Private Loan Rehabilitation Programs Doug St. Peters – Sallie Mae Tom Glanfield – Boston Portfolio Advisors Larry Chiavaro – First Associates Loan Servicing, LLC
Feb 25, 2016
Private Loan Rehabilitation Programs
Doug St. Peters – Sallie MaeTom Glanfield – Boston
Portfolio AdvisorsLarry Chiavaro – First
Associates Loan Servicing, LLC
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
2
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
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
3
How a typical family pays for college
Student Borrowing; 18%
Parent Borrowing; 9%
Parent Income & Savings; 28%
Grants & scholarships; 29%
Relatives/friends; 4%
Student income & savings; 12%
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
4
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
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
5
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
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
6
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
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
7
Private LoansDefault profile Top 5 Reasons
• Overextended 44%• Unemployed 29%• Under employed 10%• Medical 7%• Unaware 4%
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
8
Private Loans Default Profile
• 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
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
9
Private loansDefault 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
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
10
Private loansDefault 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
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
11
Private loans future• 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
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
12
A Successful Rehabilitation Story
• The Problem• Analysis and Approach• Servicing• Overall Solution
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
13
The Problem is Multifaceted1. 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.
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
14
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.
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
15
First Associates Servicing
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
16
Rehabilitation Results Prior to BPA Strategy Implementation
•Sporadic Payments
•Inconsistent Cash Flow
•Lower Overall Loan Value
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
17
Successful Rehabilitation Program Results
•Payment Continuity
•Increased Overall Cash flow
•Higher Loan Values
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
18
Overall Solution and ResultsResult: 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
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
19
Co- Signers- Loan Rehabilitation
Sep-11 Oct-11 Nov-11 Dec-11 Jan-12 Feb-12 Mar-12
ACHSettlements
OtherRehabilitatedLoans
Number ofLoans
Navigating the Sea of Change 2012 NCHER Knowledge Symposium
20
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
• Send out “Welcome Letter” package to co-borrowers
• Text message campaigns to co-borrowers and borrowers
• Voice alerts to co-borrowers and borrowers
• Explanation of outstanding default
• Set up recurring ACH• Be Nice!
Grace Current Delinquent(1-180 days) 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
Door Knocks
• “Knock n Talk”• Field Investigation
• “Knock n Talk”• Field Investigation
Legal Action
• As requested
Skip Tracing
• 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
Ongoing • Cloud Monitoring for utilities, purchases, income, credit changes
• Cloud Monitoring for utilities, purchases, income, credit changes
