Vision 2014: The Ultimate Collections Waterfall

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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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For additional information, please contact:

Rollin.Girulat@experian.com

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