diba - data challenge - frankfurt big data lab test if your idea is shared by others. ... diba data...
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ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
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ING Mid Grey
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Text Colour
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DiBa - Data Challenge
Bart Buter, Data Engineering / International Advanced Analytics
ING-DiBa AG
Goethe Universität Frankfurt • 27. Okt 2016
ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
No content below the grey line
1. ING-DiBa Kurzprofil
2. Data Challenges
3. Organisation & Rules
2
Inhaltsübersicht
ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
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3
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 Abhebungen an den 1.200 ING-DiBa Geldautomaten
160.000 Zugriffe Mobile Banking App
ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
No content below the grey line
Mehr als Länder in Europa, Nord Amerika, Lateinamerika, Asien und Australien
Mehr als Millionen private, Firmen- und institutionelle Kunden
4
ING in Europa und weltweit
ING in Europa
Marktführer Benelux
Herausforderer
Wachstumsmärkte
Ausschließlich Wholesale Banking
34
40
Mehr als Mitarbeiter
54.000
ING weltweit
ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
No content below the grey line
Wir wollen „Digital Leader“ in der Finanzbranche sein.
5
Legitimation von zu Hause aus
Videolegitimation Fotoüberweisung und Dokumenten- Upload
Rechnungen und Dokumente per Kamera einscannen und direkt über- weisen oder ein- reichen
Kreditwunsch mobil prüfen
Mobiler Kreditcheck
SmartSecure App Fingerabdruck ersetzt TAN
„Die Filiale der Zukunft haben viele Kunden
schon heute jederzeit und überall in der
Hosentasche dabei: das Smartphone“
ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
No content below the grey line
Knowing information about someone's income can be desirable in some cases and required in others. For instance, in loan
processes this information is required and regulated: it needs to be substantiated by evidence, because proof of income is required
to assess if someone is capable of repaying a loan. However, in other cases the requirements are less strict. For instance, when
marketing a new investment product, this marketing campaign should be to a target audience that has disposable income to put
into investments. For other customers this type of marketing will be irrelevant. Having an estimate of someone's income will
therefore lead to fewer customers receiving irrelevant marketing and a higher success rate for the campaign. At the same time we
want to simplify the banking experience for our customers and not ask them too many questions. Therefore, it might be more
customer-friendly if we could ask for less information from a customer, but find different ways of estimating what the income of
such a customer is.
Challenge No 1:
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 1: Income Detection using Public Data
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ING Orange
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ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
No content below the grey line
Data: - Vacancy websites - Public profiles - Statistisches Bundesambt - Chamber of Commerce - Friends and Family
Legal Ethical Assesment: - Are you allowed to use my Xing profile?
Is it desirable? - Is there an API? What are the conditions
for using it?
Validation: - Is my income truly 4709-7858 ??
7
Challenge 1
Xing: Bart Buter – Head of Data Engineering Gehalt.de: Leiter Data Engineering Income: 4.709 – 7.858
ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
No content below the grey line
Currently, many financial apps show your current balance and past transactions, others have started to include complex graphs
and visualizations, but is this the information our customers really want to see? Maybe some are only interested in knowing that
their salary has been deposited into their account and if the utility bills have been paid; others might want to see how much they
have spent on their new home theater setup. Again others might want to see how much money someone in their peer group
spends on buying a new car, while certain customers are interested in how much they need to invest to have a comfortable
retirement. This shows that not every customer has the same wishes and that it makes sense to think of solutions for a certain type
of customer.
Challenge No 2:
Our challenge to you is to design the next generation data-driven banking app for your generation (Millennials born between 1980-
2000, Generation Z 2000-2020). Base your solution on what data is currently available to you in your banking environments and
think about what is missing, or what you would like to see. Furthermore, creating applications for customers is not about what you
think is a great idea, but rather about what they think is great to use. Therefore, you should identify features that are missing in the
current banking apps, identify multiple solutions to solve this and find out what the best solution is. Base your decisions on the
needs and wants of the customers, i.e. by doing customer research. In the end we expect a working prototype of your solution,
which can be part of the next generation banking app for your generation. Additionally, we expect to see the results of the
customer research that led you to the proposed solution.
Challenge 2: Next Generation Banking
8
ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
No content below the grey line
Data:
- Your transactions from your bank.
- Friends and families
- Mobile phone
- Location
- Activity
Pitfall:
- I would like xyz. Therefore, it is a good idea
Validation:
- Test if your idea is shared by others.
- Do they have the problem you are trying
to solve?
- Do they agree that your solution is the
right solution?
9
Challenge 2:
ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
No content below the grey line
DiBa Data Challenge Team
Bettina Hartlich
Stevie Albert
Georgios Gkekas
Organisation
Christine Hennighausen
Bart Buter
10
Every team gets a mentor Discuss office hours with mentor
ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
No content below the grey line
Prizes
11
ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
No content below the grey line
- 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
12
ING Orange
RGB= 255, 98, 0
ING Light Grey
RGB= 168, 168, 168
ING Indigo
RGB= 82, 81, 153
ING Sky
RGB= 96, 166, 218
Colour Guidelines
ING Fuchsia
RGB= 171, 0, 102
ING Lime
RGB= 208, 217, 60
ING Leaf
RGB= 52, 150, 81
ING Mid Grey
RGB= 118, 118, 118
Text Colour
RGB= 51, 51, 51
Vielen Dank!
Bart Buter Head of Data Engineering – International Advanced Analytics ING-DiBa AG Telefon 069 / 27 22266776 Theodor-Heuss-Allee 2 60486 Frankfurt am Main bart.buter@ing-diba.de
www.ing-diba.de
YouTube.com/ingdiba
@ING_DiBa_Presse
Instagram.com/ingdiba
Facebook.com/ingdiba
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