Leveraging Experience-Based Knowledge for Social Impact Analysis of Research and Development Projects in Banking

Abstract

Banking projects are diverse and go beyond classic financial products and include advanced customer service tools, analytics, and AI. Large financial institutions are leaders of technological change, increasingly creating internal innovation labs that independently conduct research and development work using specialized teams, which helps them achieve a positive social impact and build a sustainable and stable competitive advantage in the long term, thanks to the rapid adaptation of solutions to changing market requirements. The issues relating to social impact analysis and assessment of R&D projects in banking are new, and a research gap can be noticed in this field. Publications on implementing such projects are mainly focused on their products and the time of delivering innovations to the market, not on the methods of managing project knowledge necessary for social impact analysis processes. There is, therefore, a need to build theoretical and methodological foundations for improving management processes and using experience-based knowledge in this area. This paper aims to propose a model inspired by case-based reasoning (CBR) and generative AI. The model can be helpful in supporting the solution of decision-making problems using historical knowledge, as well as considering the current specificity of projects and their environment. The presentation of the model is supplemented with examples concerning the social impact analysis of R&D projects in the banking sector, which prove that its use can improve the use of experience from such projects.