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LendIt USA 2017
About our speaker:
Paul DeSaulniers Sr. Director, Experian Email: Paul.Desaulniers@experian.com Phone: 714.830.7580
28/02/2017
LendIt USA 20174
1. Trended data 101
2. How Trended Data helps lenders
3. Leverage the power of trended data
4. Best practices
5. Q&A
Agenda
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Market perspective on trended data
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An underutilized tool today due to technology barriers
Intuitively ‘trended data’ sounds like a no-brainer (with value seen across the credit chain of acquisitions, origination and account management) but the limitations of technology have historically prevented its widespread use. Change after all requires people, process and technology; and “trended data” has historically been difficult to deploy with a lot of testing required – and ultimately needs the customers to adjust their decisioning, acquisition, offering and other strategies.
Barclays Research October 6, 2016
“
”
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• Understand trended data beyond the buzz word
• Learn what trended data can tell you across the Customer Life Cycle to improve your business
• Most effective uses of trended data
• How to use trended data to solve your most pressing business challenges
Objective
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Trended Data24 months of history on key data fields for every trade
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Trade #1 Balance Credit limitMinimum
payment dueAccount payment
Date of payment
Month 0 $13,300 $25,800 $275 $1,000 Aug
Month 1 $14,680 $25,800 $280 $1,000 July
Month 2 $16,060 $25,800 $286 $1,000 June
Month 3 $17,440 $25,800 $297 $1,000 May
Month 4 $18,820 $25,800 $310 $1,000 April
Month 5 $20,200 $25,800 $330 $1,000 March
Month 6 $21,580 $25,800 $343 $1,000 February
Month 7 $22,960 $25,800 $350 $1,000 January
Trade #1
Bank name Account # Open
date Credit limit Balance Actual payment
Loan type
Account condition
Account status
Special comment
Months reporting
Minimum payment
due
Months since
update
Date of payment
Visa 4812 3/9/1990 $25,800 $13,300 $1,000 Credit card OPEN CURR ACCT CH 231 $275 1 Aug-13
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A unique profile of a consumer
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FebruaryVantageScore® 720Balance $22,000 Status Good standing
Month Balance Min Pay Due Actual PayJan $22,000 $550 $2,000 Dec $26,000 $650 $3,500 Nov $20,000 $500 $12,000 Oct $28,000 $700 $8,000 Sep $35,000 $875 $6,000 Aug $45,000 $1,125 $11,000 Jul $48,000 $1,200 $3,000
Month Balance Min Pay Due Actual PayJan $22,000 $550 $550 Dec $19,000 $475 $475 Nov $16,000 $400 $400 Oct $15,000 $375 $400 Sep $11,500 $288 $320 Aug $9,000 $225 $300 Jul $6,500 $163 $200
Consumer A Consumer BFebruary
VantageScore® 720Balance $22,000 Status Good standing
✓Paying well over minimum payments
✓Demonstrated ability to pay
✓No payment stress
X Making minimum payments for the last three months X Payment amounts vs. minimum due is decreasing over time X Increasing payment stress
Trad
e D
ata
Tren
ded
Dat
a
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Differentiating consumers through payment data
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Consumer A Consumer B Consumer C Average monthly balance $3,462 $3,435 $3,465 VantageScore® 740 736 744
Monthly balanceand payments
Total annual payments $1,126 $22,390 $42,429 Average % of balance paid 2.6% 53.4% 100.0%
Who is the best prospective customer?
$- 0
$1,750
$3,500
$5,250
$7,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Total Bankcard BalanceTotal Bankcard Payments
Jan Feb Mar Apr May Jun Jul Aug Sep Oct NovDec Jan Feb Mar Apr May Jun Jul Aug Sep Oct NovDec
Historical payment data enables a much better understanding of how a consumer uses their bankcard accounts
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Problem:
Solution:
Benefit:
How trended data helps lenders
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Knowing a consumer’s credit information at a single point in time only tells part of the story
To understand the whole story, lenders need the ability to assess a consumer’s credit behavior over time
Understanding how a consumer uses credit or pays back debt over time can help lenders: • Offer the right products & terms to increase response rates • Determine up sell and cross sell opportunities • Prevent attrition • Identify profitable customers • Avoid consumers with payment stress • Limit loss exposure
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Data…
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10
trades
24 months
1,200 DATA POINTS
1 consumer
5 historical
payment fields
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…and more data!
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10
trades
24 months
120,000,000 DATA POINTS
100,000 consumers
5 historical
payment fields
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But there is a solution to help clients unlock the power of trended data…..
