AI is at the core of ING’s business. It is a data-driven enterprise, with analytics skills as a top strategic priority, and is investing in AI, big data, and analytics to improve business processes such as balance forecasting, fraud detection, and customer-relation management. In innovation, AI plays a key role in going beyond banking and redefining traditional banking services in fintech accelerator programs. The company’s working on a large scale with big data technologies to set up a data lake where all data flows from the bank come together. Once stored in stating or streaming form, this massive amount of data can be used for traditional and new innovative use cases.
Get an overview of the journey that a large bank as made from traditional IT toward in-house development with modern open source frameworks and Agile methodologies. Bas Geerdink examines an important part of ING’s architecture, giving examples of interesting data-driven use cases, and shares some results from running the models in production. Along the way, you’ll discover the lessons ING’s Innovation Department learned about the way working and deployment mechanisms create a successful data-driven team and be inspired by a working architecture of the data lake and innovative use cases at the bank, such as look ahead and instant lending, where AI plays a crucial role.
Bas Geerdink is an independent technology lead, focusing on AI and big data. He has worked in several industries on state-of-the-art data platforms and streaming analytics solutions, in the cloud and on prem. Bas has a background in software development, design, and architecture with broad technical experience from C++ to Prolog to Scala. His academic background is in artificial intelligence and informatics. Bas’s research on reference architectures for big data solutions was published at the IEEE conference ICITST 2013. He occasionally teaches programming courses and is a regular speaker at conferences and informal meetings.
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