• Cloud Monitoring for utilities, purchases, income, credit changes
Technologies to Reduce Student Loan Defaults
Navigating the Sea of Change 2012
NCHER Knowledge Symposium
Reducing Defaults and Increasing Recoveriesfor Student Loans
Enhanced Portfolio Performance Program (“EP3”)
Developed and Managed byBoston Portfolio Advisors
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
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
23
Program has Two Main Components
24
Gain Model Linkages Sources of Data
Originator/ School
• Demographics• Field of study• % Completion/
GPAServicer • Payment history
• Contact historyAgency • Payment history
• Type/ number of calls
• Settlement strategy and results
Borrower
• Credit data• Income/
EmploymentLoan • Balance size
• Vintage School Profile
• Public/ Private• Proprietary
Gain Model
Tactical Execution
Focus
• Borrower Prioritization
• High Value Segments
Effort Level
• Frequency of Calls/ letters
• Call type• Contact rate• Settlement
parameters• Texting/ social
media utilization
Loan Value
• Liquidation curves• NPV of account
Data Collection From multiple sources
________________________Gain Model analysis and scoring Creates Segmentation and Prioritization of borrowers for targeted contact strategy based on predictive analytics
________________________Program Management Servicing and collection tactics driven at borrower level based on Priority Score
________________________Results monitored, scoring model updatedAccount level tactics revised for optimal results and actionable information provided to all parties
Servicers
Collection
Agencies
School
Servicers
Collection
Agencies
School
PROGRAM MANAGEMENT
Loan Info
Borrower Info
Historical Performance/ Tactics
GAIN MODEL
Feedback Loop
25
Data Flows
Servicing Phase ImpactSegmenting and Prioritizing borrowers from origination through all repayment phases leads to lower cumulative defaults (sample results illustrated below)
26
12.0%
23.0%
28.0%31.0%
33.0%35.0%
37.0%39.0% 39.5% 40.0%
9.0%
17.3%21.0%
23.3% 24.8% 26.3% 27.8% 29.3% 29.6% 30.0%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
1 2 3 4 5 6 7 8 9 10
Cum
ulati
ve Lo
ss F
orec
ast
Years Since Entering Repayment
Current Default Forecast
Gain Model Default Forecast
Potential Savings
27
Default Phase Collection Tactics Increase Recoveries
Gain Model Batches
Non Gain Model Batches
0.00%
0.20%
0.40%
0.60%
0.80%
1.00%
1.20%
1.40%
1 2 3 4 5 6 7 8 9 10+
Cumulative Recovery Rate by Batch
52% Improvement
Segmenting and Prioritizing borrowers for more effective collection strategies leads to higher recoveries in Collections (actual results below)
Reallocate Effort based on Scoring and Prioritization
28
• 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
0
1
2
3
4
5
6
1 2 3 4 5 6 7 8
Cont
act E
ffort
Inde
x
Segment
Historical AttemptsNew Attempts - High PriorityNew Attempts - Medium PriorityNew Attempts - Low/No Priority
Sample Collection Results Comparison
29
Historical Performance - Produces 5.8% Recovery RateSegment 1 2 3 4 5 6 7 8 TotalHistorical Phone Attempts 295,000 417,000 208,000 278,000 431,000 275,000 317,000 104,000 2,325,000Phone Attempts (% of Historical) 100% 100% 100% 100% 100% 100% 100% 100% 100%Contact Rate 3.2% 2.7% 2.8% 2.3% 1.6% 1.5% 2.5% 3.4% 2.4%Close Rate 18.7% 14.6% 9.8% 8.0% 4.9% 2.6% 18.6% 8.3% 8.9%Realization Rate 80.1% 82.2% 76.0% 79.6% 76.4% 82.7% 83.5% 81.2% 79.4%
Historical Collection Amount Per Phone Attempt ($) $5.61 $3.60 $7.17 $4.54 $0.53 $0.56 $2.87 $7.07 $3.41
Historical Collections $1,656,000 $1,499,000 $1,491,000 $1,261,000 $229,000 $153,000 $908,000 $735,000 $7,932,000% of Total Collections 20.9% 18.9% 18.8% 15.9% 2.9% 1.9% 11.4% 9.3% 100.0%
