Title: Artificial intelligence (AI) and financial modeling in Nigeria
Authors: Ogechukwuka Chegwe, Ayewumi Ezonfade Fredrick, Ehiedu, Victor Chukwunweike, LL.B
Volume: 9
Issue: 3
Pages: 1-9
Publication Date: 2025/03/28
Abstract:
One of the most powerful pillars of any economy is the banking sector. Any economy's ability to develop is mostly dependent on banks and other financial institutions. Despite its lengthy history, the banking industry is rapidly embracing modern technology and is one of the main adopters of modern scientific instruments and techniques. This study investigate the effect of artificial intelligence on financial modeling in Nigeria. Specifically, the dependent variables; Financial modeling measured by Return on Equity (ROE) while the independent variables; Artificial intelligence was measured by Volume of Point of Sales (VPOS), Volume of Internet Transfer (VINT) and Volume of Mobile Transfer (VMOT). The study covered a time period of thirteen (13) years spanning from 2010 to 2022. The study adopted "ex-post facto" research design with the help of Augmented Dickey-Fuller (ADF), Correlation test and Ordinary Least Square to analyze the data sourced from CBN statistical bulletin and Federal reserve economic data. The statistical package used in this study is Econometric Views version 10. The results of the OLS test reveals that LogPOS (r = 0.095171>0.05), and LogINT (r = 0.070423>0.05) have a positive significant effect on return on equity (ROE) except LogMOT (r =0.022372<0.05), that have a positive significant relationships with ROE. Thus, LogMOT coefficient is less than the 5% significant level. The study recommends that financial institutions ought to give data privacy security top priority while making sure the integrity of the internal audit process is not compromised.