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Edward Arciniega Bank of America
Brian Gourlay Bank of America
The ultimate collections waterfall – build your collections waterfall to ensure compliance and guarantee operational excellence
John Lewis Intellaegis
Rollin Girulat Experian
#vision2014
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Rollin Girulat
Senior Product Manager, Experian
John Lewis
President, Intellaegis
Edward Arciniega
Sr. Vice President, Bank of America
Brian Gourlay
Sr. Vice President, Bank of America
Introductions
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The waterfall Rollin Girulat
Measuring and tweaking strategies John Lewis
From the field Edward Arciniega / Brian Gourlay
Panel discussion
Questions
Agenda
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The waterfall
An overview
Rollin Girulat
Experian
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The ultimate collections waterfall
What does it take to win
a major NASCAR race?
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The ultimate collections waterfall
Strategy and tuning!
So what is the parallel
between the collections
waterfall and NASCAR?
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Traditional waterfalls
Consideration I
Should I work the account?
Bankruptcy
Deceased
Military scrubs
Litigious consumers
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Traditional waterfalls
Consideration II
Skip tracing
Verify current address is good or
Search for new addresses
Look for new phones
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Traditional waterfalls
Consideration III
Scoring or prioritization
Which accounts to work first
Which accounts to work hardest
How much money to spend on an account
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The power of scoring
Working Top-20% returns almost 65% of dollars
Incidence model performance – blended data Recovered accounts captured by 5% increments
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Traditional waterfalls
Pass I
Compliance
Pass II
Skip tracing
Pass III
Scoring
10,000 records
9,500 records
7,000 records
4,200 records
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Waterfall alternative A
Pass I
Scoring
Pass II
Skip tracing
Pass III
Compliance
10,000 records
6,000 records
4,500 records
4,275 records
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Waterfall alternative B (Optimal)
Pass I
Compliance
Pass II
Scoring
Pass III
Skip tracing
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Triggers
New contact information
New signs of ability to pay
New legal hurdles (e.g., bankrupt)
The last step – PUSH
Photo: Royalbroil, published on Wikimedia Commons, June 2013
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Underlying data you buy should be of high quality
Ability to flow from step to step in the waterfall
► Should be easy to control
► Should be quick (ideally single submission)
Reporting at each step should be clear
Ability to tune / tweak should be relatively easy
Easy to implement interfaces or layouts
Last thoughts on waterfalls
Photo: Dave Hogg, Brooklyn, Michigan, published on Wikimedia Commons, June 2008
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John Lewis President,
Intellaegis
Experian Strategic Partner
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Auto finance lender – 1982-1988
► Chrysler Credit and Mitsubishi Acceptance
Auto finance vendor – 1989-2001
► Built largest repossession company in the U.S.
► Built first skip company in auto finance
Collections software – 2007-Present
► FindJohnDoe.com
► Intellaegis.com
● Financial services
● Law enforcement and government intelligence
Introduction John Lewis
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Not using a waterfall strategy for your data gathering process is like drinking water through a fire hose!
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Web-based data
Paper and PDF’s
Copy and paste
Difficult to track data
Permissible purpose and compliance tracking is a challenge
Duplicate data purchases
Batch data
Manual – not real-time
Challenge to make data actionable in software
XML data
Real-time
Waterfall changes on the fly
Integrates with software
► Workflow and automation
► Auto track compliance
► Interface telephony
Data fusion – Web to batch to XML Keep your eye on data
Big Data strategic
► ROI and RPC measurable
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Big Data strategy
Source: IBM institute for Business Value 2013 Big Data & Analytics Study
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Focus efforts on making calls…
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Simplified waterfall
The waterfall model is a sequential design process in which progress is
seen as flowing steadily downwards (like a waterfall) through the phases
of conception, initiation, analysis, design, construction, testing, production /
implementation and maintenance. — wikipedia
“ ” Scrub
Gather
Scrub
Consume
Gather
Scrub
Consume
Repeat
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Automated scrub
► Death, SCRA, BK – compliance
Gather data automatically
► TCPA – landline vs. cell – compliance
Predictive analytics
► Collectability score to start with most collectible
► Increase RPC
Consume data
► Spend time calling, not looking for data
► Work in a 100% compliant environment
Measure RPC/ROI
► Tweak as needed
The ultimate waterfall
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Waterfall strategy
Using technology and data helps identify the right party to call,
and it prevents you from calling the wrong party
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Deceased scrub
“I’m sorry, my husband passed away last year. I’ve told that to at least
five people at your company… Don’t you have a way to know this?!”
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SCRA scrub with automation
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Regulatory law scrub How do you program this?
Software should prevent users from making calls that violate federal and
state regulatory laws
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Compliance scrub Automated compliance and overrides
All materials are confidential and not to be shared or distributed without written permission by Intellaegis LLC
Compliance rules are hard coded for federal and state regulatory laws
DNC overrides are available as temporary or permanent (opt-in)
Local time zone limits are honored based on area code
Stop calling wrong parties
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Last step is most important Measure and tweak
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It’s critical you measure RPC and ROI in real-time
RPC should apply to all phone numbers, including non-customer telephone number and all customer addresses
► This is how you measure data ROI and RPC
Drive your ROI with these stats
Automatically evaluating the waterfall process
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Measuring call penetration
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Measuring RPC in real-time
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Measure your bottom line results
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Edward Arciniega Senior Vice President Bank of America
Experian Strategic Partner
Brian Gourlay Senior Vice President Bank of America
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The purpose of the automated skip tracing program is to standardize the use of the tool and ensure maximized utilization of the collector’s time and limit the ability to contact third parties
The program will provide automated running of skip tracing products at certain intervals within the Bucket 1 and Bucket 2 collection cycle
The program focuses on the correct tool to use at the correct time thereby taking the decision making out of the hands of the collector
► The team members are given their time back so as to be able to do the work vs. getting the data
Through these efforts the desired outcome is that the team member improves their overall results, gets more contacts and drives accounts current
From the field
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Bucket 1
Within Bucket 1 we do a validation of the portfolio to ensure the data we have is accurate and most up to date
► This is a large number however the cost to benefit ratio is high
► We would look to do a verification of telephone numbers, three maximum
► Any conflicting / confirmation of data will be brought in and loaded onto the system of record notes
From the field
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Bucket 2
The searches become much more directed
► A review of usage shows redundancies where collectors are using multiple products to get the same results, with cost.
► Best direction was to create automated searches at 40 and again at 50 days delinquent
► At 40 days maximize contact data
● Example: Contact Plus
► At 50 days validation of data in preparation for Bucket 3
● Example: People at work
From the field
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Cost
Manual hits East West TTl Automated
Hits 3840 8098 11938 Customer
Input 16,708 Cost
cost per hit cost per hit
Auto Manual
Cost 2076 4697 6773 Hits 9,144 1837 0.2 0.57
Cost
per hit 0.54 0.58 0.57 54.73%
DPD Test Group Accounts Bad Count Bad Rate
20 Automated skip trace Manual skip trace
768 238
258 82
33.59% 34.45%
40 Automated skip trace Manual skip trace
3,461 852
818 195
23.63% 22.89%
50 Automated skip trace Manual skip trace
1,364 330
454 88
33.28% 26.67%
Total Automated skip trace Manual skip trace
5,593 1,420
1,530 365
27.36% 25.70%
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Open discussion
Questions
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