Historical Placements $10,614,000 $15,389,000 $21,645,000 $28,137,000 $16,999,000 $27,860,000 $7,060,000 $9,053,000 $136,757,000Historical Collection Rate 15.6% 9.7% 6.9% 4.5% 1.3% 0.5% 12.9% 8.1% 5.8%
Improvement by Redistributing Phone Attempts - Increases Recovery Rate by 32%Segment 1 2 3 4 5 6 7 8 TotalPhone Attempts - Redistributed 443,000 521,000 364,000 348,000 154,000 101,000 238,000 156,000 2,325,000Phone Attempts (% of Historical) 150% 125% 175% 125% 36% 37% 75% 150% 100%Contact Rate - No Change 2.4%Close Rate - No Change 8.9%Realization Rate - No Change 79.4%
Projected Collection Amount Per Phone Attempt ($) $5.61 $3.60 $7.17 $4.54 $0.53 $0.56 $2.87 $7.07
Projected Collections $2,487,000 $1,873,000 $2,609,000 $1,579,000 $82,000 $56,000 $682,000 $1,103,000 $10,471,000% of Total Collections 23.8% 17.9% 24.9% 15.1% 0.8% 0.5% 6.5% 10.5% 100.0%
Collection Rate With Redistribution of Phone Attempts 23.4% 12.2% 12.1% 5.6% 0.5% 0.2% 9.7% 12.2% 7.7%
Gain ($) $831,000 $374,000 $1,118,000 $318,000 ($147,000) ($97,000) ($226,000) $368,000 $2,539,000Gain (%) 50% 25% 75% 25% -64% -63% -25% 50% 32%
SAME AS HISTORICAL
Sample Collection Results Comparison
30
Improvement by Redistributing Attempts, and Increasing Contact and Close RatesImprovement Assumptions(% Change) 1 2 3 4 5 6 7 8# Phone Attempts 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%Contact Rate 20.0% 15.0% 10.0% 5.0% 0.0% 0.0% 0.0% 0.0%Close Rate 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% 20.0% 20.0%Realization Rate 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
Segment 1 2 3 4 5 6 7 8 Total# Phone Attempts 443,000 521,000 364,000 348,000 154,000 101,000 238,000 156,000 2,325,000Call Attempts - Redistributed 150% 125% 175% 125% 36% 37% 75% 150% 100%Contact Rate - Improved 3.9% 3.1% 3.1% 2.4% 1.6% 1.5% 2.5% 3.4%Close Rate - Improved 22.5% 17.6% 11.7% 9.6% 5.9% 3.1% 22.3% 9.9%Realization Rate - No Change 80.1% 82.2% 76.0% 79.6% 76.4% 82.7% 83.5% 81.2%
Projected Collection Amount Per Phone Attempt ($) $8.08 $4.96 $9.46 $5.72 $0.64 $0.67 $3.44 $8.49
Projected Collections $3,581,000 $2,585,000 $3,443,000 $1,989,000 $98,000 $68,000 $818,000 $1,324,000 $13,906,000% of Total Collections 25.8% 18.6% 24.8% 14.3% 0.7% 0.5% 5.9% 9.5% 100.0%Projected Collection Rate 33.7% 16.8% 15.9% 7.1% 0.6% 0.2% 11.6% 14.6% 10.2%
Gain ($) $1,925,000 $1,086,000 $1,952,000 $728,000 ($131,000) ($85,000) ($90,000) $589,000 $5,974,000Gain (%) 116% 72% 131% 58% -57% -56% -10% 80% 75%
Gain Model Results: Number of Future Payers Cumulative Gain
Previous Results: Using Limited Segmentation Attributes
Improved Results: Analytics Using Additional Attributes
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)
Page 32
Incremental Calls
AttemptedContact
Rate
Cumulative Contacts
Made
Cumulative Contact Expense
Payment Rate
Cumulative Accounts
Cumulative Recoveries Profit/Loss
Total 1,000,000 3.23% 32,301 $705,000 18.74% 6,054 $5,614,246 $4,909,246
Decile
Incremental Calls
AttemptedContact
Rate
Incremental Contacts
Made
Incremental Contact Expense
Payment Rate
Incremental Accounts
Incremental Recoveries
Incremental Profit/Loss
Cumulative Profit/Loss
1 100,000 6.50% 6,500 $87,500 28.5% 1,853 $1,717,925 $1,630,425 $1,630,4252 100,000 6.00% 6,000 $87,500 26.0% 1,560 $1,446,674 $1,359,174 $2,989,5993 100,000 5.00% 5,000 $87,500 24.0% 1,200 $1,112,826 $1,025,326 $4,014,9254 100,000 4.00% 4,000 $87,500 22.0% 880 $816,072 $728,572 $4,743,4975 100,000 3.25% 3,250 $87,500 21.0% 683 $632,920 $545,420 $5,288,9176 100,000 2.75% 2,750 $87,500 16.0% 440 $408,036 $320,536 $5,609,4537 100,000 2.00% 2,000 $87,500 15.0% 300 $278,206 $190,706 $5,800,1608 100,000 1.25% 1,250 $87,500 14.0% 175 $162,287 $74,787 $5,874,9479 100,000 1.00% 1,000 $87,500 12.0% 120 $111,283 $23,783 $5,898,72910 100,000 0.50% 500 $87,500 8.9% 45 $41,267 ($46,233) $5,852,497
