The effect of corporate governance, risk and ESGtowards bank performance: does Fintech matter?
This thesis examines how corporate governance, risk, and ESG affect bank performance and providesa novel theoretical framework for incorporating fintech into the relationship in the context of EU banks.The banking sector is transitioning to become increasingly digitised. Corporate governance, risk, andESG management in banking are changing, and fintech involvement is currently popular on the market.First, the study identifies a positive significant relationship between corporate governance and bankperformance. It demonstrates how improved corporate governance can boost bank performance andhow, in accordance with Agency Theory, improved governance will prevent the agency problem inbanks. Additionally, the results suggested that fintech acts as a moderator to enhance the relationship.Second, the study find that bank risk negatively affects bank performance, suggesting that performancewould decrease as risk rises. Furthermore, it was demonstrated that fintech has a moderating impact onthe relationship between risk and bank performance. It demonstrates how fintech intervention helpsbanks improve risk management by minimising and controlling the risk, in line with the ConsumerTheory's suggestion that an initiative like fintech or the enhancement of existing products and services,improvement of operations to minimise risk, improved performance in banks. Third, it has beendiscovered that ESG has a positive impact on bank performance, suggesting that implementing morerobust ESG practises will improve bank performance. According to the Theory of Stakeholders, it isthe obligation of a bank to add value for its stakeholders, and one way to do this is through ESG.Additionally, it was concluded that fintech mediates the link between ESG and bank performance. Thisindicates that banks with higher fintech engagement have better ESG results, which has indirectlyboosted performance.Secondary data for the analysis was gathered from a variety of sources, including Orbis Bank Focus,Refinitiv data stream, annual financial reports, the World Bank's Development Indicators, WorldwideGovernance Indicators, and CrunchBase (CB). The analysis included both static and dynamic paneldata approaches, including the fundamental Partial Least Square-Structural Equation Model (PLSSEM), the second generation of data analysis, and Ordinary Least Square (OLS) for robustness. Thisstudy will be useful to a wide range of stakeholders, including investors and managers, lenders, andpolicymakers in the EU region and around the world. It will also provide academicians and researcherswith future research directions in the banking and fintech fields.
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