Private Loan Rehabilitation Programs

Report
Private Loan Rehabilitation Programs
Doug St. Peters – Sallie Mae
Tom Glanfield – Boston Portfolio Advisors
Larry Chiavaro – First Associates Loan Servicing, LLC
Private Loans Overview
• Total Student loan indebtedness made headlines this year as it
approached $1 trillion
• Source of funds for college
– Awards – financial gov. support – scholarships
– Savings
– Parents/relatives
– Loans
• Government
• Private
2
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How a typical family pays for college
Relatives/friends, 4%
Student income & savings, 12%
Student Borrowing, 18%
Parent Borrowing, 9%
Grants & scholarships, 29%
Parent Income & Savings, 28%
3
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Private student – new loans
• Growth has slowed: +2% last year (SLM)
• SLM New products – SMART Option
– Pay while in school
•
•
•
•
Shorten loan term
Save interest
Increase student connectivity
Borrower can choose and choices result in interest options
• Interest rate - Fixed rate private loans in market, competitive
against non-subsidized government rates
4
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Private student loans
underwriting
• Underwriting guidelines increase quality focus
• Co-borrowers
• 64% of portfolio (+3% vs. prior year)
• 94% of SMART Option
• Loan/School mix changing
– Less for profit schools loans down -2% of the mix last year
5
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Private loan - defaults
• Protected form bankruptcy
• Characteristics require different work effort/strategy
– Average balances are increasing
– More co-borrowers 37% vs. 34% py
– Pre-default more aggressive worked
• Settlement, repayment programs, less use of forbearance, pre-default
pre-litigation talk offs
6
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Private Loans
Default profile Top 5 Reasons
•
•
•
•
•
7
Overextended
Unemployed
Under employed
Medical
Unaware
44%
29%
10%
7%
4%
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Private Loans
Default Profile
•
•
•
•
•
8
46% withdrew from School
40% graduated
59% have a FICO score under 600
9% never used forbearance vs. 21% PY
54% made between 25-60 months of payments
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Private loans
Default collections
• Volume - monthly defaults are dropping - under $100MM
in September
• Larger balances = less settlements
• More co-borrowers
– Work both borrowers
– More skip work
– Co-borrower release programs
9
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Private loans
Default collections
• More collection programs
– Settlement campaign
– Reduced interest pay
• 0% interest
• Report to Credit Bureau – paying as agreed
– Litigation (pre-default and post default)
– Segmentation of inventory
• Contingency fee rate impact
• Competition
• Contests
• Collection agency – Collect it fast, Collect it right
10
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Private loans future
•
•
•
•
•
•
11
Demand
College costs more
Government not raising loan limits
Direct loans adds to national debt
Competitive interest rate vs. other government backed loans
Flexible – ability to provide GAP financing as well as other
supporting products
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A Successful Rehabilitation Story
•
•
•
•
12
The Problem
Analysis and Approach
Servicing
Overall Solution
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The Problem is Multifaceted
1. No Payments – Following the economic crisis, many private student loan
borrowers stopped paying loans altogether or reduced the monthly payments.
2. Loan Share of wallet – Average person has about 15 monthly payments to
make (car, housing, insurance, etc). Student loans have dropped from about
9th in priority of the 15 to almost dead last.
3. Increased transiency – Moved home, to other states, etc., becoming harder to
track.
4. Servicing operations were not prepared for the volume of delinquencies and
defaults. Many similarities to the mortgage business.
5. Increasing % of drops – Some students left the workforce to gain better skills
for their next job. Many left school before finishing and do not believe they
owe money or just do not pay.
13
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Boston Portfolio Analyzed the Situation
Numerous pieces to the problem were analyzed and then modeled into a
comprehensive contact and settlement strategy:
Historical payment performance
Economic conditions and credit migration
Portfolio segmentation by numerous categories
Servicing effectiveness vs. cost of service
Estimate rehab success levels
Based on the above, BPA selected the optimal pool that addressed the
issues. First Associates took over from there.
