Coronavirus Pandemic and Financial Soundness of Fidelity Bank Ghana Limited: Evidence from 2019 and 2020 Financials

Abstract

The Wuhan COVID19 disease in China turned a worldwide pandemic in 2020. It disrupted normal ways of life; caused collateral damage across the globe; and altered traditional banking model due to multiple lockdowns, movement restrictions, border closures, and other protocols put in place by governments to control the spread of the disease. Ghana was not an exception to all of these challenges posed by COVID-19 pandemic. Riding on the new-normal theoretical underpin, this study empirically quantified the effect of COVID19 on financial soundness of Fidelity Bank Ghana Limited. CAMEL indicators measured financial soundness. Using secondary data analysis technique, one-way analysis of variance (ANOVA), descriptive statistics, and SPSS software, the research established that: (i) the bank performed better in all the aforementioned indicators in 2020 than in 2019; and (ii) there was no statistical difference between the performance of the bank in 2019 and 2020 (except in liquidity). Theoretically, the new normal theory proved to be relevant in this study as the bank performed better in 2020 (when banking halls were mostly closed) than in 2019 due to its increased investments in financial technology (FinTech), digital technology (DigTech), and big-data technology (BigTech). The study offered far-reaching results-backed recommendations.

Corporate Governance and Banks’ Capital Adequacy in Gambia: The Moderating Impact of Politics

“…The Shapiro-Wilk test of normality was carried out with the aid of statistical package for social sciences (SPSS); and the results as shown in Table 2 indicate that all the variables passed this basic assumption for parametric research. The results of the normality test on all the variables show that their significance values are greater than 0.05; hence, this show that they are drawn from normal distribution (Wahua & Ezeilo, 2021;Wahua, Mkombo, Okai & Acquah-Yalley, 2022). Table 3 shows that the Model used in this study is a good fit for the analyses carried out (F = 25.36; Sig = 0.001); and that it accounted for 92% and 88% of the variations that occurred in capital adequacy when error terms is not accounted for, and when error was accounted for respectively.…”