QUANTIFYING THE RISK ON BANKS RETURNS ARISING FROM FINANCIAL TECHNOLOGY ADOPTION
The fact that FinTechs now performs functions which were previously the exclusive reserve of bank financial institutions such a loan extension, fund raising, assets management, payments, credit management, etc. is not only risky to their profitability and continual existence but also to the economy as a whole. With it’s over surging penetration impact in the financial system, the question on how it will affect bank profitability and continual existence has not been empirically addressed.
The FinTechs revolution accelerated with the new regulations enacted in the wake of the 2008 financial crisis. After the 2008 financial crisis, heavy regulations were imposed on the banks, making it much more expensive to extend financial services to their customers. Traditional banks are not only vulnerable to FinTechs penetration in the area of financial service extension but also in assessing the right workforce. The concern on what will be the state of the future financial institutions therefore becomes a researchable issue. Should FinTechs replace the banking sectors or should they collaborate? believes it is not likely that it will replace the conventional banking because, according to them, although FinTechs operations can reduce banks’ profitability, many FinTechs companies actually depends on existing bank accounts. Whatever be the condition, the fact remains that there are potential tradeoffs that is capable of generating both risk and prospects for the bank and the public.
The rapid global technology revolution has raised serious concerns on what could be its long run impact on banks, especially with its attendant technological unemployment. The on-going debate in literature whether and to what degree financial technology adoption will emit risk to bank profitability is examined in this study. The trade-off analysis and a family of symmetric and asymmetric GARCH approach to Value-at-Risk (VaR-GARCH) based on the camel and value at risk theoretical framework were used to determine potential risk and estimate the conditional variance of bank returns in a panel of thirty-four African countries for the period 2002-2018. The Kupiec log likelihood ratio test and mean relative scaled bias used to evaluate the models’ accuracy and efficiency levels respectively found that the best model to estimate the conditional variance of bank returns is the exponential GARCH (1, 1) with student-t distribution. The worse expected loss on banks’ return due to FinTechs adoption will not exceed 3.01% at 95% confidence interval. Therefore, with a higher FinTechs’ risk/standard-deviations than that of banks’ return and a high VaR value of bank returns, it implies that aside banks, FinTechs also emits risks to other sectors, therefore this study recommends that African economies will benefit from FinTechs diffusion through improved financial service delivery only when a substantial level of collaboration between bank financial institutions and FinTechs companies is reached.
Author-Tochukwu Timothy Okoli and Devi Datt Tewari
Journal of Internet Banking and Commerce