The best services have one thing in common: a superb customer experience. Banking services are no exception to this rule, and indeed the quest for an effortless, well informed, and personalized customer experience is one of the main goals of today's innovation in digital banking services. According to what Maslow has described in his "pyramid of needs", customers are seeking a more intimate and meaningful experience where banking services can actively assist the customer in performing and managing their financial life. Predictive APIs have a fundamental role in all this, as they enable a new set of customer journeys such as automatic categorization of transactions, detecting and alerting recurrent payments, pre-approving credit requests or provide better tools to fight fraud without limiting legitimate customer transactions. In this talk, I will focus on how to provide better banking services by using predictive APIs. I will describe the path on how to get there and the challenges of implementing predictive APIs in a strictly audited and regulated domain such as banking. Finally, I will briefly introduce a number of data science techniques to implement those customer journeys and describe how big/fast data engineering can be used to realize predictive data pipelines.
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ING group
http://www.ing.com/About-us/Purpose-Strategy.htm
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ING group
Empowering people to stay a step ahead
in life and in business.
http://www.ing.com/About-us/Purpose-Strategy.htm
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Abraham Harold Maslow
(April 1, 1908 – June 8, 1970) was an American
psychologist who was best known for creating
Maslow's hierarchy of needs
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Human needs
Physiology
Contractual
Love & belonging
Esteem
Self-actualization
breathing, food, water, sleep
security of body, resources,
health, employment, property
friend, family, partner
security of love and belonging
self-esteem, confidence,
achievements, respect
spontaneity, creativity,
acceptance, freedom, ethics
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Data as a Relationship
Trust
Transparency of Use
Customer First
Regulations and Laws
Respect and Protect
Providing a Service
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Help the customer
Propose, Advise, Select, Filter, Connect, Simplify
Actionable Data, Ethical approach
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Help the customer
Propose, Advise, Select, Filter, Connect, Simplify
Protect the customer
Detect, Prevent, Alert, Block, Defend, Identify, Authorize
Actionable Data, Ethical approach
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Strategic data-driven initiatives
● We are looking at fintech innovation to help
strengthen our lending capabilities and better serve
our consumer and SME clients.
● We launched a strategic partnership with Kabbage,
one of the leading US-based technology platforms
providing automated lending to SME.
● A first pilot project, in Spain, is underway.
● In January 2016, we made an investment in fintech
WeLab, which provides consumer loans in China and
Hong Kong in a fully automated process that just
takes minutes, from application to approval.
http://www.slideshare.net/ING/4q15-media
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Strategic data-driven initiatives
http://www.slideshare.net/ING/4q15-media
● Innovation helps to empower people to make better
financial decisions
● In Poland, we launched Moje ING, a new omnichannel
banking platform, based on a similar platform in Spain.
● The platform gives customers insights
into their personal finances in an easy
and intuitive way.
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Predictive API’s: How to get there?
Input
Hand Designed
Program
Input Input
Rule-based System
Output
Hand Designed
Features
Mapping from
features
Output
Learned
Features
Mapping from
features
Output
Classic Machine
Learning
Input
Learned
Features
Learned
Complex features
Output
Mapping from
features
Representational
Machine Learning
Deep Learning
Prof. Yoshua Bengio - Deep Learning
https://youtu.be/15h6MeikZNg
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Predictive API’s: How to get there?
Data +
Tools / Applications / API’s
Frameworks & Libraries
Scientists & Engineers
Domain Experts
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Predictive API’s: How to get there?
Data +
Tools / Applications / API’s
Frameworks & Libraries
Scientists & Engineers
Domain Experts
21. @natbusa | linkedin.com: Natalino Busa
Predictive API’s: Research at ING
Clustering geolocated data
using Spark and DBSCAN
How to group users’ events using machine learning and distributed computing
By Natalino Busa
January 28, 2016
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Real-time fraud detection using process
mining with Spark Streaming
Bolke de Bruin (ING), Hylke Hendriksen (ING)
Data Science & Advanced Analytics
Predictive API’s: Research at ING
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Data Science: quality and parsimony
How data scientists feel
about their models
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Data Science: quality and parsimony
How data scientists feel
about their models
How managers feel about
data scientists’ arguing models
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Data Science: start lean
● What‘s the improvement?
● Can you quantify your model quality?
● Can you quantify impact impact?
● What is the impact for the customer journey?
● Can it be converted in financial results?
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Tools and applications:
inspiration from the web
The API for banking data.
Two levels:
- Transactions
- Risk Scoring