session 61

Session 61

Financial Partners’

Journey Through

NSLDS

Pam Eliadis

and

Valerie Sherrer

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

4

Student Eligibility

1

5

Student Eligibility

• Loan level data that affect Student Eligibility:

– Loan Statuses

– Originations

– Disbursements

– Cancellations/Refunds

– Outstanding Balances

6

Student Eligibility

Schools see eligibility information:

1. ISIR

2. NSLDS FAP Website

7

Student Eligibility

Loan Status

• Default Status is based on Lender Claim Payment

• Rehabilitated Loans should be reported timely

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

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

Student Eligibility

Originations

• Report Originations as they happen

• Helps Schools see pending aid for Transfer Students

11

Student Eligibility

Cancellations/Refunds

Factor in determining the Net Loan Amount for aggregate calculation

12

Student Eligibility

• Disbursements

Factor in aggregate calculation

13

Student Eligibility

• Outstanding Principal and Interest Balance

Amounts

OPB factored in aggregate calculations, OIB and Other Fees are not

14

2

Enrollment Reporting

15


• 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


• 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

Enrollment Reporting Flow

18


When student drops below half-time attendance: Loan Status: IA to IG

19

Enrollment ReportingWhen student re-enters school:

Loan Status: RP to DA

20


• 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


• Possible Effects of Non-Reported

Enrollment Changes

– Loan converted to repayment early

– Loan entering repayment delayed

– Borrower enters grace period without

knowledge

22


Data Quality Monitoring

2006 IA/ID DA

Jan 260,389 65,378

Feb 282,469 82,381

Mar 294,921 91,004

Apr 290,532 87,451

May 297,569 87,417

Jun 281,140 73,435

Jul 265,881 64,955

Aug 261,977 60,826

Inconsistencies between enrollment

and loan statuses

23


• 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

3NSLDS Data

Quality

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

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

NSLDS Data QualityAccurate Contact Information

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

NSLDS Data Quality – Accurate Information

• Resolve reporting errors

• Close unconsummated loans

• Report loan transfers

30


• Resolve reporting errors:

– Actively work reporting errors

– Analyze loan errors holistically

– Resolve for next submission

31

NSLDS Data Quality –Accurate Information

• Non-Closure of Unconsummated Loans:

– May cause GAs to “assume” the loan status

– Creates conflicting information

32

NSLDS Data QualityAccurate Information

Unconsummated Loan Aging

Assumed by the GA

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

NSLDS Data QualityAccurate Information

Lender Held Loans OPB Update in Last 60 Days

0

20

40

60

80

100

Jan Feb Mar Apr May Jun Jul Aug

Month

Per

cen

tag

e (%

)

Average

Lowest

35


Number of Identifier Conflicts by Month

Jan 2006 12,708

Feb

2006 12,691

Mar

2006 12,714

Apr 2006 12,623

May

2006 12,464

Jun 2006 12,601

Jul 2006 12,835

Aug

2006 13,208

36

4

Cohort Default Rates

37


• Recognize what data reported to NSLDS impacts

the Cohort Default Rate (CDR)

– Formula

– Fields

– Rates

– Frequency

– Adjustments

38


Borrowers who entered repayment in FY04 and

defaulted in FY04 & 05

divided by

Borrowers who entered repayment in FY04

39


• 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


• Two Lender Calculations

– Originating Lender Rate

– Current Holder Rate

• One GA Calculation

41


• 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

Cohort Default RatesCDR on the Web

43

Cohort Default RatesCDR on the Web

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 correctionsCDR Guide for GAs and Lenders: http://www.ifap.ed.gov/drmaterials/FY04Cohortguide.html

45

5

NSLDS Security

46

NSLDS Security

• Define NSLDS Security rules and user

responsibilities

– DCL Gen 05-06

– Audit Reports

– Data Mining

– User IDs

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

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

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

NSLDS Security

• User ID’s

– Will be disabled after 12 months of inactivity

– Cannot be shared with colleagues

– Obtain through FSAwebenroll.ed.gov

51

6

NSLDS Re-engineering

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

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


• 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


• Goals for Re-Engineering

• Improve Data Usefulness:

– Data Timeliness

– Data Quality

– Program Monitoring and Oversight

56


• 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


• Students, Parents, and Schools Benefits:

– Timely information for making eligibility

decisions

– Enhanced data integrity

– Program Information Parity

58


• 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


• Next Steps:

– Collaboration with community stakeholders

– Focus Groups being held in conjunction with

both Federal Student Aid conferences

– Definition of requirements

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: [email protected]

[email protected]

session 61

Documents