Vision 2014: Driving Profitable Growth Through Emerging Consumer and Commercial Customers
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Driving profitable growth through emerging consumer and commercial customers
Ben Arnold DIRECTV
Paul DeSaulniers Experian
#vision2014
Sung Park Experian
2 © 2014 Experian Information Solutions, Inc. All rights reserved. Experian Public.
G = R⋅ fP ⋅ ne ⋅ fl ⋅ fi ⋅ fe ⋅ L
G = number of advanced civilizations
R = The birth rate stars like our Sun
ne = number of planets like Earth per planetary
system
fl = The fraction of the Earth‐like planets
supporting life
fi = The fraction of life‐supporting planets where
intelligent life develops
fc = The fraction of planets with intelligent life that
are capable of interstellar
communication
L = Lifespan of such civilizations
Accuracy of estimation
The probability
of a star
supporting this
type of
civilization is
3,333,333,333
to 1!
Dr. Frank Drake –
Astronomer, astrophysicist, founder of SETI
Drake equation – estimates number of civilizations capable of interstellar communication in galaxy
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Girlfriend equation – estimates the chances of finding true love in OC!
G = ?
Potential girlfriends
Population 3,055,745 3,055,745
Female % 56% 1,711,217
Accuracy of estimation
The probability
of finding a
girlfriend in
O.C. is
161,878 to 1! Age 28-50 27% 462,029
Master’s degree 5% 23,101
Single 50% 11,551
I find attractive 50% 5,775
Finds me attractive 10% 578
Likelihood of meeting 5% 29
Subtract my relatives 10 19
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0%
2%
4%
6%
8%
10%
12%
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
% of applicant
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
% of applicant
Accuracy of estimation
No information:
Cannot assess risk
Oldest trade = 10 years
Lower risk but imprecise
Oldest trade = 10 years
Current trades = 5
Lower risk more precise
0%
5%
10%
15%
20%
25%
30%
35%
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
% of applicant
Assess the risk of a new applicant for credit or services
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DIRECTV
► Challenges and opportunities of evolving markets
Extended ViewSM
► Providing credit risk insights of underserved consumer markets
Allscore
► Custom commercial risk solution to score every business inquiry
DIRECTV
► Implementation and results
Agenda
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DIRECTV
Expanding market needs
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DIRECTV overview
Note: All numbers reflect estimated 2013 Y/E
performance
DIRECTV Revenues: $32.8B
SKY Brasil (93% owned)
Subscribers: 5.4M
PanAmericana (100% owned)
Subscribers: 6.3M
SKY Mexico (41% owned)
Subscribers: 6.1M (Not consolidated)
DIRECTV Latin America Subscribers: 17.8M Revenues: $6.8B
Game Show Network
42% owned (Not consolidated)
Sports Networks Subscribers: 5.9M
Net Revenues: $0.2B
DIRECTV U.S. Subscribers: 20.2M Revenues: $24.7B
DIRECTV is the world’s largest pay TV provider with over 37 million subscribers
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2014 2010
The increasing breadth of competition has transformed the Pay TV market
2005
Most of these new and disruptive services are complements to Pay TV; however, there is a small but growing cohort of consumers replacing Pay TV with these services
Source: No Pay TV Analysis , April 2013
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Over the same time period, Pay TV penetration has plateaued
2013
85%
2012
85%
2011
86%
2007
86%
2006
85%
2005
84%
2010
86%
2009
88%
2008
87%
Overall Pay TV
Penetration
Percent
Source: SNL Kagan
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Rising SAC adds pressure to incremental gross adds decisions
2007 2008 2009 2010 2011 2012 2013
Avg. SAC per Sub $692 $715 $712 $796 $813 $859 $873
$-
$100
$200
$300
$400
$500
$600
$700
$800
$900
$1,000
USD
s ($
)
Average Subscriber Aquisition Cost per Sub
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Residential
► 1M – 1.5M unique applications per month
● Results in 300k – 400k gross activations per month
► Fee/no fee decision based on credit
● Very few “fee” customers activate
► Pre-extended view ~10% of applications were “no hit”
● All charged a fee
● Very low activation rate
Who walks through the door
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Commercial
► Only for specific business segments (public, private, and business viewing)
► If “hit” at Experian – no fee is charged, regardless of score
► ~35% of applications were “no hit”
► Activation rate falls by half when fee is charged
Who walks through the door
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Experian solutions for
emerging markets
Extended ViewSM for consumer
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Approximately 34 million U.S. households – 68 million people – are financially underserved
The underserved population
Source: FDIC 2011 Household Survey
Banked
86 million
72%
Underbanked
24 million
20%
Unbanked
10 million
8%
Total underserved
(% of U.S. households): 28%
Percentage
of ethnic groups
who are
underserved
55% Black
48% Hispanic
41% American
Indians
20% White
19% Asian
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Underserved doesn’t necessarily mean lower incomes
Underserved income distribution
28%
12%
5%
2%
0.50%
22%
26%
23%
19%
14%
Less than $15,000
$15,000-$30,000
$30,000-$50,000
$50,000-$75,000
At least $75,000
Underserved households by income
Underbanked Unbanked
Source: FDIC 2011 Household Survey
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Built from:
► Premier AttributesSM
► Rental data
► Full file public records
Score range 400-990
► The higher the score the more creditworthy the consumer
12–14 month performance window
Extended ViewSM Score
No hit to bureau
No trades on bureau (inquiry and/or public record only)
External collection trades only
Less than five open or closed trades on bureau
No open trades with updates in the last six months
Untapped!