14
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First Associates Servicing
15
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Rehabilitation Results Prior to BPA Strategy Implementation
•Sporadic Payments
•Inconsistent Cash
Flow
•Lower Overall Loan
Value
16
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Successful Rehabilitation Program Results
•Payment Continuity
•Increased Overall
Cash flow
•Higher Loan Values
17
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Overall Solution and Results
Result: Loan owners have a portfolio of paying borrowers with strong cash flows and long term value.
Boston Portfolio and First Associates teamed for a highly successful outcome:
Excellent monthly cash flow
Long term value for sale
High borrower satisfaction levels
Cost effective
Now expanding the program
18
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Co- Signers- Loan Rehabilitation
Number of
Loans
ACH
Settlements
Other
Rehabilitated
Loans
Sep-11
19
Oct-11
Nov-11
Dec-11
Jan-12
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Feb-12
Mar-12
Activities for “Rehabbed” Loans
• Analyze portfolio to determine
fields captured at origination or
servicing
• Skip Trace using credit bureau data
• Review cohort defaults, % of co’s,
cell #’s, school info, emails
• Develop campaign strategy
• Social media contacts
20
• Send out “Welcome Letter”
package to co-borrowers
• Text message campaigns to coborrowers and borrowers
• Voice alerts to co-borrowers and
borrowers
• Explanation of outstanding default
• Set up recurring ACH
• Be Nice!
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Technologies to Reduce Student Loan Defaults
Grace
Delinquent
(1-180 days)
Current
Default
Physical Mail
•
•
Congratulations
Reminders
•
Statements
•
•
•
•
Statements
Collection Letters with ACH promo
Outreach Letters
Demand Letters
•
•
•
•
Statements
Collection Letters with ACH promo
Outreach Letters
Demand Letters
Email
•
•
Reminders
Educational materials
•
Statements
•
•
Reminders
Educational Materials
•
•
Reminders
Educational Materials
Phone
•
Alerts and Reminders
•
•
•
•
Voice Alerts
Outbound IVR
Predictive Dialing
Preview Calls
•
•
•
•
Voice Alerts
Outbound IVR
Predictive Dialing
Preview Calls
Text
•
Alerts and Reminders
•
Texting campaigns
•
Texting campaigns
•
•
“Knock n Talk”
Field Investigation
•
•
“Knock n Talk”
Field Investigation
•
As requested
Door Knocks
Legal Action
Skip Tracing
Ongoing
•
•
At boarding
Active monitoring
•
•
At boarding
Active monitoring
•
•
•
•
At boarding
Active monitoring
Individual Trace
Social Media Trace
•
•
•
•
At boarding
Active monitoring
Individual Trace
Social Media Trace
•
Cloud Monitoring for utilities, purchases,
income, credit changes
•
Cloud Monitoring for utilities, purchases,
income, credit changes
•
Cloud Monitoring for utilities, purchases,
income, credit changes
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Reducing Defaults and Increasing Recoveries
for Student Loans
Enhanced Portfolio
Performance Program (“EP3”)
Developed and Managed by
Boston Portfolio Advisors
Program has Two Main Components
Program Management
• Allocate placements among multiple agencies to
