Implementing artificial intelligence in corporate and investment banking: Use cases, infrastructure and change management strategies
Abstract
Leveraging artificial intelligence (AI) in daily banking processes to excite nonretail banking customers, support revenue generation, (semi-)automate fundamental banking processes and/or better protect a corporate and investment bank from risks connected to its nonretail banking business are the focus of this paper. This paper provides empirical examples from its authors’ practical implementation experience in the two largest Austria-based international banking groups. The paper discusses identifying and building the most promising AI use cases for nonretail banking, setting up the IT infrastructure required to successfully run AI use cases in a compliant way and preparing the organisation and its employees to deal with this new technology ethically and in compliance with regulations. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
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Author's Biography
Martin Giesswein is a faculty member of the WU Executive Academy, teaching courses on artificial intelligence (AI), digital economics and digital humanist leadership. In 2025, he was awarded first prize in the ‘Digital Humanism in Practice’ award. He also works as AI ethics adviser in the European DRAIGON project. He is the author and editor of several books, and his latest book explores AI scenarios projected through the year 2040. Martin Giesswein is one of the co-initiators of DigitalCity.Wien, the 10-year cooperation between the digital economy and the City of Vienna. He was previously a CEO and general manager in the IT industry.
Vedad Sehanovic is a product owner in the AI Center of Excellence at Raiffeisen Bank International in Vienna. He takes end-to-end product responsibility for the development and implementation of machine learning and generative artificial intelligence solutions, with a focus on corporate banking and risk management. His professional background includes roles in data science and credit risk modelling. He holds degrees in economics and quantitative finance.
Stephan Waniek is a business owner within the Group CIB Business Transformation unit at Raiffeisen Bank International (RBI) in Vienna. He coordinates and prioritises the ideation, implementation and operation of end-to-end generative artificial intelligence use cases within the Corporate & Investment Banking Division of RBI Group. His professional background includes roles in relationship management, product sales and business development. He holds an MBA degree from Vienna University of Economics and Business Administration.
Thomas Werth is leading the Data & AI Tribe on the IT side in Erste Group. He is responsible for business intelligence and analytical/artificial intelligence platforms, data management and reporting solutions and data science. He has successfully led large-scale IT transformations and developed a comprehensive understanding of data strategies and data governance. Prior to joining Erste Group, Thomas held several management positions in IT consulting, mainly in the financial services industry. He holds degrees in economics and IT.
