Pa ge 1 Pa ge 63 American Journal of Smart Technology and Solutions (AJSTS) Impact of Financial Technology (FinTech) on Accounting Efficiency and Supply Chain Performance in Nigeria’s Logistics Sector Akanbi, Taibat Adenike1, Gbadegesin Adeolu Emmanuel2* Volume 4 Issue 2, Year 2025 ISSN: 2837-0295 (Online) DOI: https://doi.org/10.54536/ajsts.v4i2.5819 https://journals.e-palli.com/home/index.php/ajsts Article Information ABSTRACT Received: July 30, 2025 Accepted: September 01, 2025 Published: September 19, 2025 Using annual time-series data between 2000 and 2024, the study follows an Autoregressive Distributed Lag (ARDL) modeling strategy to estimate both short-run dynamics and long- run relationships between Financial Technology (FinTech), Accounting Efficiency and Supply Chain Performance within Logistics Sector in Nigeria. The value of electronic financial transactions is used as a proxy of FinTech adoption, financial reporting quality indices as a proxy of accounting efficiency, and composite logistics indicators as a proxy of supply chain performance. Descriptive analysis shows that there is a lot of variation in FinTech uptake but not much variation in accounting practices. Cointegration of the variables is supported by the ARDL bounds test. The long-run estimates show that the efficiency of FinTech and accounting have a statistically significant positive impact on logistics performance, with coefficients of 0.42 and 0.35, respectively. In the short-run, the efficiency gains of accounting have an immediate effect, and the benefits of FinTech are felt in a more long-term way. The error correction term implies a high rate of convergence to equilibrium (adjustment speed of 45%). Model robustness is validated by diagnostic tests. The results suggest that FinTech usage and effective financial management are mutually supportive factors of supply chain efficiency in Nigeria. Based on this, companies and policy makers ought to intensify the use of digital financial instruments and enhance accounting functions to promote robust and competitive logistics systems. Keywords Accounting Efficiency, FinTech, Logistics, Supply Chain Finance, Supply Chain Performance 1 Department of Accounting, Faculty of Management Sciences, Ladoke Akintola University of Technology Ogbomoso, Nigeria 2 Department of Transport Management, LAUTECH Open and Distance Learning, Nigeria * Corresponding author’s e-mail: aegbadegesin@lautech.edu.ng INTRODUCTION Financial technology (FinTech) is changing how companies handle payments, financing, and financial records by making them faster, more error-free, and more accessible (Lee & Shin, 2018). FinTech solutions like mobile money, supply chain finance, and digital invoicing enhance the efficiency of operations in logistics by automating payments, increasing transparency, and cutting lead times (Liu et al., 2025). Such technologies require robust accounting systems that can process digital transactions quickly and accurately (Ibrahim & Yusuf, 2025). Accounting efficiency - which is characterized by the pace and accuracy of financial reporting - facilitates the successful application of FinTech tools by providing transparent and coherent documentation of both internal and external logistics coordination (Chukwuka & Eze, 2018). Collectively, FinTech and accounting efficiency are key drivers of supply chain performance, indicating responsiveness, cost-effectiveness, and reliability in logistics operations. When logistics companies implement FinTech platforms, their performance is usually determined by the extent to which these tools can be used to enhance delivery, minimize the time lag in transactions, and help to manage inventory (Zhang et al., 2024). Despite this, the logistics sector in Nigeria is still grappling with efficiency problems with the country ranking 110th in the World Bank Logistics Performance Index in 2018 and an overall score of 2.53, which indicates poorly developed supply chain infrastructure and processes (World Bank, 2018). Although the use of FinTech in Nigeria has been growing, many logistics firms still experience delays in reconciliation, lack of transparency in the history of transactions, and ineffective integration of digital tools and accounting systems (Osei-Tutu & Agyemang, 2023). Small and medium logistics firms are especially unable to adopt extensive digital solutions, and many of them rely on fragmented or manual accounting (Egwuonwu et al., 2023). Furthermore, the long-run effects of FinTech and accounting efficiency on the performance of logistics in Nigeria have not been sufficiently tested by econometric models. Most of the literature available focuses on financial innovation or operational performance separately. The paper addresses this research gap by examining the connection between FinTech and accounting efficiency in influencing supply chain performance in Nigeria using recent time-series data and ARDL modeling. Hypotheses of the Study Two hypotheses were tested in this study: H01: FinTech adoption has no positive impact on accounting efficiency; H02: FinTech adoption has no positive impact on supply chain performance. LITERATURE REVIEW FinTech refers to the financial technological developments that promote the smooth, safe, and efficient financial transactions. It encompasses mobile payments, digital lending, blockchain, and other IT-enabled financial Pa ge 64 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025 services (Arnaut & Bećirović, 2023; Suryono et al., 2020). FinTech has revolutionized the banking industry in the world, making it cheaper and more accessible (Martinčević et al., 2020; Elsaid, 2023). The rapid growth of FinTech in sub-Saharan Africa and in Nigeria, in particular, is explained by the high