create a competitive champion/ challenger
program
• Manage all placements, close and returns, status
updates
• Analyze agency performance and direct new
placements to top performers
• Provide agencies with specific settlement levels
and operating tactics at the borrower level
23
Gain Model
Leverage data from various sources
Score borrowers, prioritize and calculate NPV
Forecast probability and amount of repayment
Match accounts to agencies that perform best in a
particular segment
• Focus on the right accounts with the right tactics
in collection cycle
•
•
•
•
Gain Model Linkages
Sources of Data
Originator/
School
• Demographics
• Field of study
• % Completion/ GPA
Servicer
• Payment history
• Contact history
Agency
• Payment history
• Type/ number of calls
• Settlement strategy and results
Borrower
• Credit data
• Income/ Employment
Loan
• Balance size
• Vintage
School Profile
• Public/ Private
• Proprietary
24
Tactical Execution
Focus
• Borrower Prioritization
• High Value Segments
Effort
Level
•
•
•
•
•
Loan
Value
• Liquidation curves
• NPV of account
Gain
Model
Frequency of Calls/ letters
Call type
Contact rate
Settlement parameters
Texting/ social media utilization
Data Flows
Data Collection
From multiple sources
Collection
Agencies
Servicers
________________________
GAIN MODEL
Gain Model analysis and scoring
Creates Segmentation and Prioritization of
borrowers for targeted contact strategy based
on predictive analytics
School
Historical
Performance/ Tactics
Borrower Info
Loan Info
________________________
Servicing and collection tactics driven at
borrower level based on Priority Score
Feedback Loop
Program Management
PROGRAM MANAGEMENT
________________________
Results monitored, scoring model
updated
Account level tactics revised for optimal results
and actionable information provided to all
parties
25
Servicers
Collection
Agencies
School
Servicing Phase Impact
Segmenting and Prioritizing borrowers from origination through all repayment phases leads to
lower cumulative defaults (sample results illustrated below)
Cumulative Loss Forecast
Current Default Forecast
Gain Model Default Forecast
45%
40%
35%
31.0%
35.0%
39.0%
39.5%
40.0%
Potential
Savings
28.0%
30%
23.0%
25%
20%
15%
33.0%
37.0%
12.0%
21.0%
23.3%
24.8%
26.3%
27.8%
29.3%
29.6%
30.0%
8
9
10
17.3%
10%
5%
9.0%
0%
1
2
3
4
5
6
7
Years Since Entering Repayment
26
Default Phase Collection Tactics Increase Recoveries
Segmenting and Prioritizing borrowers for more effective collection strategies leads to higher
recoveries in Collections (actual results below)
Cumulative Recovery Rate by Batch
Gain Model Batches
1.40%
1.20%
52% Improvement
1.00%
0.80%
0.60%
Non Gain Model Batches
0.40%
0.20%
0.00%
1
27
2
3
4
5
6
7
8
9
10+
Reallocate Effort based on Scoring and Prioritization
•
•
•
Traditional Industry Approach (Gray bars) used credit bureau recovery score to target borrowers
Gain Model Approach uses enhanced Segmentation and Prioritization to rank order each borrower based on probability of
payment (Green is highest, Red is lowest)
Improvement using Gain Model Approach can range upwards of 30%-50% higher
Historical Attempts
New Attempts - High Priority
6
New Attempts - Medium Priority
