ING-DiBa

Bart Buter

ING-DiBa AG

Frankfurt • 04. November 2016

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Die ING-DiBa an einem Tag

20.000 Anrufe im Kundendialog

4.300 Kontakte in der Immobilien-finanzierung

2.500 Email-Eingänge pro Tag im Kundendialog

5,2 Mio. Seiten-aufrufe im Internet

400.000 Logins im Internetbanking & Brokerage

50.000 Vorgänge im Dokumenten Service

29.000 Abhebungenan den 1.200 ING-DiBa Geldautomaten

160.000 ZugriffeMobile Banking App

2,304

3,749

2005 2015

5.3

8.5

2005 2015

82

241

2005 2015

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Erfolgreich anders

Privatkunden in Mio.

Mitarbeiterzahl

Geschäftsvolumen in Mrd. €

Drittgrößte Privatkundenbank

# Institut Kunden in DE in Mio.

1 Deutsche Bank PBC (inkl. Potsbank) 23

2 Commerzbank (inkl. Comdirect) 11

3 ING-DiBa 7,8

4 Santander 6,3

5 Targobank 4

Hohe Kundenzufriedenheit

Basis: Motivierte und engagierte Mitarbeiter

Geschwindigkeit von Veränderung nimmt weiter zu und Innovationsdruck auf die Banken steigt

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71% of Millenials

would rather go to the dentist than listen to what banks are saying.

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ING-DiBa Strategie – der Kunde steht im Mittelpunkt

3Q2016https://www.youtube.com/embed/B6K_hvM052g

Hackatonhttps://www.youtube.com/watch?v=di67BJPd8I0

Movie Time, Hackathon

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Income Estimation Use Case

Bart Buter / Georgios Gkekas

ING-DiBa AG

Frankfurt • 04. November 2016

International Advanced Analytics: Mentors

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Georgios GkekasSenior BigData Engineer

Expertise: Scalable BigData solutions, softwarearchitecture/development, distributed applications

Georgios.Gkekas@ing-diba.de

Bart ButerHead of Data Engineering

Expertise: Building Big Data Environments, Connecting People & Delegation.

Bart.Buter@ing-diba.de

Center of excellence in advanced analytics

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• Specialists in machine learning and big

data technologies

• Support business units

• Experiment with new data

• Technology

• Methods

• Sources

• Training and knowledge transfers

• Development of exploration

environment

• Fundamental research

From

Generalized predictions

Rule based

Millions of calculations

Sampled data

Structured data

Central Calculations

International Advanced Analytics

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To

Individual predictions

Self learning

Billions of calculations

Very large datasets

Structured and unstructured data

Distributed Computing

Our question to youCan you estimate the income of a person?

Be creative- We give you the problem- We expect a solution from you

Be a startup that we would like to work with- Work Responsibly

- Ethically- Legally

- Fit to our values and vision- Any time anywhere- Clear and easy- Empower us

You are a fictive startup

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Can you give us an indication of someone’s income based on publicly-available data. Furthermore, since working with personal data carries considerable responsibility, we would like you to investigate the legal and ethical implications of your solutions. We would like you to define a minimal set of data which you would want from the customer and which you can enrich with public data e.g. statistics bureau data, publicly-available profiles, income comparison sites, etc. We expect you to demo a working prototype together with a legal and ethical assessment of the prototype and a documentation regarding the validation of your results.

Challenge

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Income The flow of cash or cash-equivalents received from work (wage or salary), capital(interest or profit), or land (rent). (http://www.businessdictionary.com/definition/income.html)

Income estimation Using data to create a model that can estimate the incomeThis is not the same as the sum of all incoming money, because people can receive a one-off donation, get money back for dinner with friends, use money from their savings account, transfer money from one account to another.

Why? income might correlate with interest in financial products

Higher income:Investments & Mortgages

Lower incomeOver draft, savings goals

Income Estimation

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Because, In reality a bank would be unlikely to share its data with a young startup.

We have the expertise to analyze data internal to the bank, asking the same from you for this challenge wouldn’t add value to us.

However, We only have partial observability i.e. we only have access to our internal data, but we don’t have a full overview if a customer uses multiple banks.

Banking traditionally uses limited external datasets, with the rise of companies monetizing their data by providing data-services and government opening up datasets it might be that we have missed useful data sources.

We might have internal data sets about income that we are not allowed to use. i.e. for protecting our customers and the bank from fraud, more is permitted than for marketing.

Therefore, We’d like to see some creative use of the data available outside of our bank.

A data challenge without a data set

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• Open data• Income resources (gehalt.de,

stepstone.de)• Vacancy websites (monster.de,

stepstone.de)• Public social profiles• Statistics bureau (dstatis)• Public data from work councils (Verdi,

e.t.c.)• Public statistical data on prices

(immobilienscout.de)• Closed data• Private social profiles (Facebook, e.t.c.)• Professional networks (XING, LinkedIn,

e.t.c.)• Questionairs• Ask people to give you the information

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Possible Data Sources

• Methods• Scraping• Public APIs

• Technologies• Python libraries• scrapy -> https://scrapy.org/• lxml & requests -> http://docs.python-

guide.org/en/latest/scenarios/scrape/• Java libraries• Jaunt -> http://jaunt-api.com/• Jsoup -> https://jsoup.org/• jArvest -> http://sing.ei.uvigo.es/jarvest/

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How to get the data?

Service Oriented Architecture• Easy to consume• Easy to understand• Easy to integrate• Easy to deploy• Easy to discover• Easy to version• Rely on open standards• Based on APIs

Open Interfaces

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How to design?

Abstract - high degree of aggregation

https://income.de?postal=604**&age=30-50

{" income ": [

{"range": "55000-70000","probability": 86%

},{

"range": "45000-60000","probability": 78%

}]

}

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API design - Fine grained control over the detail of the result

Detailed - high degree of personalization

https://income.de?street=heerstrasse&postal=60488&name=georgios-gkekas&linkedinid= 0672474{

“income": [{

"range": “69120-70300","probability": 93%

},{

"range": “61450-63900","probability": 86.5%

}]

}

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API design - Fine grained control over the detail of the result

Data is more important than insights / analytics

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What do we want from you?

Scrapedata

Gatherunstructured

data

Structured data

Usefulinformation

Understanddata

Estimateincome

Higher importance Lower importance

ImplementationMethod

Sources

Data mining

APIs Scraping

ML

You could also design an API for getting JUST the data from the various data sources

• Raw data• Aggregated data• Combined data• Enriched data

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API design – Raw data retrieval

• Present your data sources• Present an evaluation of legal considerations & access methods• Present method for structuring the data

• Define API/interface• High-level architecture

• Tech stack• Data flow

• High-level implementation plan• Work packages

• Make sure your proposal is feasible under the time constraints• Supporting materials

• Not desired but up to 2 pages if necessary to convince us

Proposal for the first deliverables

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- You are not working for DiBa, your ideas, solutions and actions are yours.

- Financial matters and related data are private and sensitive, treat them as such.

- When in doubt contact us or your professor.

Rules

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Vielen Dank!

Bart Buter – Bart.Buter@ing-diba.de 069 / 27 222 66776Georgios Gkekas – Georgios.Gkekas@ing-diba.de 069 / 27 222 69371

International Advanced Analytics

ING-DiBa AGTheodor-Heuss-Allee 260486 Frankfurt am Main

www.ing-diba.de

YouTube.com/ingdiba

@ING_DiBa_Presse

Instagram.com/ingdiba

Facebook.com/ingdiba