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Credit Profile Point-in-time snapshot
of a consumer’s credit standing
Trended Data Dynamic story
of how a consumer is using credit over time
Credit3D Solutions that
unlock the power of the credit profile and trended data
3D
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Trended Data Time Line
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1998 2000 2002 2004 2006 2008 2010 2012 2013 2014 2015 2016 2017
1998 Experian launches “Credit Trends”
2001 First batch
product “TrendView”
(73 attributes)
2002 Launch Trended
Raw Archive
data
2005 Custom
trended data models on Exp. data
2010 Experian launches:
Short term (108)
Credit Line Mgmt (56)
2012 Experian launches
TAPS (Total Annual
Plastic Spend)
2013 Payment Stress
(132) Balance transfer
(2)
2014-2015Experian “extends” trade table by 18 new fields and launches
EIRC (Estimated Interest Rate Calculator)
Experian is the first in the industry to provide trade level spend, yield and revenue data by industry in a non-consortium
environment
2016 Experian launches
Trended Data in on-line credit
reports
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Trended Data/ Credit3D A comprehensive view of the consumer
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Payment behavior: MIN PAY – 2%
Annual card spend: $7,500
6 month yield: $ 74
Average effective APR 16.99%
In the market? Personal Loan
BT Index (0-999) 875
BTs in last 12 months 2
Revolving trades: 4
Transacting trades: 0
Surfer, Transactor- Segment ID
Utilization increase in last 6 months:
+ 35%
Credit card balance last 6 months:
+ $8,000
BEHAVIOR
RISK REVENUE
RESPONSE
Credit3D leverages
behavioral insight to improve risk, tap into new credit segments,
improve response, profitability and develop market share strategies
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Experian TAPS℠ • Annual credit card spend Estimated Interest Rate Calculator℠ • Interest rate and term information
for personal loan, student loan, auto, revolving bankcard, retail bankcard and mortgage
Extended Trade • Trade-level profitability metrics Custom models • Client initiated
Trend View℠ • Identify revolving / transacting
trades
Short-Term Attributes℠ • Capture balance / utilization
changes
Line Management Attributes℠ • Identity limit changes Payment Stress Attributes℠ • Aggregate payment data Custom attributes • Client initiated
In the Market Models℠ • Propensity to open auto, personal
loan, student loan, mortgage, HELOC and bankcard
Balance Transfer Index℠ • Propensity to balance transfer Balance Transfer Surfer Overlay℠ • Propensity to be a rate surfer Custom scores • Client initiated
Leverage the power of Trended Data
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Trended attributesProfitability modelsPropensity scores
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Credit3D / Trended Data capabilities
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Who is likely to respond to an offer? Balance Transfer Index℠
In the Market Model℠
Likelihood to balance transfer in 6 months
Likelihood to open a trade in next 90 days
Is there a better way to understand risk or to conduct swap set analysis?
Payment Stress Attributes℠
Deleveraging Attributes℠
Level of consumer payments against balances
Change in total payment obligations over time
Short-Term Attributes℠ Changes in revolving balance and utilization
How can I acquire profitable consumers? How do I increase wallet share and usage?
EIRC for Revolving℠
Experian TAPS℠
Yield in the last 6 months and effective APR
Credit card spend in last 12 months
How does a consumer use credit? How do I identify revolvers, transactors and consolidators?
Trend View℠ Revolving / transacting trades / balance transfer activity /seasonality Trend View Segment ID
Business Challenge Solution What clients receive
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Marketing strategy should be about more than just response rate. A comprehensive approach can ensure quality originations and healthy portfolio growth. ➢Response Rate ➢Risk Expansion ➢Long-term Value
Three Pillars of Comprehensive Prescreen
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How do you reach receptive audiences to get the most out of your marketing campaigns?
Offer timing Offer relevance
Combine propensity models and offer relevance to get the right consumers the right offer at the right time.
Response Rate: Make an ImpactMost people don’t need your product; are you effectively finding those that do?
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Risk Expansion: Not Your Average JoeRisk expansion without all the risk
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Current Profile • Credit Score: 641 • Utilization: 41% • Revolving and Personal Trades: 4 • Outstanding Balances: $13,000 What’s Joe Doing? • Making more than the monthly payment to pay down revolving debt • Seeking personal loan to consolidate remaining balance • Wants one monthly payment at a lower interest rate than revolving
cards Where’s Joe Going? • Prime risk score as a result of decreased utilization • Building new borrowing relationships How do you spot the trend? • Declining trended utilization indicating deleveraging • Ability to pay indicated by estimated income
` Past Present Future
Score 618 641 703
Utilization 66% 41% 23%
Trades 6 4 4
Balances $21,000 $13,000 $6,000
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• Maximize response rates: Propensity tools aren’t enough. Layering credit attributes can further refine results and improve campaign performance.
• Risk expansion: Expand risk score cutoffs without taking on incremental risk. Trended data helps identify trends in credit behavior. Find candidates in lower score ranges who are deleveraging and trending up.
• Long-term value: Understanding how a consumer uses credit enables long-term loyalty building. Give your team the edge by identifying likely short-term and long-term borrowers.
Think comprehensive
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LendIt USA 2017
Paul DeSaulniers Sr. Director, Experian Email: Paul.Desaulniers@experian.com Phone: 714.830.7580
28/02/2017
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