FCRA compliant credit score designed to assess the creditworthiness of underserved consumers who have limited or no traditional credit history
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Population distribution
No credit trades
Thin file: External collection only
Thin file: Stale credit; no trades reported in six months
Thin file: four or less credit trades
Full file: five or more credit trades
82%
8%
3% 6%
1%
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Extended ViewSM Score Risk levels
Prime
30%
Subprime
70%
82%
6%
8%
1%
3%
30% of the underserved population will perform as prime credit consumers
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Retail
► Point-of-sale
Utilities
Auto
Telecommunications, energy and cable
Bank card
How are clients using this tool today?
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Experian solutions for
emerging markets
Allscore for commercial risk assessment
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Established businesses have business credit and commercial credit score
Emerging business credit risk lacking or non-existent
Creditor challenge – how to accurate assess commercial risk?
► Deposit assessment decreases acceptance
Experian solution:
► Allscore – score every commercial inquiry!
► Customized scoring solution using
● Traditional business credit bureau attributes
● Geographic risk of client portfolio
● Geographic risk of all businesses in U.S.
● Cannot be used for declination!
Allscore background
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Allscore background
Client portfolio
Bad rate by 5-digit ZipTM
Number of businesses
ZipTM 12347
Bad rate 7%
ZipTM 12343
Bad rate 4%
ZipTM 12344
Bad rate 6%
ZipTM 12346
Bad rate 4%
ZipTM 12345
Bad rate 5%
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Allscore background
Client portfolio
Bad rate by 5-digit ZipTM
Number of businesses
Client portfolio
Zip CodeTM 12345 and 12346 have enough businesses
ZipTM 12347
Bad rate 7%
ZipTM 12343
Bad rate 4%
ZipTM 12344
Bad rate 6%
ZipTM 12346
Bad rate 4%
ZipTM 12345
Bad rate 5%
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Allscore background
Client portfolio
Bad rate by 5-digit ZipTM
Number of businesses
Client portfolio
Zip CodeTM 12345 and 12346 have enough businesses
Client portfolio
Zip CodesTM without enough businesses get bad rate for the SCF = 3 digit ZipTM of 5.2%
ZipTM 123
Bad rate 5.2%
ZipTM 123
Bad rate 5.2%
ZipTM 123
Bad rate 5.2%
ZipTM 12346
Bad rate 4%
ZipTM 12345
Bad rate 5%
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Logistic regression modeling method
New geo-risk attributes
► Attributes based on geographic location – 5 digit ZipTM, SCF (ZipTM 3), CBSA – Core Based Statistical Area, state, population
► Risk of client portfolio’s commercial customers by geography
Allscore model development methodology
● Geographic risk stabilized by business density – risk weighted by concentration from smaller to larger region
● Risk of all emerging credit businesses by geography
▲ Identified emerging credit businesses from Experian commercial database
▲ Emerging credit businesses defined as young and thin
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Multi-segment model
► Experian “hits” using traditional credit attributes
► Experian “no-hits” using geo-risk attributes
Allscore model development methodology
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DIRECTV emerging
market solution
Implementation and results
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Model build
► Performed historical analysis using archive data
Issues with sample size
► Most “no hit” customers don’t activate
► Has secondary impact to performance of new subs
Extended ViewSM implementation
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Launched October 2013
Tail end of credit scoring waterfall
► Implemented as stand alone product
Reduced “no hits” by 20%
► Scored population skewed toward higher risk (expected result)
30,000 incremental gross activations exclusively from Extended ViewSM
► Mitigated risk of unknown behavior via calibration
► Mix is riskier than overall base – but better than just bottom end subs
► Lifetime Value (LTV) range from $200-$2000
Extended ViewSM implementation
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Launched September 2013
“No hits” reduced to 12% of inquiries scored (65% reduction)
Increased potential gross additions by 4.5k annually
► This included now charging a fee to normal Experian high risk subs
► Partially tempered as we did not charge a fee to all high risk subs
● Began charging a fee to new business segments
Allscore implementation
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Quality and quantity were significant enough to allow us to raise our fee and still maintain incremental gains in subscriber additions
► Reduces the take rate of fee subs (desired) to help mitigate risk
LTV range from $600 – $5000
Allscore implementation
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Leaders push boundaries and take risks
DirecTV took risks to expand into previously unknown markets
► Blind risk versus calculated risk
► Calculated risks = calculated benefits
Conclusion
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