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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


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


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


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


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


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


DIRECTV

Expanding market needs


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


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


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


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


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


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


Experian solutions for

emerging markets

Extended ViewSM for consumer


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


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


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


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%


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


Retail

► Point-of-sale

Utilities

Auto

Telecommunications, energy and cable

Bank card

How are clients using this tool today?


Experian solutions for

emerging markets

Allscore for commercial risk assessment


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


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%


Allscore background

Client portfolio



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%


Allscore background

Client portfolio



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%


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


Multi-segment model

► Experian “hits” using traditional credit attributes

► Experian “no-hits” using geo-risk attributes

Allscore model development methodology


DIRECTV emerging

market solution

Implementation and results


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


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


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


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


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


For additional information, please contact:

[email protected]

[email protected]

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