liquidating Trust a unique and comprehensive collection of loan origination data, servicing data, performance data, rejection data and broker data for loans originated/serviced by New Century between 1997 and its bankruptcy filing in 2007.
New Century was, of course, the second largest originator of subprime mortgage loans in the United States. At the time of its bankruptcy filing in March 2007, it was the largest subprime mortgage lender ever to fail.
IP Recovery, Inc. is making this data available on a non-exclusive, perpetual license basis so that you may analyze the data on your own equipment or access it, remotely, through a facility provided by IP Recovery, Inc.
A description of the data and its many applications follows below. For pricing details, database "screenshot" samples and answers to any specific questions that you may have, please contact us.
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The New Century loan data is of unprecedented data/analytics and litigation value to:
- Banks, hedge funds, pension funds, fund managers, insurance companies and other financial institutions holding CDS, CMOs and other asset-backed securities;
- Large-scale investors seeking to value, purchase or sell asset-backed securities, particularly but not exclusively those backed by subprime mortgages;
- Plaintiffs' and defendants' counsel, and their experts, in asset-backed securities litigation involving lenders, issuers, underwriters, rating agencies, accounting firms, bond insurers, hedge funds, collateralized debt obligation trusts, etc.;
- Derivative, bond and other security-rating agencies;
- Think-tanks / policy institutes;
- Academic institutions;
- Vendors of business intelligence, risk analysis and credit assessment-related software and services; and
- State and Federal regulators and prosecutors.
This data (sample database "snapshots" will be provided upon serious inquiry) can not be found anywhere else. Nor can the information provided here be approximated from any other sources, as New Century did not report this data to LPS, Intex or other sources.
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The lack of historical data with which to validate the efficacy of past and current CDS/CMO pricing and valuation models was a significant contributor to the ongoing subprime crisis.
Even small changes in underlying assumptions or data can lead to dramatic and unexpected changes in valuation. Reliance upon Gaussian copula functions which minimized or eliminated the review of historical default data was, and remains, a recipe for disaster.
The New Century database, which covers all 3.2 million New Century originated loans, including all loans which collateralize the currently-traded NCHELT notes, presents an entire chapter of financial history, and will give you an unique opportunity to mine its data for as-yet-undiscovered default and default correlation insights.
Recent reports indicate that we are facing a similar imminent crisis as pay-option ARM and adjustable-rate hybrid ARM defaults surge.
The New Century data provides an unprecedented window into the specific conditions underlying past market failures. Understanding what actually happened with subprime mortgages and their related securities can help prevent future debacles involving option ARMs and other financial products.
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Access to this database will benefit your (or your customers’ or clients’) data analytics/quantitative research by enabling you to:
- ascribe a more accurate present value to any subprime mortgage-backed securities (however packaged) that you currently manage, hold, intend to purchase, have written off, or are contemplating writing off;
- better predict future performance of mortgage-backed securities and related assets, based upon a detailed, comprehensive historical data set;
- identify and quantify known and as-yet-unknown temporal, geographic and demographic default correlations;
- improve your ability to gauge probabilities of multiple defaults in and across all current and future mortgage-backed securities;
- enhance your existing credit models and multiple-default modeling techniques and algorithms;
- refine your pricing models for all products traded in the credit derivative market; and
- supplement (or supplant) historical data that you have already generated internally, or received from outside Structured Finance Indices or other sources.
While the New Century data's value is obviously heightened vis-à-vis the various NCHELT notes, data this granular will necessarily provide deep, unique insight re the current state and future performance of ANY mortgage-backed security.
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By illuminating such a wide swath of the historical subprime picture, its structure and its failures, this data will also benefit your (or your customers’ or clients’) litigation posture, by helping you to better:
- prepare for/defend against/obviate actions brought by state and federal regulators, state and federal prosecutors and private citizens relating to, inter alia, alleged unfair and deceptive lending practices involving sub-prime mortgages, ongoing investigations regarding hedge fund marketing practices, FINRA Conduct Rule 2310 and IM 2310-3 proceedings, shareholder derivative lawsuits, ERISA lawsuits and the like;
- prepare for litigation against brokers and appraisers involved in the origination of sub-prime mortgage loans; and
- unwind pooled tranches of investment paper into its constituent loans, and trace some-if-not-all of the chain of title of specific loan paper.
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The New Century database is populated principally with private data, not otherwise available in the public domain. The database is roughly 44 gigabytes (44GB) in size, containing 871 origination and servicing data attributes for each of 3.2 million sub-prime loans, including but not limited to:
- borrower and co-borrower demographics;
- ethnicity, gender, age;
- income, FICO, employer;
- county, zip, doc type (full, stated, no-doc, etc.);
- program (fixed, variable, rate, and terms of the adjustments);
- front end and back end ratio;
- price, LTV, funding date;
- occupancy description;
- note rate, amount and maturity;
- underwriting credit grade;and much more.
Additionally, there are 150 attributes for each of 200,000+ Broker Data records.