New Attempts - Low/No Priority
Contact Effort Index
5
4
3
2
1
0
1
2
3
4
5
Segment
28
6
7
8
Sample Collection Results Comparison
Historical Performance - Produces 5.8% Recovery Rate
Segment
Historical Phone Attempts
Phone Attempts (% of Historical)
Contact Rate
Close Rate
Realization Rate
Historical Collection Amount Per
Phone Attempt ($)
Historical Collections
% of Total Collections
Historical Placements
Historical Collection Rate
1
295,000
100%
3.2%
18.7%
80.1%
2
417,000
100%
2.7%
14.6%
82.2%
3
208,000
100%
2.8%
9.8%
76.0%
4
278,000
100%
2.3%
8.0%
79.6%
5
431,000
100%
1.6%
4.9%
76.4%
6
275,000
100%
1.5%
2.6%
82.7%
7
317,000
100%
2.5%
18.6%
83.5%
8
104,000
100%
3.4%
8.3%
81.2%
Total
2,325,000
100%
2.4%
8.9%
79.4%
$5.61
$3.60
$7.17
$4.54
$0.53
$0.56
$2.87
$7.07
$3.41
$1,656,000
20.9%
$1,499,000
18.9%
$1,491,000
18.8%
$1,261,000
15.9%
$229,000
2.9%
$153,000
1.9%
$908,000
11.4%
$735,000
9.3%
$7,932,000
100.0%
$10,614,000 $15,389,000 $21,645,000 $28,137,000 $16,999,000 $27,860,000 $7,060,000 $9,053,000 $136,757,000
15.6%
9.7%
6.9%
4.5%
1.3%
0.5%
12.9%
8.1%
5.8%
Improvement by Redistributing Phone Attempts - Increases Recovery Rate by 32%
Segment
Phone Attempts - Redistributed
Phone Attempts (% of Historical)
Contact Rate - No Change
Close Rate - No Change
Realization Rate - No Change
Projected Collection Amount Per
Phone Attempt ($)
Projected Collections
% of Total Collections
Collection Rate With
Redistribution of Phone Attempts
Gain ($)
29
Gain (%)
1
443,000
150%
2
521,000
125%
3
364,000
175%
4
348,000
125%
5
154,000
36%
6
101,000
37%
7
238,000
75%
8
156,000
150%
SAME AS HISTORICAL
Total
2,325,000
100%
2.4%
8.9%
79.4%
$5.61
$3.60
$7.17
$4.54
$0.53
$0.56
$2.87
$7.07
$2,487,000
23.8%
$1,873,000
17.9%
$2,609,000
24.9%
$1,579,000
15.1%
$82,000
0.8%
$56,000
0.5%
$682,000
6.5%
$1,103,000
10.5%
$10,471,000
100.0%
23.4%
12.2%
12.1%
5.6%
0.5%
0.2%
9.7%
12.2%
7.7%
$831,000
50%
$374,000
25%
$1,118,000
75%
$318,000
25%
($147,000)
-64%
($97,000)
-63%
($226,000)
-25%
$368,000
50%
$2,539,000
32%
Sample Collection Results Comparison
Improvement by Redistributing Attempts, and Increasing Contact and Close Rates
Improvement Assumptions
(% Change)
# Phone Attempts
Contact Rate
Close Rate
Realization Rate
1
0.0%
20.0%
20.0%
0.0%
2
0.0%
15.0%
20.0%
0.0%
3
0.0%
10.0%
20.0%
0.0%
4
0.0%
5.0%
20.0%
0.0%
5
0.0%
0.0%
20.0%
0.0%
6
0.0%
0.0%
20.0%
0.0%
7
0.0%
0.0%
20.0%
0.0%
8
0.0%
0.0%
20.0%
0.0%
1
443,000
150%
3.9%
22.5%
80.1%
2
521,000
125%
3.1%
17.6%
82.2%
3
364,000
175%
3.1%
11.7%
76.0%
4
348,000
125%
2.4%
9.6%
79.6%
5
154,000
36%
1.6%
5.9%
76.4%
6
101,000
37%
1.5%
3.1%
82.7%
7
238,000
75%
2.5%
22.3%
83.5%
8
156,000
150%
3.4%
9.9%
81.2%
$8.08
$4.96
$9.46
$5.72
$0.64
$0.67
$3.44
$8.49
Projected Collections
% of Total Collections
Projected Collection Rate
$3,581,000
25.8%
33.7%
$2,585,000
18.6%
16.8%
$3,443,000
24.8%
15.9%
$1,989,000
14.3%
7.1%
$98,000
0.7%
0.6%
$68,000
0.5%
0.2%
$818,000
5.9%
11.6%
$1,324,000
9.5%
14.6%
$13,906,000
100.0%
10.2%
Gain ($)
Gain (%)
$1,925,000
116%
$1,086,000
72%
$1,952,000
131%
$728,000
58%
($131,000)
-57%
($85,000)
-56%
($90,000)
-10%
$589,000
80%
$5,974,000
75%
Segment
# Phone Attempts
Call Attempts - Redistributed
