Vision 2014: Members-in-trouble-collections-strategies-for-credit-unions
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Transcript of Vision 2014: Members-in-trouble-collections-strategies-for-credit-unions
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Members in trouble — collections strategies for credit unions
Bill Butler Experian
Alex Siotos Experian
#vision2014
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Life events happen to the best of us How will your members remember you?
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Balancing act
► What drives decisions today?
Best practices and case studies
► Compliance in action
► Member retention
► Optimize resources and maximize revenue
Question and answer
Agenda
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Balancing act—what
drives decisions
today?
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1) Compliance
Regulations, best practices, and fines
2) Member retention
Which Members to invest in
Importance of credit education
3) Optimizing resources and revenue
Segmenting and prioritizing accounts to improve efficiency
Eliminate wrong party contacts and acquire valuable information for quick actionable opportunities
The new balance beam – collection, retention… …and “compliance”
Refining your focus:
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Best practices:
Compliance in action
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Compliance Where does it fit into collections?
Evaluate Prioritize Locate Review Monitor
Member life cycle thru collections
Compliance
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Servicemembers Civil Relief Act (SCRA)
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Telephone Consumer Protection Act (TCPA)
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Account suppression or filtering for special handling:
Compliance is needed for all accounts
Portfolios to be screened monthly
Address SCRA, TCPA, FDCPA, and more
Types of searches: Department of Defense active duty military, bankruptcies, deceased, fraud address indicator, cell phone identification and verification
How do I protect my credit union?
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Dynamic nature of data:
Individuals move ~12 times per lifespan (average)
About 42M Americans (14%) move each year
There are over 4M births, 2M deaths, 2M marriages, and 1M divorces
Socials inexact due to shared SSN, fraud and key entry errors not caught by algorithms
Over 5% use “Jr.” and “Sr.”
40%+ consumers now use cell phone as their primary phone
► Age groups do vary
Continued compliance
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Contact strategies
Cell phone
► Identify the phone numbers in your database that are cell “vs.” residential land line or other types
● Manually dial cells
● Ask for permission to continue to call cell
● Document the members response
How do I protect my credit union?
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Contact strategies
Wrong party calling
► Consider phone cutoff score to increase confidence and performance
► Once you have verified-eliminate it quickly from your calling campaign
● Protect yourself from lawsuits
Right party calling
► Determine the “right” number of calls during what time period
How do I protect my credit union?
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50K active accounts
Nationwide coverage
Goals: Verify good address / phone data, standardize data, separate landline from cells for compliance, and append new information
Results:
Data hygiene example:
Client case study results Contact solutions
Phone verification = 62% / address verification = 70%
Hit rate = 79% with new information
► 78% with one or more new phones
► 12% new addresses
Phones: 53% landline / 47% cells and non-published
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Best practices:
Member retention
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Strengthen member relations through consumer credit management
Enhance your ability to drive member satisfaction
► Meet the needs of credit challenged members
► Create a positive experience for members that don’t understand how credit works
► Put customers on the path to achieving their financial goals
Member retention Customer relations are constantly changing
An informed and educated consumer who has the tools to better
manage their financial health is a great long term member
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Member education
Explanation and copy of personal credit report
Review of each section within the credit report
Discuss different types of inquiries
Discuss potentially negative and positive items
Potentially fraudulent accounts and attempts
Credit report basics
Personal VantageScore®
Explanation and review of score factors
How do creditors utilize scoring models?
Examples of actions that may improve my VantageScore®
Benchmark scores for the nation, my state and region
Credit score
Tips and information for maintaining a healthy credit profile
Data management tips
Links to online resources for credit management and life events information
Value add services
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Educated consumers are reacting to the education they have received and see shorter timelines to reach positive improvements
Member education Analysis results
Action Educated
group Control group
Average VantageScore® 3.0 +14 pts +/- 0 pts
Number of credit inquiries -9% 0%
External collection trades -21% +1%
Percent of trades ever delinquent in last 12 months - 7% 0%
Trades voluntarily closed (3 months after course) +10% -8%
Number of open revolving bankcard trades >75%
utilization (3 months after course) -13% -4%
Data shown is 12 months post observation, unless otherwise noted
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Best practices:
Optimize resources
and maximize revenue
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Scoring
► Recovery – highest ability to pay versus least ability to pay
► Resource management
Additional segmentation with attributes
Event based notification
► Trigger events vs. real-time or batch processing to reduce effort and improve collections
Optimize resources and maximize revenue Best practices throughout the life cycle
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6-month performance window
Performance definition:
► Good – any payment over the performance window
► Bad – no payment over the performance window
Average liquidation rate: 2.1%
Total records: 62,097
Type of debt: Auto
Placement status: fresh, first, second, third, quad, other
Average balance ~ $8,021
Scoring in action Auto portfolio analysis
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Auto debt type validation Cumulative $ recovered
% of total accounts worked
% o
f Tota
l $ c
olle
cte
d
0%
20%
40%
60%
80%
100%
PriorityScore Incidence
PriorityScore Dollar
50/50 Chance Odds
Two times the performance
without a score
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6-9 month performance on placements
Performance definition
► Good – any payment over the performance window
► Bad – no payment over the performance window
Average liquidation rate: 1.3%
Total records: 1,493,111
Type of debt: credit card
Placement status: fresh, first, second, third, quad, other
Average balance ~ $3,191
Scoring in action Credit card portfolio analysis
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Credit card debt type validation Cumulative $ recovered
% of total accounts worked
% o
f to
tal $
colle
cte
d
0%
20%
40%
60%
80%
100%
PriorityScore Incidence
PriorityScore Dollar
50/50 Chance Odds
Collected ~70% vs. ~30% with the
same effort
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By overlaying additional attributes, Experian has seen appreciable lift over and above the use of a score alone
Further separation of recovered and non-recovered accounts
Customization without the added time and expense of a custom model
The attributes and thresholds applied will vary widely depending on dollar amounts, placement level, type of account being worked, etc.
