The spread of information technology and the digitalization of financial services raise a range of theoretical questions as the structures of the banking industry undergo change. This change has intensified with the impact of the COVID-19 pandemic which is already being observed. The purpose of this study is therefore threefold: (1) to analyze the impact of IT and the digitalization of financial services on the strategy and functioning of the pre-COVID-19 banking sector; (2) to study the challenges banks are facing in the COVID era in managing the crisis, and (3) to highlight post-COVID stakes.  This study shows, on the one hand, that the crisis confirms the need for banks to combine physical proximity and digital offer, and on the other hand, that digitalization could be the solution for banks to consistently mitigate risks. Through this digital transformation and their ability to re-invent themselves, the banks would guard against potential similar crises. By adopting a more digitized and open behavior, they would be immune to such crises because they would have appropriate strategic plans, as they would be better equipped to counter the threats and better prepared to transform them into opportunities. JEL Classification Codes: B26, B41, G21, G32, O32.

This paper explores the determinants of access to finance for small and medium enterprises (SMEs) in the context of asymmetric information. Our sample consisted of 250 Tunisian SMEs financed by Arab International Bank of Tunisia, broken down by sector of activity, size and region. The results of multiple linear regressions showed that size, interest rate, trade credits and profitability have a significant influence on the total volume of credit. The bank considers the size of commercial and industrial SMEs, and those located in the District of Tunis and the Center-East, as a positive signal when considering a loan. The bank also considers high interest rates when considering loans to commercial SMEs, microenterprises and SMEs located in the District of Tunis. As far as innovation is concerned, the results showed that service SMEs, micro-enterprises and SMEs located in the District of Tunis and in the Center-East, find it difficult to get a credit. It is interesting to note that the bank neglects liquidity issues and the net worth of the SME in its financing decision, which contradicts the theoretical assumptions. Finally, we conclude that bank's financing of Tunisian SMEs is characterized by conditions dominated by the problem of asymmetric information.

The paper presents the use of the difference GMM, the system GMM and the Panel VAR for the purpose of determining the critical determinants of non-performing loans. The aim of the paper is to point out the factors that explain the volatility of NPLs in a time of crisis. The study focused on a sample of 18 Tunisian banks observed during the period 2008-2018. The paper seeks to identify the impact of crucial macro, microeconomic and governance variables on the NPLs. The results suggest that the deterioration in asset quality can be attributed to both macroeconomic and bank-specific factors. The liquidity risk has a positive and significant correlation with the NPLs of Tunisian banks. The variable "Revolution" presents a positive though not significant relationship with these. Also, the results emphasize the strength of macrofinancial feedback loops in Tunisia. As for the effect of the positive shock of the revolution on the NPL level, we note that it is significant and negative. The decomposition of the sample into two sub-samples: pre-revolution period and post-revolution period allowed showing that the ROA and the ownership structure affect negatively and significantly the NPLs of the banks in the two periods, while the capital affects them positively. It appears that bank-specific factors explain well the volatility of NPLs, especially in the post-revolution period. Finally, by a descriptive study, we have shown that the COVID-19 crisis explains the volatility of the NPLs of Tunisian banks.

The aim of this paper is to propose an appropriate method that could assist decision-makers in the finance department responsible for hedging against the exchange risk yielding a better strategy to shield the company from the undesired scenarios of loss. Our research interrogation related to an intelligent solution devoted to the minimization of the currency risk incurred by our Tunisian studied Holding when trading on the foreign exchange market. The study focused on the four most involved currencies in the Tunisian and Foreign trading market: USD, EUR, GBP, and JPY. Our sampling period runs from January 03, 2011 to June 30, 2021. First, the results suggest that the key interest rate and the foreign exchange reserves are most determinant variables compared to the other variables. Second, we present a feasible procedure to hedge against currency risk consisting of five steps, through a developed Artificial Intelligence based program, a correlation analysis and the Temporal Causality Model. Finally, we create our different hedging scenarios and the desired exchange rate is forecasted for a period (from 1 month to 12 months). Based on the forecasted exchange rate values, the studied Holding is able to conclude the most advantageous forward hedging contract by choosing the term of the contract at which the exchange rate level is the most profitable rate according to its position in the market.

This study examines the relationship between Information Technology investment and the profitability of Tunisian banks, via static and dynamic panel regression models. Our study focused on 15 Tunisian banks for 19 years (2001-2019). To assess the profitability of these banks, three measures were used: two traditional accounting ratios and net interest margin. Our research has shown the importance of the role played by IT in Tunisian banks since IT investments improve their profitability. This finding contradicts the “Productivity Paradox” that high IT investments are not associated with better performance. Indeed, Tunisian banks are acting on their size to boost their performance, and the more the banks take the risk by granting more loans, the more profitable they are by increasing their Return on Assets. Finally, public banks are more profitable than private banks when considering their net interest margin. JEL Classification Codes: B21, C58, G21, G32, O32.