TECHNOLOGICAL AND REGULATORY ENVIRONMENTAL FACTORS ANDFINANCIAL PERFORMANCE OF GUARANTY TRUST HOLDING COMPANYPLC, 2013–2023

Abstract

This study examined the relationship between technological and regulatory environmental
factors and the financial performance of Guaranty Trust Holding Company Plc (GTCO) from
2013 to 2023. The study was reframed as an exploratory single-case time-series analysis
because the empirical evidence was drawn from one financial institution rather than the
entire Nigerian banking industry. Therefore, the findings are specific to GTCO Plc and
should not be generalised to all deposit money banks in Nigeria. Using an ex post facto
research design, the study relied on secondary annual data obtained from GTCO annual
reports, Central Bank of Nigeria publications, and Nigeria Inter-Bank Settlement System
data. Financial performance was measured using return on assets (ROA), while the
explanatory variables included IT investment ratio, digital transaction value, cash reserve
ratio (CRR), and capital adequacy ratio (CAR). The data were analysed using descriptive
statistics, correlation analysis, and multiple regression. The findings showed that the
technological variables had positive relationships with ROA in the reported exploratory
model. However, the regulatory variables produced statistically insignificant results at the
5% level. Specifically, CRR showed a negative but statistically insignificant relationship with
ROA, while CAR showed a positive but statistically insignificant relationship with ROA.
These findings suggest that technological factors may be associated with GTCO’s financial
performance, but the evidence is not sufficient to establish causality. The results should be
interpreted cautiously due to the small number of annual observations, the single-bank casestudy design, and the use of national-level digital transaction data as a proxy for
technological environment. The study concludes that technological and regulatory conditions
may be relevant to bank performance, but stronger evidence would require a larger dataset,
such as quarterly observations or panel data covering several Nigerian banks.