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Wholesale Banking

Empowering with advanced analytics

Applying advanced analytics (AA) techniques to enormous and varied data sets, we can develop artificial intelligence (AI) that identifies patterns and makes predictions. ING is leveraging the power of artificial intelligence in banking. At ING Wholesale Banking Advanced Analytics (WBAA), we build powerful and innovative software products that use advanced analytics to deliver insights to our clients. We aim at improving your decision-making, optimising your business processes and enabling your delivery.

What does ING Wholesale Banking Advanced Analytics do?

The ING Wholesale Banking Advanced Analytics team (aka WBAA), often gets requests for information on who we are and what we do as a team. We love this interaction but want to provide information that is consistent, complete, easy to consume and share. Read our blog to learn more about us.

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Other articles you may find relevant

ING spins out Katana to become a fintech — Transforming an advanced analytics product to a company

ING announced the spin out of WBAA 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.

An experimentation day at WBAA

At ING WBAA we know that experimentation lies at the heart of data science and data engineering. To come up with innovative machine learning solutions and creative use cases you need to dedicate time to research and experimentation. Learn more on how we leverage the value of experiments.

WBAA – Our efforts towards diversity and inclusion

This is a story about diversity and inclusion efforts in our beautiful ING tribe. A tribe of diverse passionate people who build innovative products to bring a positive impact in the lives of our colleagues at ING and beyond.

WBAA non-financial risk squad

To leverage AI technological advancements, while adequately mitigating the associated risks, WBAA has set up a non-financial risk (NFR) team of experts from different disciplines. Our NFR team works towards a holistic approach to data security, risk management and legal topics around building data-driven algorithmic products

Holmes – Making Information Sharing easy!

Holmes is a tool for front office staff developed by Wholesale Banking Advanced Analytics to help search easily through all ING credit packs and ING market research. It makes information sharing easier and it helps serve customers better. Currently it's being rolled out to the first users globally. How does Holmes work? See this one-minute video.

Harnessing data science for social good

It is commonly accepted that data scientists are the smartest people in every field and a hot commodity for every industry. However, high compensation rates, ready access data without onerous red tape and advanced computing environments, are not enough to keep them engaged.

The Data Analytics platform

ING WBAA has developed the Data Analytics Platform (DAP) aiming to democratise data, analytics and machine learning for the whole ING. Making the data accessible and understood within the corporation can accelerate decision-making and unleash real-time opportunities.

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Research by Wholesale Banking Advanced Analytics

We are proud to work amongst top-talent. Many of our colleagues have accomplished significant research contributions in academia during their past or current roles. This is a knowledge sharing repository to be leveraged by the wider community including topics relevant to Data Science, Software Engineering, and UX Design.

Internship theses at Wholesale Banking Advanced Analytics

Wholesale Banking Advanced Analytics is known as a knowledge sharing and experimentation hub within ING. Nurturing research and incubating innovative ideas is in the core of our DNA. Every year we offer MSc students the opportunity to apply and develop their skills in real-world business problems by leveraging our Advanced Analytics capabilities.

Women in Data science/STEM

WBAA women data scientists and engineers share their perspectives regarding the opportunities offered in the data science/STEM arena but also regarding the challenges that have to be addressed in order to narrow the gender gap.

How we innovate by embracing failure with the Sword of enlightenment

When experiments are at the core of innovation, we shouldn’t be afraid to fail, we should be afraid of not trying. At WBAA we try to create the right working culture, to embrace failure by creating a safe space where people dare to fail and where we share our failures and learnings as much as possible.

How to make “Data science in a box” possible

An inspiring presentation during the biggest Kubernetes and Cloud Native technologies conference, on the journey and architectural edifice behind WBAA’s Data Analytics Platform (DAP). Learn more about DAP’s architectural vision, emphasizing on the compute layer, the storage and its unique security model.

Facilitating data discovery with Apache Atlas and Amundsen

Read how we implemented the concept of the data discovery service “Amundsen” within the Data Analytics Platform to support our data democratisation efforts.