1. Session 61 Financial Partners’ Journey Through NSLDS Pam Eliadis and Valerie Sherrer

2. 2 Objectives Identify how loan level data affects student eligibility Specify how the flow of enrollment data impacts timely conversion to repayment Examine ways financial partners can improve NSLDS Data Quality Recognize what data reported to NSLDS impacts the Cohort Default Rate Define NSLDS Security rules and user responsibilities Re-engineering NSLDS to Enhance Student Aid History Management

3. 3

4. 4 Student Eligibility 1

5. 5 Loan level data that affect Student Eligibility: –Loan Statuses –Originations –Disbursements –Cancellations/Refunds –Outstanding Balances

6. 6 Student Eligibility Schools see eligibility information: 1.ISIR 2.NSLDS FAP Website

7. 7 Student Eligibility Loan Status Default Status is based on Lender Claim Payment Rehabilitated Loans should be reported timely

8. 8 Student Eligibility - Aggregates Three Major Variables: –Net Loan Amounts (Guaranty minus Cancellations) –Disbursements –Outstanding Principal Balance Aggregate Loan Limits are calculated for each student on NSLDS to assist the FAA in determining student eligibility.

9. 9 Student Eligibility – Loan Status Identification of Consolidation’s Underlying Loans: –Loan Status Code = PN, DN, PC, DP or PF –Loan Status Date within 210 days (before or after) of the Consolidation Loan Date

10. 10 Student Eligibility Originations Report Originations as they happen Helps Schools see pending aid for Transfer Students

11. 11 Student Eligibility Cancellations/Refunds Factor in determining the Net Loan Amount for aggregate calculation

12. 12 Student Eligibility Disbursements Factor in aggregate calculation

13. 13 Student Eligibility Outstanding Principal and Interest Balance Amounts OPB factored in aggregate calculations, OIB and Other Fees are not

14. 14 2 Enrollment Reporting

15. 15 Enrollment Reporting Impacts of Enrollment Reporting on Financial Partners –Enrollment Reporting Flow –Changes to the Loan Status –Impact on the Date Entered Repayment –Effects of Non-Reported Enrollment Changes

16. 16 Enrollment Reporting How do students get on a school’s roster? –Reporting of a loan –School adds them to a roster –Reporting of an ACG or SMART Grant (as of Jan. 2007)

17. 17 Enrollment Reporting Flow

18. 18 Enrollment Reporting When student drops below half-time attendance: Loan Status: IA to IG

19. 19 Enrollment Reporting When student re-enters school: Loan Status: RP to DA

20. 20 Enrollment Reporting Impact on Date Entered Repayment (DER) –Enrollment Effective Date used to drive DER –DER is loan based, not student based –GA Data Provider Instructions Grace = Separation + 6 months DER = Separation + 6 months + 1 day After entering repayment, DER does not change

21. 21 Enrollment Reporting Possible Effects of Non-Reported Enrollment Changes –Loan converted to repayment early –Loan entering repayment delayed –Borrower enters grace period without knowledge

22. 22 Enrollment Reporting Data Quality Monitoring 2006IA/IDDA Jan 260,389 65,378 Feb 282,46982,381 Mar 294,92191,004 Apr 290,53287,451 May 297,56987,417 Jun 281,14073,435 Jul 265,88164,955 Aug261,977 60,826 Inconsistencies between enrollment and loan statuses

23. 23 Enrollment Reporting Effective Enrollment Reporting and usage: –Reduces risk of default –Minimizes technical defaults NSLDS: –Maintains the official enrollment data –Provides GA’s enrollment data weekly –Instructs GA’s to inform Lender/Lender Servicers timely

24. 24 3 NSLDS Data Quality

25. 25 NSLDS Data Quality Examine how Financial Partners can improve NSLDS Data Quality –Timely reporting to GAs by lenders –Accurate Contact information –Accurate information

26. 26 NSLDS Data Quality Benefits of Timely Reporting –Timely reporting of information affecting student eligibility –New data reported quickly for decision making –Effective program management and oversight

27. 27 NSLDS Data Quality Accurate Contact Information

28. 28 NSLDS Data Quality – Accurate Contact Information Contact information displayed on NSLDS web sites Contact Information used for the Interactive Voice Response Unit for 1-800-4FEDAID

29. 29 NSLDS Data Quality – Accurate Information Resolve reporting errors Close unconsummated loans Report loan transfers

30. 30 NSLDS Data Quality – Accurate Information Resolve reporting errors: –Actively work reporting errors –Analyze loan errors holistically –Resolve for next submission

31. 31 NSLDS Data Quality –Accurate Information Non-Closure of Unconsummated Loans: –May cause GAs to “assume” the loan status –Creates conflicting information

32. 32 NSLDS Data Quality Accurate Information Unconsummated Loan Aging Assumed by the GA

33. 33 NSLDS Data Quality GA Data Quality Measures –Review Benchmark reports –Data Integrity Improvement Plans –Reconcile Fee Payment Backup Data –Annual Reconciliation with NSLDS –Research Reasonability Report variances