Total 1,000,000 32,250 $875,000 7,255 $6,727,497 $5,852,497
Results Without Segmentation and Prioritization
Results With Segmentation and Prioritization
Segmentation and Prioritization Improves Profitability
High Response Segment: Comparison of results with and without Segmentation and Prioritization
Page 33
Segmentation and Prioritization Improves Profitability
Low Response Segment: Comparison of results with and without Segmentation and Prioritization
Incremental Calls
AttemptedContact
Rate
Cumulative Contacts
Made
Cumulative Contact Expense
Payment Rate
Cumulative Accounts
Cumulative Recoveries Profit/Loss
Total 1,000,000 1.59% 15,872 $705,000 4.90% 777 $532,087 ($172,913)
Decile
Incremental Calls
AttemptedContact
Rate
Incremental Contacts
Made
Incremental Contact Expense
Payment Rate
Incremental Accounts
Incremental Recoveries
Incremental Profit/Loss
Cumulative Profit/Loss
1 100,000 3.75% 3,750 $55,000 14.0% 525 $359,460 $304,460 $304,4602 100,000 2.75% 2,750 $55,000 8.9% 245 $167,577 $112,577 $417,0363 100,000 2.50% 2,500 $55,000 8.9% 223 $152,342 $97,342 $514,3794 100,000 1.75% 1,750 $55,000 6.0% 105 $71,892 $16,892 $531,2715 100,000 1.50% 1,500 $55,000 3.6% 54 $36,973 ($18,027) $513,2446 100,000 1.00% 1,000 $55,000 2.8% 28 $19,171 ($35,829) $477,4157 100,000 0.95% 950 $55,000 1.8% 17 $11,708 ($43,292) $434,1238 100,000 0.75% 750 $55,000 1.5% 11 $7,703 ($47,297) $386,8269 100,000 0.65% 650 $55,000 1.0% 7 $4,450 ($50,550) $336,27610 100,000 0.25% 250 $55,000 0.5% 1 $856 ($54,144) $282,132
Total 1,000,000 15,850 $550,000 1,215 $832,132 $282,132
Results Without Segmentation and Prioritization
Results With Segmentation and Prioritization
34
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)
BPA Priority Score # Borrowers
Initial Balance
Amount Collected
# Call Attempts # Contacts # Letters
Collection Time (minutes)
A 34,180 $117,061,342 $11,895,790 1,139,990 80,180 218,160 1,534,771B 66,460 $155,305,797 $1,610,337 1,573,420 32,680 282,560 1,177,039C 63,940 $170,739,747 $521,801 2,079,380 13,480 258,250 843,128
TOTAL 164,580 $443,106,886 $14,027,928 4,792,790 126,340 758,970 3,554,938
BPA Priority Score
% of Borrowers
% of Initial Bal
% of Collected
% of Call Effort
% of Contacts
% of Letters % Time Worked
A 20.8% 26.4% 84.8% 23.8% 63.46% 28.7% 43.2%B 40.4% 35.0% 11.5% 32.8% 25.87% 37.2% 33.1%C 38.9% 38.5% 3.7% 43.4% 10.67% 34.0% 23.7%
TOTAL 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
BPA Priority Score
Recovery Rate
Collection Factor
Effort Factor
A 10.2% 308% 108%B 1.0% -71.6% -18.0%C 0.3% -90.4% -39.0%
TOTAL 3.2%
35
Champion/ Challenger Performance Heat Map
Balance Range Max FICO Agency A Agency B Agency C Agency D Agency E Agency F Agency G Agency H TOTAL Factor
$0-$4,999 Unknown 10.42% 89.58% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.0% 8.52 $0-$4,999 Below 500 21.66% 78.34% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.0% 1.67 $0-$4,999 500-549 71.78% 0.00% 3.12% 7.85% 16.48% 0.78% 0.00% 0.00% 100.0% 2.99 $0-$4,999 550-599 38.61% 1.11% 7.16% 21.22% 0.00% 28.08% 3.81% 0.00% 100.0% 3.58 $0-$4,999 600-649 15.76% 0.00% 46.57% 18.02% 9.64% 6.12% 3.89% 0.00% 100.0% 3.36 $0-$4,999 650-699 31.91% 22.83% 2.47% 20.04% 15.47% 0.00% 7.28% 0.00% 100.0% 9.27 $0-$4,999 700-749 28.04% 4.20% 46.84% 12.53% 0.00% 0.00% 8.39% 0.00% 100.0% 8.59 $5,000-$09,999 Unknown 86.18% 0.00% 0.00% 13.82% 0.00% 0.00% 0.00% 0.00% 100.0% (0.65) $5,000-$09,999 Below 500 96.71% 0.00% 3.29% 0.00% 0.00% 0.00% 0.00% 0.00% 100.0% (0.02) $5,000-$09,999 