Contact Rate - Improved
Close Rate - Improved
Realization Rate - No Change
Projected Collection Amount Per
Phone Attempt ($)
30
Total
2,325,000
100%
Gain Model Results: Number of Future Payers Cumulative Gain
Advanced Analytics Model with additional attributes identifies 82% of all future payers vs. 57% for the existing attributes (y-axis) when selecting
top 20% of borrowers identified by model (x-axis)
Previous Results: Using Limited Segmentation
Attributes
Improved Results: Analytics Using Additional
Attributes
Segmentation and Prioritization Improves Profitability
High Response Segment: Comparison of results with and without Segmentation and Prioritization
Results Without Segmentation and Prioritization
Total
Incremental
Calls
Attempted
1,000,000
Decile
1
2
3
4
5
6
7
8
9
10
Total
Incremental
Calls
Attempted
100,000
100,000
100,000
100,000
100,000
100,000
100,000
100,000
100,000
100,000
1,000,000
Contact
Rate
3.23%
Cumulative
Contacts
Made
32,301
Cumulative
Contact
Payment Cumulative Cumulative
Expense
Rate
Accounts Recoveries Profit/Loss
$705,000 18.74%
6,054
$5,614,246 $4,909,246
Results With Segmentation and Prioritization
Page 32
Contact
Rate
6.50%
6.00%
5.00%
4.00%
3.25%
2.75%
2.00%
1.25%
1.00%
0.50%
Incremental
Contacts
Made
6,500
6,000
5,000
4,000
3,250
2,750
2,000
1,250
1,000
500
32,250
Incremental
Contact
Payment Incremental Incremental Incremental Cumulative
Expense
Rate
Accounts Recoveries Profit/Loss Profit/Loss
$87,500
28.5%
1,853
$1,717,925 $1,630,425
$1,630,425
$87,500
26.0%
1,560
$1,446,674 $1,359,174
$2,989,599
$87,500
24.0%
1,200
$1,112,826 $1,025,326
$4,014,925
$87,500
22.0%
880
$816,072
$728,572
$4,743,497
$87,500
21.0%
683
$632,920
$545,420
$5,288,917
$87,500
16.0%
440
$408,036
$320,536
$5,609,453
$87,500
15.0%
300
$278,206
$190,706
$5,800,160
$87,500
14.0%
175
$162,287
$74,787
$5,874,947
$87,500
12.0%
120
$111,283
$23,783
$5,898,729
$87,500
8.9%
45
$41,267
($46,233)
$5,852,497
$875,000
7,255
$6,727,497 $5,852,497
Segmentation and Prioritization Improves Profitability
Low Response Segment: Comparison of results with and without Segmentation and Prioritization
Results Without Segmentation and Prioritization
Total
Incremental
Calls
Attempted
1,000,000
Decile
1
2
3
4
5
6
7
8
9
10
Total
Incremental
Calls
Attempted
100,000
100,000
100,000
100,000
100,000
100,000
100,000
100,000
100,000
100,000
1,000,000
Contact
Rate
1.59%
Cumulative Cumulative
Contact
Contacts
Expense
Made
$705,000
15,872
Payment
Rate
4.90%
Cumulative
Accounts
777
Cumulative
Recoveries
$532,087
Profit/Loss
($172,913)
Results With Segmentation and Prioritization
Page 33
Contact
Rate
3.75%
2.75%
2.50%
1.75%
1.50%
1.00%
0.95%
0.75%
0.65%
0.25%
Incremental Incremental
Contact
Contacts
Expense
Made
$55,000
3,750
$55,000
2,750
$55,000
2,500
$55,000
1,750
$55,000
1,500
$55,000
1,000
$55,000
950
$55,000
750
$55,000
650
$55,000
250
$550,000
15,850
Payment
Rate
14.0%
8.9%
8.9%
6.0%
3.6%
2.8%
1.8%
1.5%
1.0%
0.5%
Incremental Incremental Incremental Cumulative
Accounts Recoveries Profit/Loss Profit/Loss
$304,460
$304,460
$359,460
525
$417,036
$112,577
$167,577
245
$514,379
$97,342
$152,342
223
$531,271
$16,892
$71,892
105
$513,244
($18,027)
