(BIG) DATA IN CREDIT SCORING - ADM · Company confidential –Do not distribute without notice ©AE...

Company confidential – Do not distribute without notice ©AE 2014 1

(BIG) DATA IN CREDIT SCORING

Value and Approach

Bram Vanschoenwinkel

ADM 04/10/2016


PASSIONATE DECISION SUPPORT ARCHITECT

Master in Computer Science, Ph.D. in Science (Machine Learning, Data Mining)

6y Management Consulting @ MÖBIUS

5y Information Management & Analytics @ AE

(different sectors: finance, retail, utilities, postal services, industry, insurance, HR services,…)

SOLUTION LEAD ANALYTICS

Responsible for the Analytics offering @ AE

Strategy, presales, recruitment, team lead, project lead

+ inspire other people

To acknowledge the potential and joy of analytics


In a world where technology is radically changing the way your customers interact with the world, you want to be able to make better decisions faster.

AE conceptualizes, designs and builds intelligent decision support systems to

optimize operational excellence

support the best

customer experience

drive your strategy by enhanced

insights

develop innovating

business models


Credit Scoring

Possibilities and value introduced by (big) data

Project Approach


CREDIT SCORING

Credit Risk:

uncertainty or likelihood that a negative event takes place.

Risk management is the broad term to

control and regulate the risk to the extent possible.

In financial terms, a negative event is a loss.

Risk of default, most commonly defined as 90 days past due

Credit is vital to theeconomy,

but not without

RISK


To be honest, I amnot that

creditworthy

I already have a lot of debt

elsewhere but I am going to try

here

I am extremelycareful, will payoff straight away

I am not too suremyself whether I can pay off my

loan

ADM

CREDIT SCORING


NOW EOL

We can only usedata generated bythe applicant up to

this point!

PREDICT

Probability of default

1%

67%

20%

11%

78%

CREDIT SCORING


Credit Scoring


Project Approach


POSSIBILITIES INTRODUCED BY (BIG) DATA

InternalTraditional

Same methods used for over decades

VariablesUsually length of relationship with the bankPrevious credit informationTotal amount of resources at the bankStill a lot of subjective interpretation involved to make the final decision

Classification TechniqueLogistic regression


InternalNon Exploited


New variables that are already available internally

• current and savings account informatione.g. pseudo social network built on credit and debittransactions

• derived variables on account movementse.g. preferred day of week for transactions

• data collected for marketing purposes• unstructured data

e.g. calls to call center, complaints, emails• etc.

“New” classification techniquesSupport Vector Machines, Random Forests, …


External


Variables sourced externallySocial Media informationKBO sector informationTelecomGovernment

“New” classification techniquesSupport Vector Machines, Random Forests,…



InternalTraditional

InternalNon

ExploitedExternal

New

classification

techniques


For the riskiest 5% of thepopulation, we now have an 8 times better chance of pickinga real defaulter than a random

pick

3 times better than the

original traditional model

Lift chart

VALUE INTRODUCED BY (BIG) DATA


Big improvementin risky segments

VALUE INTRODUCED BY (BIG) DATA


Credit Scoring


Project Approach


Agile Analytics

Iterative and Incremental

cost

value

cost value

PROJECT APPROACH


Scrum

Was last option valuable?If so, continue. If not, ..

Check next option?

Ability to showcase results at each iteration + check if you are on right track

What went well last sprint?What didn’t?

Ability to redirect at each iteration/sprintAbility to tackle problems before they grow

PROJECT APPROACH


Profiles involved

Risk Business experts

External Data Scientists

PROGRAM MANAGER

PRODUCT OWNER

SCRUM MASTER

BUSINESS STAKEHOLDER

PROJECT APPROACH


We live in a data flooded world,

agile is a great way to

scratch the surface

so that we can take a

direction

that is guided by business value

(BIG) DATA IN CREDIT SCORING - ADM · Company confidential –Do not distribute without notice ©AE...

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