next generation credit decisions: where big data outperforms the credit bureaus
TRANSCRIPT
BIG DATA SCORING2015
OUR VISION
BRING LENDING INTO THE DIGITAL INFORMATION AGE
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ATTRACTING THE NEXT GENERATION OF AUTO BUYERS
LENDING TO THE UNDERBANKED NON-PRIME CUSTOMERS
23% of UK population, that is
15m people
25% of USA population,
that is 83m people
…
13% of UK population, that is
8m people
20% of USA population,
that is 64m people
…
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Credit scoring for the past 20 years…
FICO
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Credit scoring 2.0
FICO
6Source: Telefonica Millennial Study
People aged 18-33 spend on average 6h a
day online
Studied abroad
Doesn’t use credit cards
No student loan
Fan of Apple Pay
Irregular income
No mortgage
Has a blog
Fan of social media
Freelancedesigner
Loves hissmartphone
Has tons of friends
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Social media
Device infoInternet service
provider
Google searchresults
Governmentdatabases
Onlinebehavior Employer info
Blogs
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Social media
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Freelance jobs
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Behavior
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Device
Government data
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Location
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Public online data
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Current situation
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With Big Data Scoring
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Case 1 – credit loss decrease 34.6%BEFORE• Client: non-bank consumer
lender in CEE• Current scoring: regression
based models• Current data: (1) loan
application, (2) negative credit bureau data, (3) positive credit bureau data
• Credit loss: 7.5% (accepted clients in scorebands 7-10)
AFTER ADDITION OF BIG DATA
While accepting the same amount of loan applications,
credit loss dropped by 34.6% to 4.9%
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Case 2 – also works with offline clientsBEFORE• Client: non-bank consumer
lender in CEE• Current scoring: regression
based models• Current data: (1) loan
application, (2) negative credit bureau data, (3) positive credit bureau data
• Credit loss: 6.2% (accepted clients in scorebands 4-10)
AFTER ADDITION OF PARTIAL BIG DATA SCORE TO OFFLINE
CLIENTS
While accepting the same amount of loan applications,
credit loss dropped by 9.7% to 5.6%
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Thank you!Erki [email protected]+44 7852 266613
Big Data Scoring Ltd1 Canada Square, Canary WharfLondon, E14 5AB