$36,973
54
$477,415
($35,829)
$19,171
28
$434,123
($43,292)
$11,708
17
$386,826
($47,297)
$7,703
11
$336,276
($50,550)
$4,450
7
$282,132
($54,144)
$856
1
$282,132
$832,132
1,215
Sample Gain Model Effort and Performance Results
Collection Agency effort and performance is tracked by BPA Priority Score to ensure Gain Model
tactics are consistent with BPA recommendations (color coded results at bottom)
34
BPA Priority
Score
# Borrowers
A
34,180
$117,061,342 $11,895,790
B
66,460
$155,305,797 $1,610,337
C
TOTAL
63,940
164,580
$170,739,747 $521,801
$443,106,886 $14,027,928
BPA Priority
Score
% of
Borrowers
% of Initial
Bal
A
20.8%
B
40.4%
C
TOTAL
BPA Priority
Score
A
B
C
TOTAL
Initial
Balance
Amount
Collected
# Call
Attempts
1,139,990
1,573,420
2,079,380
Collection Time
# Contacts # Letters
(minutes)
80,180
218,160
1,534,771
32,680
282,560
1,177,039
4,792,790
13,480
126,340
258,250
758,970
843,128
3,554,938
% of
Collected
% of Call
Effort
% of
Contacts
26.4%
84.8%
11.5%
38.9%
100.0%
38.5%
100.0%
3.7%
100.0%
23.8%
32.8%
43.4%
63.46%
35.0%
Recovery
Rate
10.2%
1.0%
0.3%
3.2%
Collection
Factor
308%
-71.6%
-90.4%
Effort
Factor
108%
-18.0%
-39.0%
100.0%
25.87%
10.67%
100.0%
% of
Letters % Time Worked
28.7%
37.2%
34.0%
100.0%
43.2%
33.1%
23.7%
100.0%
Champion/ Challenger Performance Heat Map
Balance Range
$0-$4,999
$0-$4,999
$0-$4,999
$0-$4,999
$0-$4,999
$0-$4,999
$0-$4,999
$5,000-$09,999
$5,000-$09,999
$5,000-$09,999
$5,000-$09,999
$5,000-$09,999
$5,000-$09,999
$5,000-$09,999
$10,000-$14,999
$10,000-$14,999
$10,000-$14,999
$10,000-$14,999
$10,000-$14,999
$10,000-$14,999
$10,000-$14,999
$15,000-$19,999
$15,000-$19,999
$15,000-$19,999
$15,000-$19,999
$15,000-$19,999
$15,000-$19,999
$15,000-$19,999
$20,000-$29,999
$20,000-$29,999
$20,000-$29,999
$20,000-$29,999
$20,000-$29,999
$20,000-$29,999
$20,000-$29,999
$30,000+
$30,000+
$30,000+
$30,000+
$30,000+ 35
$30,000+
$30,000+
Max FICO Agency A Agency B Agency C Agency D Agency E Agency F Agency G Agency H
Unknown
Below 500
500-549
550-599
600-649
650-699
700-749
Unknown
Below 500
500-549
550-599
600-649
650-699
700-749
Unknown
Below 500
500-549
550-599
600-649
650-699
700-749
Unknown
Below 500
500-549
550-599
600-649
650-699
700-749
Unknown
Below 500
500-549
550-599
600-649
650-699
700-749
Unknown
Below 500
500-549
550-599
600-649
650-699
700-749
10.42%
89.58%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
21.66%
78.34%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
71.78%
38.61%
15.76%
31.91%
0.00%
3.12%
7.85%
16.48%
0.78%
0.00%
0.00%
1.11%
7.16%
21.22%
0.00%
28.08%
3.81%
0.00%
0.00%
46.57%
18.02%
9.64%
6.12%
3.89%
0.00%
22.83%
2.47%
20.04%
15.47%
0.00%
7.28%
0.00%
28.04%
4.20%
46.84%
12.53%
0.00%
0.00%
8.39%
0.00%
86.18%
0.00%
0.00%
13.82%
0.00%
0.00%
0.00%
0.00%
96.71%
0.00%
3.29%
0.00%
0.00%
0.00%
0.00%
0.00%
62.97%
46.13%
53.46%
15.35%
0.36%
9.16%
17.42%
0.00%
0.00%
10.46%
0.00%
0.00%
5.31%
18.92%
24.34%
1.08%
1.92%
2.31%
0.00%
8.44%
22.56%
6.90%
0.00%
7.42%
1.22%
0.00%
35.82%
16.78%
15.84%
0.00%
7.14%
6.57%
2.50%
2.95%
33.21%
30.43%
0.00%
26.66%
6.38%
0.00%
4.41%
4.41%
0.00%
88.17%
0.00%
3.01%
0.00%
0.00%
21.35%
39.96%
11.17%
13.03%
15.90%
24.19%
14.20%
4.73%
18.94%
12.36%
