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CEO BIAS, MORAL HAZARD AND ADVERSE SELECTION: A LITERATURE REVIEW ON RISK DYNAMICS IN DIGITAL BANKING IN INDONESIA, WITH A PITCHING RESEARCH APPROACH Mardjono, Amerta; Maupa, Haris; Setyawan, Ignatius Roni
International Journal of Application on Economics and Business Vol. 3 No. 3 (2025): Agustus 2025
Publisher : Graduate Program of Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/ijaeb.v3i3.1483-1494

Abstract

This paper investigates the impact of CEO bias, specifically overconfidence, on the financial sustainability of digital banks and the relationship between these risks. To organize prospective assessment into CEO decision-making within the digital banking industry, the evaluation employs the pitching research methodology (Faff, 2015 and 2024).This study compares and contrasts an array of existing theories and prior academic findings published between 1970 and 2024, categorized into key components such as CEO bias, moral hazard, adverse selection, and fintech solutions, and how each of these interacts with financial sustainability and governance in digital banking. This study indicates that CEO overconfidence plays a critical role in influencing the risk management practices of digital banks, particularly in the context of moral hazard and adverse selection. While fintech innovations such as big data and machine learning have improved banks' ability to assess borrower risk, they cannot fully mitigate the risks posed by information asymmetry, especially when CEO bias skews decision-making. This paper is expected to fill part of a gap in linking the studies of how CEO bias impacts the financial sustainability of digital banks, exposing moral hazard and adverse selection. It provides a practical approach to examining the moderating influence of CEO bias on moral hazard and adverse selection in Indonesia’s digital banking sector, where fintech tools are heavily relied upon. While previous research has focused on the technical risks of fintech solutions, this paper explores how behavioral biases, particularly overconfidence, impact digital banking sustainability.