500-549 62.97% 9.16% 17.42% 0.00% 0.00% 10.46% 0.00% 0.00% 100.0% (0.67) $5,000-$09,999 550-599 46.13% 5.31% 18.92% 24.34% 1.08% 1.92% 2.31% 0.00% 100.0% 0.69 $5,000-$09,999 600-649 53.46% 8.44% 22.56% 6.90% 0.00% 7.42% 1.22% 0.00% 100.0% 1.10 $5,000-$09,999 650-699 15.35% 35.82% 16.78% 15.84% 0.00% 7.14% 6.57% 2.50% 100.0% 0.33 $5,000-$09,999 700-749 0.36% 2.95% 33.21% 30.43% 0.00% 26.66% 6.38% 0.00% 100.0% 8.95 $10,000-$14,999 Unknown 4.41% 4.41% 0.00% 88.17% 0.00% 3.01% 0.00% 0.00% 100.0% 3.78 $10,000-$14,999 Below 500 21.35% 14.20% 4.73% 18.94% 12.36% 28.41% 0.00% 0.00% 100.0% (0.84) $10,000-$14,999 500-549 39.96% 1.67% 22.43% 26.75% 0.00% 2.51% 6.69% 0.00% 100.0% (0.71) $10,000-$14,999 550-599 11.17% 4.88% 55.88% 15.50% 2.47% 5.93% 4.18% 0.00% 100.0% 0.48 $10,000-$14,999 600-649 13.03% 30.59% 8.73% 0.00% 3.52% 43.74% 0.40% 0.00% 100.0% 0.43 $10,000-$14,999 650-699 15.90% 46.22% 4.06% 26.20% 0.00% 3.56% 1.63% 2.43% 100.0% 0.39 $10,000-$14,999 700-749 24.19% 65.06% 0.00% 0.00% 0.00% 0.00% 0.00% 10.75% 100.0% (0.36) $15,000-$19,999 Unknown 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.0% (0.90) $15,000-$19,999 Below 500 3.99% 96.01% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.0% (0.05) $15,000-$19,999 500-549 44.38% 0.00% 9.08% 19.19% 13.43% 13.92% 0.00% 0.00% 100.0% (0.54) $15,000-$19,999 550-599 77.91% 2.55% 7.89% 11.07% 0.00% 0.59% 0.00% 0.00% 100.0% 0.09 $15,000-$19,999 600-649 33.92% 32.57% 17.51% 0.00% 0.00% 7.97% 8.03% 0.00% 100.0% (0.54) $15,000-$19,999 650-699 20.85% 64.46% 0.00% 0.00% 0.00% 8.81% 5.87% 0.00% 100.0% (0.53) $15,000-$19,999 700-749 1.22% 6.83% 0.00% 0.00% 89.18% 0.00% 1.82% 0.95% 100.0% 8.63 $20,000-$29,999 Unknown 0.00% 0.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.00% 100.0% (0.92) $20,000-$29,999 Below 500 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.0% (0.98) $20,000-$29,999 500-549 79.93% 20.07% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.0% (0.93) $20,000-$29,999 550-599 26.65% 3.53% 15.87% 27.43% 11.26% 8.41% 6.85% 0.00% 100.0% (0.54) $20,000-$29,999 600-649 9.19% 9.71% 62.86% 9.70% 2.26% 5.67% 0.59% 0.00% 100.0% 0.20 $20,000-$29,999 650-699 25.98% 59.29% 8.00% 0.00% 0.00% -1.07% 7.80% 0.00% 100.0% (0.35) $20,000-$29,999 700-749 11.62% 64.44% 0.00% 18.95% 0.00% 0.00% 4.99% 0.00% 100.0% 0.14 $30,000+ Unknown 0.00% 0.00% 0.00% 100.00% 0.00% 0.00% 0.00% 0.00% 100.0% (0.51) $30,000+ Below 500 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.0% (0.94) $30,000+ 500-549 0.00% 0.00% 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.0% (0.99) $30,000+ 550-599 13.13% 0.00% 3.75% 0.00% 0.00% 83.12% 0.00% 0.00% 100.0% (0.70) $30,000+ 600-649 79.13% 0.00% 0.00% 20.87% 0.00% 0.00% 0.00% 0.00% 100.0% (0.87) $30,000+ 650-699 0.00% 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.0% (0.92) $30,000+ 700-749 0.00% 100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.0% (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• 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
36
37
Information Uses
Finance• Cash flow and funding
requirement projections• NPV valuations by loan
and student
Admissions• Probability of
graduation• Probability of
payment• Co-borrower
alternatives
Private Loan Collections Management• Maximize value of
cash receivables• Loss mitigation tactics• Optimize settlement
offers• Identification of
optimal loans for saleFederal LoanCohort Management• Minimize losses• Forecast default
rates for potential action steps
Student Success Monitoring• Tactical
solutions to improve persistence rates
• Student payment behavior
• Performance by Segment
• Probability of graduation
Gain Model information can be harnessed for other purposes