28.41%
0.00%
0.00%
1.67%
22.43%
26.75%
0.00%
2.51%
6.69%
0.00%
4.88%
55.88%
15.50%
2.47%
5.93%
4.18%
0.00%
30.59%
8.73%
0.00%
3.52%
43.74%
0.40%
0.00%
46.22%
4.06%
26.20%
0.00%
3.56%
1.63%
2.43%
65.06%
0.00%
0.00%
0.00%
0.00%
0.00%
10.75%
100.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
3.99%
96.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
44.38%
77.91%
33.92%
20.85%
1.22%
0.00%
9.08%
19.19%
13.43%
13.92%
0.00%
0.00%
2.55%
7.89%
11.07%
0.00%
0.59%
0.00%
0.00%
32.57%
17.51%
0.00%
0.00%
7.97%
8.03%
0.00%
64.46%
0.00%
0.00%
0.00%
8.81%
5.87%
0.00%
6.83%
0.00%
0.00%
89.18%
0.00%
1.82%
0.95%
0.00%
0.00%
0.00%
0.00%
0.00%
100.00%
0.00%
0.00%
100.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
79.93%
26.65%
9.19%
20.07%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
3.53%
15.87%
27.43%
11.26%
8.41%
6.85%
0.00%
9.71%
62.86%
9.70%
2.26%
5.67%
0.59%
0.00%
25.98%
59.29%
8.00%
0.00%
0.00%
-1.07%
7.80%
0.00%
11.62%
0.00%
64.44%
0.00%
18.95%
0.00%
0.00%
4.99%
0.00%
0.00%
0.00%
100.00%
0.00%
0.00%
0.00%
0.00%
100.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
13.13%
79.13%
0.00%
100.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
3.75%
0.00%
0.00%
83.12%
0.00%
0.00%
0.00%
0.00%
20.87%
0.00%
0.00%
0.00%
0.00%
0.00%
100.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
TOTAL
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
Factor
8.52
1.67
2.99
3.58
3.36
9.27
8.59
(0.65)
(0.02)
(0.67)
0.69
1.10
0.33
8.95
3.78
(0.84)
(0.71)
0.48
0.43
0.39
(0.36)
(0.90)
(0.05)
(0.54)
0.09
(0.54)
(0.53)
8.63
(0.92)
(0.98)
(0.93)
(0.54)
0.20
(0.35)
0.14
(0.51)
(0.94)
(0.99)
(0.70)
(0.87)
(0.92)
(0.80)
Improvement In Servicing and Collection Phases
Improvements are Realized in Both Phases of Loan Lifecycle
Pre-Default Servicing Phase
• Segmentation and Prioritization of loans focuses on accounts with higher probabilities of payment
• Special call and letter campaigns targeted at specific borrowers
• Selective forbearance or modification options implemented
Post-Default Collection Phase
•
•
•
•
36
Segmentation and Prioritization of loans focuses on accounts with higher probabilities of payment
Specialized tactics are implemented within each segment to ensure greatest performance
Improved call strategies to increase contact rates and payments
Settlement offers customized to each borrower based on probability of payment, contact rates, close rates,
and various student attributes
Gain Model information can be harnessed for other purposes
Information Uses
Private Loan
Collections Management
Admissions
• Probability of graduation
• Probability of payment
• Co-borrower alternatives
•
•
•
•
Finance
• Cash flow and funding requirement
projections
• NPV valuations by loan and student
Maximize value of cash receivables
Loss mitigation tactics
Optimize settlement offers
Identification of optimal loans for sale
Federal Loan
Cohort Management
• Minimize losses
• Forecast default rates for potential
action steps
37
Student Success Monitoring
• Tactical solutions to
improve persistence rates
• Student payment behavior
• Performance by Segment
• Probability of graduation

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