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Recently, ING WBAA completed its second yearly experimentation week — a week full of energy, curiosity, anticipation for outcomes and celebrations. It’s such a pleasure working in a team that provides the freedom to explore interesting possibilities by dedicating valuable time to experimentation.

This time, I was one of the twelve people who chose to work for the Plastic Whale experiment. The “captain” — as we call the initiator of each idea — was Marc Rooding — Chapter Lead Software Engineering at WBAA. I was very enthusiastic from the first moment that Marc expressed his desire to run an experiment for such a valuable social good cause, and this enthusiasm was even greater for all of us once we realised we would work with Plastic Whale’s representatives, throughout the whole process. …

This is a story about diversity and inclusion efforts in a beautiful tribe of diverse passionate people who build innovative products to bring a positive impact in the lives of our colleagues at ING and beyond. It’s about us — who come from different nationalities, cultures, backgrounds having different expertise and super powers, speaking different languages and having many more diverse characteristics.

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“Our data driven thinking, passion to innovate, attitude of getting things done, and more than everything, our zeal to continuously learn and improve as individuals and as a team, is what unites and makes us a part of the WBAA tribe. …

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A disruptive open-source python package developed by ING WB Advanced Analytics enabling the monitoring of ML model input data and predictions over time.

ING WB Advanced Analytics (WBAA) is a tribe that builds 10x data-driven products. Within our tribe, the CoreAlgos-Research squad works on developing data science models and analytics tooling to be leveraged for our products while at the same time, to benefit the wider data science community.

Max Baak — Data Science Lead and Tomas Sostak — Data Scientist at WBAA, have worked in filling a significant gap regarding the monitoring and from there improvement of the performance of machine learning (ML) models that are running in production. …

Check out our plan to deal with the quarantine! Practical tips to keep business going and retain team cohesion while having fun.

On the 11th of March, the World Health Organization (WHO) declared the novel COVID-19 outbreak a pandemic. With the new virus creeping across the globe, organizations, teams, and managers need to be well-prepared and take the necessary measures before the storm hits. ING Wholesale Banking Advanced Analytics (WBAA) initiated these measures right on time in order to protect the well-being of our team members while ensuring business continuity.

Bolke de Bruin announced a full plan for WBAA to tackle the Coronavirus crisis. He said regarding his decision and strategy onwards:

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VP of Engineering ING WBAA

“ING asked us to prepare for a prolonged work-from-home scenario. With the team, we sat down to really think out what matters when such a scenario kicks in. It’s not just “hey, go home and it’s business as usual”. It became apparent that it was important to address anxiety, the needs of people without a strong social network locally and how to keep having fun. So when ING took the decision to execute the work-from-home scenario we were able to communicate very clearly what we expected from the Tribe and what they could expect from us. I am extremely proud and humbled by the fact that the Tribe responded so decisively: we had 20 volunteers within an hour or two, people are constantly sharing how they deal with issues and people are flexible and reaching out towards each other while adjusting to the new current”.

ING announced the spin out of WB Advanced Analytics portfolio tool Katana to become an independent fintech company. What does it take to transform a product into a company? Frank Derks — Global Tribe Lead of ING WB Advanced Analytics and Santiago Braje — CEO of Katana Labs provide the answers.

Today ING announced the spin out of Katana, a cutting-edge Advanced Analytics tool that helps traders and investors make faster and sharper decisions when trading bonds. This is an important milestone for ING WB Advanced Analytics (WBAA) and Katana Labs proving that WBAA can enable the creative journey of a high performing team all the way from an Artificial Intelligence (AI) idea to an independently funded fintech.

But what does it take to make this happen? How does ING leverage Advanced Analytics capabilities to create successful products and companies that can benefit both ING and the market? …

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ING WB Advanced Analytics at Sibos 2019

How would the world be if we were able to make well-informed decisions, if we could evaluate all possibilities and have a universal view before taking the next step? What if our pensions, investments and future were based on this universal thought process?

Androniki Menelaou — Senior Data Scientist at ING WB Advanced Analytics and Product Owner of Katana Lens attempted to answer these questions during her thoughtful presentation at Sibos 2019 which took place for the first time in London, as the capital of a booming tech and financial ecosystem.

Sibos is a renowned conference that connects business thought leaders and decision makers to discuss on the latest innovations and future of finance. This year’s theme, “thriving in a hyper-connected world”, explored the opportunities and challenges that arise from a data-driven era. An era where human and machine competences are leveraged and need to co-exist to bring out the best value propositions for organisations. …

The data science and developers community is well-aware of the global PyData network and its advanced knowledge sharing impact. PyData, brings together the data science and scientific computing communities to learn and discuss on the best methods, novel practices, and emerging trends in big data analytics, processing, and visualisation.

During this year’s PyData in Amsterdam, ING WB Advanced Analytics shared knowledge with the international open source community on two different topics: “Uncertainties on ML Predictions” and “Genetic Regex”.

“Uncertainties on Machine Learning Predictions”

To reach intelligent decisions it is essential to be able to provide uncertainties on machine learning (ML) predictions. …

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WBAA’s Krzysztof Adamski and Rob Keevil at the biggest Kubernetes and Cloud Native technologies conference.

KubeCon+CloudNativeCon is a vendor-neutral conference gathering the attention of world-class developers, IT-professionals and C-suite technology and business leaders across the globe.

This year more than six thousands of experts gathered in Barcelona, Spain to share their knowledge, focus on innovation, and discuss on the most novel trends in container-orchestration and micro-services architectures, using open-source systems like Kubernetes, Prometheus and more.

In this context, Krzysztof Adamski and Rob Keevil gave an inspiring presentation in “How to make Data Science in a Box possible”, by showing to the audience the journey and architectural edifice behind WBAA’s Data Analytics Platform (DAP) — the project that aims to democratize Data, Analytics and Machine Learning for the whole ING. …

Yeshwanth Kumar sharing knowledge in “Building a CQRS + Event Sourcing Micro-Service with Akka”

WB Advanced Analytics (WBAA) was present at the Scala Central Meet-up which took place at our ING office in London. The team was represented by Yeshwanth Kumar, Data Engineer currently working in the development of WBAA’s Data Analytics Platform. In a full house, Yeshwanth shared knowledge in how to use Akka — a free open-source toolkit for building highly concurrent event-driven applications for Scala and Java.

Scala as a general purpose programming language that combines functional and object-oriented code, can be applied in so many different ways as many are the programmers in the community behind it. …

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One of our talented data scientists, Rafah El-Khatib represented ING WB Advanced Analytics during this year’s Data Science Festival. London’s Data Science Festival is successfully organised for three years now, gathering more than two thousands data enthusiasts and top tech companies. Rafah’s talk was based on Feature Selection Best Practices — LOFO, and a Survey of Key Feature Importance Packages

In a previous blog we talked on the Leave-One-Feature-Out Importance, a promising open source contribution made by WB Advanced Analytics Data Scientists: Ahmet Erdem, Rafah El-Khatib, Eva van Weel and Stephane Collot.

The idea for the feature importance python package was initiated by Ahmet Erdem, during WBAA’s Data Science Focus Sessions, where our data scientists can exchange insights on their projects’ progress or the technical struggles they might be experiencing, and from there, come up with smart solutions. …


Nicole Mpozika

Communications @ ING WB Advanced Analytics

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