Segmentation
Attributes with thresholds or matrixed score
Score only splits
Total population
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Segmentation lift over score only
17% Lift
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Top-20 premier attributes
Variable Rank
Percentage of trades ever 90 or more days delinquent or derogatory 1
Total number of mortgage type trades presently 90-180 days delinquent reported in the last 6 months 2
Total number of mortgage type trades presently 60 days delinquent reported in the last 6 months 3
Total number of mortgage type trades presently 30 days delinquent reported in the last 6 months 4
Total number of unsatisfied charge-off trades 5
Total number of trades ever 90 or more days delinquent or derogatory in the last 24 months, including external collections 6
Total number of external collections with a balance > $250 7
Total number of trades presently satisfactory that were ever 30 or more days delinquent or derogatory, including external
collections 8
Total balance on open revolving trades reported in the last 6 months 9
Number of months since the most recent external collection 10
Total number of trades ever 60 or more days delinquent or derogatory in the last 24 months, including external collections 11
Total available credit amount on open revolving bankcard trades reported in the last 6 months 12
Total balance on open first mortgage trades reported in the last 6 months 13
Total credit amount on open first mortgage trades reported in the last 6 months 14
Overall balance to credit amount ratio on open revolving trades reported in the last 6 months 15
Worst present status on a trade reported in the last 6 months, including external collections 16
Worst ever status on a trade in the first 12 months of open date 17
Total available credit amount on open revolving trades reported in the last 6 months 18
Total number of ever derogatory trades, external collections, or public records 19
Worst present status on a revolving trade reported in the last 6 months 20
Based on previous client validations, not a guarantee of future performance.
Results can change as applied to different portfolios and/or as additional client validations are performed and added to the overall results shown here.
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Event-based opportunities
No ability to pay
Diminishing ability to pay Full capacity to pay
A debtor’s cycle of delinquency
Debtor
Overextended
Health issues
Job loss Bankruptcy Employment
Paying off
debts
Shopping for
credit
New
credit line
Be notified of these events and then determine the right time to collect
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Using collection triggers in combination with a scorecard/attribute strategy
is the most effective way to collect payments
Triggers in action Bankcard portfolio analysis
Lift : 55%
All collection triggers
Avg payment: $56
% of accounts: 13.2%
3.4%
More payments Less payments
Lift: 175%
Best collection triggers
Avg payment: $94
% of accounts: 3.1%
6.0%
Base Population
Lift : -8%
No collection trigger
Avg payment: $34
% of accounts: 86.8%
2.2%
Liquidation rate
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Variable Rank
Performance
% of Trigger
Population #
Liquidation $
% Lift
Average
Payment $
% Lift
Recreational Merchandise Inquiry 1 4672% 1099% 0.0%
Paid was 150 2 1402% 745% 0.1%
Closed Zero Bal was 120 3 2610% 730% 0.0%
Paid was 120 4 602% 722% 0.1%
Closed Zero Bal was 150 5 1029% 639% 0.0%
Settled Dispute 6 490% 400% 5.2%
Paid Collection 7 450% 333% 2.0%
Auto Lease Inquiry 8 860% 327% 0.0%
Credit Available Home Equity Loan 9 123% 304% 0.1%
Closed Zero Bal was 90 10 214% 272% 0.0%
Paid was 90 11 254% 272% 0.2%
Credit Available Revolving Bankcard 12 105% 241% 3.3%
Home Equity Inquiry 13 206% 241% 0.3%
Credit Available Bankcard 14 65% 226% 0.3%
Paid Charge-off 15 349% 196% 1.6%
Current 60 was 150-180 16 118% 190% 0.0%
Business Loan Inquiry 17 18% 185% 0.1%
Mortgage Inquiry 18 160% 184% 5.9%
Current was 150 19 324% 183% 0.7%
Paid was 180 20 269% 179% 0.1%
Paid Recreational Merchandise 21 79% 160% 0.0%
Paid Auto Loan 22 106% 150% 2.4%
Credit Available Flexible Spending 23 19% 123% 0.0%
Top event based notification performance chart
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Call to action
Setup standard compliance processes to reduce regulatory risk
Strengthen business practices around improving contact strategies
Score your accounts based on greater ability to pay
Additional segmentation by credit attributes for greater separation
Event-based notification
► Be the first to know when a member is curing other debt
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Q&A
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For additional information, please contact:
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in the Daily Roundup:
www.experian.com/vision/blog
@ExperianVision | #vision2014
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