34. 34 NSLDS Data Quality Accurate Information

35. 35 NSLDS Data Quality – Accurate Information Number of Identifier Conflicts by Month Jan 200612,708 Feb 200612,691 Mar 200612,714 Apr 2006 12,623 May 200612,464 Jun 200612,601 Jul 200612,835 Aug 2006 13,208

36. 36 4 Cohort Default Rates

37. 37 Cohort Default Rates Recognize what data reported to NSLDS impacts the Cohort Default Rate (CDR) –Formula –Fields –Rates –Frequency –Adjustments

38. 38 Cohort Default Rates Borrowers who entered repayment in FY04 and defaulted in FY04 & 05 divided by Borrowers who entered repayment in FY04

39. 39 Cohort Default Rates What NSLDS fields affect the CDR calculation? –Date Entered Repayment (DER) –Loan Type –Date Claim Paid –Claim Reason Code –Loan Status Codes –Student Identifiers

40. 40 Cohort Default Rates Two Lender Calculations –Originating Lender Rate –Current Holder Rate One GA Calculation

41. 41 Cohort Default Rates How often are the CDRs Calculated? –Draft Cohort Default Rate (CDR) Calculate January Publish February –Official Cohort Default Rate (CDR) Calculate August Publish September

42. 42 Cohort Default Rates CDR on the Web

43. 43 Cohort Default Rates CDR on the Web

44. 44 Cohort Default Rates How do Financial Partners request an adjustment to their CDR? –Lenders: Data Correction to GA within 30 days of publication The GA has 15 days to respond –GA: GA has 45 days to submit data corrections CDR Guide for GAs and Lenders: http://www.ifap.ed.gov/drmaterials/FY04Cohortguide.html

45. 45 5 NSLDS Security

46. 46 NSLDS Security Define NSLDS Security rules and user responsibilities –DCL Gen 05-06 –Audit Reports –Data Mining –User IDs

47. 47 NSLDS Security Dear Colleague Letter GEN 05-06 –NSLDS may not be used for marketing purposes –Student/Borrower’s permission is required –Reminds users of Federal Student Aid’s enforcement obligation

48. 48 NSLDS Security Audit Reports –Every student look-up is tracked by User ID –Lender Audit Security Reports Requested by Destination Point Administrator Number of look-ups by user id Past 90 days

49. 49 NSLDS Security No Data Mining Completely Automated Public Turing Test to Tell Computers and Humans Apart (CAPTCHA) tool Monitoring top 20 users and organizations

50. 50 NSLDS Security User ID’s –Will be disabled after 12 months of inactivity –Cannot be shared with colleagues –Obtain through FSAwebenroll.ed.gov

51. 51 6 NSLDS Re-engineering

52. 52 NSLDS Re-Engineering NSLDS Functionality –Monitor aid eligibility through applicant pre- screening, post-screening, and transfer monitoring processes; –Receive student enrollment updates from schools and their servicers, process and store this information in the Operational Data Store (ODS), and then distribute relevant enrollment updates to interested trading partners (i.e. lenders, lender/servicers, guaranty agencies).

53. 53 NSLDS Re-Engineering NSLDS Functionality –Manage the default rate processes including calculation, distribution, and publishing of default rates –Provide aid-level calculation services and provide SAHM operational reports and metrics –Manage receipt of student, aid, and organization data to provide an integrated student view of financial aid history

54. 54 NSLDS Re-engineering Goals for Re-Engineering –Align with Federal Student Aid Data Strategy Efforts Implement FFEL data flow changes to facilitate design and implementation of Information Framework(IF)/ Student Aid History Management (SAHM)

55. 55 NSLDS Re-engineering Goals for Re-Engineering Improve Data Usefulness: –Data Timeliness –Data Quality –Program Monitoring and Oversight

56. 56 NSLDS Re-engineering FFELP Community Benefits: –Data source becomes responsible for reporting –Using current industry data exchange formats and methods (i.e. XML Schemas) –Standardized reporting for all life-cycle stages (i.e CommonLine) –Reduced duplicative reporting among FFEL participants –Interface Consistency

57. 57 NSLDS Re-engineering Students, Parents, and Schools Benefits: –Timely information for making eligibility decisions –Enhanced data integrity –Program Information Parity

58. 58 NSLDS Re-engineering Federal Student Aid Benefits: –Improved Customer Service to all constituents –Facilitates better decision making –Enhanced data integrity –Improved oversight of FFEL Program –Meets Target State Vision for the Enterprise

59. 59 NSLDS Re-engineering Next Steps: –Collaboration with community stakeholders –Focus Groups being held in conjunction with both Federal Student Aid conferences –Definition of requirements

60. 60 Thank you! We appreciate your feedback and comments. We can be reached at: Phone: Valerie Sherrer 202-377-3554 Pam Eliadis at 202-377-3554 Fax:202-275-0913 Email:valerie.sherrer@ed.gov pam.eliadis@ed.gov