The Flow in the Funnel: Modeling Organizational and Individual Decision-Making for Designing Financial AI-Based Systems

Nowadays, the current application of artificial intelligence (AI) to financial context is opening a new field of study, named financial intelligence, in which the implementation of AI-based solutions as financial brain aims at assisting in complex decision-making (DM) processes as wealth and risk management, financial security, financial consulting, and blockchain. For venture capitalist organizations (VCOs), this aspect becomes even more critical, since different actors (shareholders, bondholders, management, suppliers, customers) with different DM behaviors are involved. One last layer of complexity is the potential variation of behaviors performed by managers even in presence of fixed organizational goals. The aim of this study is twofold: a general analysis of the debate on implementing AI in DM processes is introduced, and a proposal for modeling financial AI-based services is presented. A set of qualitative methods based on the application of cultural psychology is presented for modeling financial DM processes of all actors involved in the process, machines as well as individuals and organizations. The integration of some design thinking techniques with strategic organizational counseling supports the modeling of a hierarchy of selective criteria of fund-seekers and the creation of an innovative value proposition accordingly with goals of VCOs to be represented and supported in AI-based systems. Implications suggest that human/AI integration in the field can be implemented by developing systems where AI can be conceived in two distinct functions: (a) automation: treating Big Data from the market defined by management of VCO; and (b) support: creating alert systems that are coherent with ordered weighted decisional criteria of VCO.

Automated summary

The application of artificial intelligence in the financial field is creating a new area of study called financial intelligence, aimed at assisting in complex decision-making processes. This is particularly crucial for venture capitalist organizations where different actors with varying decision-making behaviors are involved. This study proposes a modeling approach for financial AI-based services and suggests the integration of human/AI systems for better decision-making support.