1 / 20

May, 2013

Hub for Student Loan Data Competitive Advantage in Sharing Data with Investors. May, 2013. Outline of the Presentation . Introduction to MeasureOne and myself What is the Dig Deal with Providing Investors with Loan Level Data What are the trends A Case Study Q and A .

gaura
Download Presentation

May, 2013

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Hub for Student Loan Data Competitive Advantage in Sharing Data with Investors May, 2013

  2. Outline of the Presentation • Introduction to MeasureOne and myself • What is the Dig Deal with Providing Investors with Loan Level Data • What are the trends • A Case Study • Q and A

  3. What are MeasureOne’s to Qualifications? • Led by Founder and CEO Dan Feshbach • Created the LoanPerformance database and invented data sharing in the mortgage space • Grew from 5 charter members contributing 1 million loans to every major lender in mortgage, tracking 50 million payments a month • 20+ years of experience in building industry wide databases: • Operating a neutral third party data hub • Handling sensitive data • Managing questions, issues, and feedback regarding data content and interpretation • Providing data to investors, dealers, rating agencies and regulators

  4. Experienced Team of Student Loan Data and Capital Markets Professionals Dan Feshbach Dana Arvidson CEO Director Capital Markets and Products • 8 year tenure at First Marblehead • Head of equity and debt investor relations • Met with hundreds of PSLABS investors • Deep knowledge of investor data and analytics requirements • 25+ years experience building cooperative business information databases • Founder and former CEO, LoanPerformance, the leading source of loan level information on mortgage loan performance Rushali Parikh Andrea Murad Director of Data and Analytics Student Loan Ratings Expert • Worked on Student Loan ABS originations at Deutsche Bank in New York • Involved in new client pitches, rating process, preparing offering documents, structuring cashflows, addressing investor concerns • Collateral analysis of loans underlying student loan deals • Former Senior Director at Fitch Ratings • Over 10 years experience in student loan ratings • Developed criteria for new FFELP and Private student loan issuances • Rated hundreds of deals • Authored articles and special reports for Fitch Ratings

  5. What We Do - Platform for analyzing student loan Securities and Whole Loans Turnkey Collateral and Bond Analytics Capabilities Data and Metric Standardization Investor and Rating Agency support and communication services Transaction support - facilitate analysis of the sale of securities and whole loans: Dashboards; Bond Analytics; Data Room; Support Services

  6. The Trends in Loan Level Data Disclosure Investor Driven Regulatory Driven Competition Driven • Experience during the mortgage meltdown • Investor drive to independently analyze security performance in house • Rating agency missteps / failure • Reg AB started it • OCC and Federal Reserve Loan Level Databases • Reg AB ii is coming • Fannie and Freddie Loan Level Releases on government guaranteed • Opportunity to take a leadership position • Competition with mortgage and other complex asset classes • Business requirements – most companies even the biggest are data poor in something • Mortgage, Credit Card, Small Business, Auto data cooperatives

  7. Student Loans: More Complex Credit and Cashflow Risk than Mortgage • Long weighted-average life • Borrowers with little-to-no credit history • Dizzying set of factors affect the timing and absolute level of cash flows – Borrower benefits, loss mitigation • Investors express universal frustration with no central, standardized data repository • Limits investor base size impact new issuance and trading

  8. What are your data assets? Unstructured Data Structured Data • Web and mobile customer interactions • Email • Chat • Text • Call Center interactions • IVR • Call center notes • Social media Data • Lender/Issuer • Loan Level • Application – • Denied • Approved • Underwriting files • Servicing • CRM Marketing Data • Enhanced Data • Credit Bureau Data, Utilities data • Employment Data There are also Data Assets that you have access to

  9. Who cares about Student Loan Performance Data? Credit Community Lending Community Investment Banks Investment Banking Investors Lenders Issuers Loan Buyers Banks, Credit Union Servicers Collectors Bond Insurers Rating Agencies Syndicate Desk Risk Management Government Education Sector Sales and Trading Warehouse Lending Students Departments of Education Consumer Finance Protection B Secondary Trading Whole Loan Trading Colleges and Universities Congress, Legislatures Federal Reserve, OCC, FDIC,

  10. Core Issues Limiting Investor Participation in the Market Inconsistently Calculated Metrics and Content Accessibility • Data scattered across 40+ websites • Limited research coverage • Lack of up to date rep lines • Lack of loan level data to analyze performance • Key metrics including Net WAC, CPR, and CDR often unavailable • Calculated differently by each issuer • The time cost of access of the limited data available keeps investors from wanting to get up to speed on the asset class

  11. What Loan Level Data Do Investors Care About? • Geographic Information • Product Information • Product type (consolidation) • Loan Program (PLUS, Subsidized Stafford, Unsubsidized Stafford… • School Information • Major (Business Science Liberal arts, Health Science • In school/Grace/Drop-out Status) • Reported Year in School • School Type (For profit, Public, Private, 2 yr, 4 yr) • Credit Information • #,$ student loans • #, $ credit card, auto, mortgage and other debt • Credit Score • Performance Information • Delinquency (30,60,90 …Days past Due) • Default • Claim and Loss • Prepayment (Consolidation Driven, Borrower Driven, Default Driven) • Payment Plan Utilization (IBR, Graduated Repayment…) • Deferment/Forbearance/Deferment Utilization (Total, time in status, Number of Uses…) • In-school/Grace/drop out Status (Total, Time Remaining) • Collections (Amount Collected , aging…) • Recoveries

  12. Case Study – Private Student Loan Portfolio Sale MeasureOne’s Role Deal Data Manager • Hired by the seller to be deal data manager • Provided secure data room for documents related to the deal • Reporting and Analysis Platform to enable investors to enable investors to quantify and project performance and create rep lines • Loan Level Files for investors who wanted to build models or conduct analysis in house • 24 - 7 Support Number of data users • 5 Dealers • 25 investors • 50 + licenses to access theMeasureOne”sAnalysis Platform

  13. Student Loan Analysis Platform – Predefined Dashboards: Investors Get Up to Speed Quickly Overview of the Portfolio with Easy Drill Down

  14. Turnkey analytics: roll rate analysis with one click

  15. Example of an investor email data request

  16. What Data did Investors Request: Some Examples • Roll rates • 1M, 3M, 6M Roll rates, loan count and balance moving between statuses and between delinquency buckets • Detailed statistics re modifications, forebearance, deferrment, and loan modifications • Payment Modification Grant Rate • Detailed Prepayments break outs • Scheduled payment, Negative Amortization, Consolidation, Borrower Prepayment, Borrower Curtailment • Flexible repline creation

  17. Issues Lenders and Issuers have in Sharing Loan Level Data Are lenders giving up competitive advantage by enabling lenders to create origination scores? What about consumer protections to privacy? Do investors have the ability to process the data? Will data access increase investor questions and thus investors relations costs?

  18. You can control your data Array of tools to limit distribution and use as appropriate • Customized content for different verticals: Investors, Rating Agencies, Prospective Lender Customers… • Complete control over nature, frequency, fields of data released • Contractual: NDAs, Limitations on Use, Matching to External Limitations or Prohibition … • Technical: Download/Export Limitations, Logging, Field/Pool Level Filters

  19. What is in it for issuers and lenders? • More buyers for your bonds and at better spreads • Increase the groups competitiveness in the new private loan market – Every one is data poor in something • Improve servicing performance • Reports and information to support with the policy process and discussions with DOE, Congress and State legislatures • Simplify your IR function by referring investors to MeasureOne platform • Be prepared for Reg AB II

  20. Data Transparency is ComingEmbrace it for Competitive AdvantageDan FeshbachDan@measureone.com415-971-1977

More Related