saturation of mobile phones and unmet financial needs (Giglio, 2021; Kola- Oyeneyin et al., 2021). Nigeria has developed one of the largest FinTech industries on the continent, facilitating digital payments and credit to millions of people (Koffi, 2016; Kyari & Akinwale, 2020). In 2023, 2.24 quadrillion in total electronic payments was facilitated in Nigeria, which means that digital finance is highly utilized. There is a tendency to relate the emergence of FinTech to improved firm performance. To illustrate, Okoye et al. (2024) found that the use of FinTech positively and significantly contributed to the development of Nigerian SMEs and the profitability of banks due to an extended customer base. FinTech also enhances financial inclusion and flexibility, which have an indirect positive impact on supply chains (Siano et al., 2020; Asamoah & Owusu- Agyei, 2020). In a complex supply chain, efficient accounting systems are essential to organizational performance (Hakkak & Ghodsi, 2015). Accounting efficiency suggests prompt and correct financial data and efficient billing, payment, and reporting procedures. These processes have been found to be enhanced by FinTech tools. Harsono and Suprapti (2024) emphasize that FinTech-powered solutions (e.g. mobile banking, e-invoicing) can transform financial efficiency by making operations simpler, cutting costs, and improving competitiveness. Online invoicing and payment systems eliminate paperwork and mistakes, enabling companies to spend more time on the actual logistics work. Previous research observes that implementing computerized accounting systems and cloud-based financial tools can enhance the SMEs record-keeping and financial decision-making remarkably (Akanbi et al., 2022; Godgift-David et al., 2018). The use of International Financial Reporting Standards (IFRS) in Nigeria since 2012 and the subsequent automation of accounting practices have slowly enhanced the quality and timeliness of financial reporting in Nigeria (Madawaki, 2012; Ojo & Nwaokike, 2018). Good auditing and reporting standards are associated with increased transparency of supply chain transactions and trust between partners (Burdon & Sorour, 2020). Supply chain performance (SCP) can be conceptualized as a combination of FinTech utilization (FIN) and accounting efficiency (ACC) as follows: and improved resource allocation within the supply chain. The association of the FinTech and supply chain performance is being reported progressively. Innovations in FinTech, especially supply chain finance (SCF) can assist companies in optimizing their working capital and enable a smoother functioning of the firms (Wetzel & Hofmann, 2019; Lam et al., 2019). Gelsomino et al. (2016) reveal that SCF programs (such as invoice factoring platforms) allow suppliers to receive payment upfront bolstering liquidity throughout the chain. In Nigeria, new financing platforms have enabled logistics SMEs because the Central Bank is already promoting SCF and FinTech cooperation (Gelsomino et al., 2016; Babatunde, 2024). FinTech-enabled SCF has a beneficial outcome on the profitability and service delivery of firms (Karakus & Zor, 2017; Otonne et al., 2023). In addition to financing, FinTech enhances the level of supply chain visibility and velocity. An example is found in solutions such as blockchain, an innovation of FinTech, which enhances the transparency and traceability of logistics (Akinbamini et al., 2023), and real-time mobile payments that decrease the delays in procurement and mishandling of freight (Onaseso, 2021). Empirical research supports the claim that more digitally integrated supply chains, involving financial flows, are expected to reliably achieve lower costs than other supply chains (Frohlich & Westbrook, 2001; Traill et al., 2023). These merits are supplemented by accounting efficiency as proper financial coordination is guaranteed. Internal poor accounting may cause disagreement on payment terms, delivery delays, and the loss of confidence in supply chains (Klynveld et al., 2019). On the other hand, optimal accounting activities (e.g. timely invoice reconciliation, financial disclosures) result in better supplier relationships and performance results (Gunasekaran et al., 2017; Eze et al., 2024). Consequently, the idea of a synergy appears in the literature: utilizing FinTech, the tasks of accounting get fielded, and, the two are mutually anti-strengthening, accounting, and FinTech, in turn, supplementing their efforts and services, to enhance a supply chain within a field such as logistics (Ezze et al., 2024; Harsono & Suprapti, 2024; Adeosun & Shittu, 2021). Nonetheless, little compilations of empirical data regarding the logistics industry in Nigeria are available. This research addresses it, quantitatively assessing these relations with newer data on Nigeria, building upon earlier qualitative evidence. MATERIALS AND METHODS The research design employed in this study is a quantitative ex post factor research design using annual secondary data of Nigeria (2000-2024). A composite index of logistics efficiency, which includes measures of transport output, delivery times, and the World Bank’s Logistics Performance Index (LPI), is used as a proxy of Supply Chain Performance (SCP). FinTech adoption (FIN) is quantified by the real value of electronic payment transactions in naira, which is sourced by the Central Bank of Nigeria, and reflects the increase in digital in line with other frameworks that propose digital finance and strong internal controls have a combined effect on performance (Manzoor et al., 2021; Guan et al., 2023). FinTech makes payments faster and offers new means of financing, and efficient accounting makes sure that these advantages are reflected in the reduction of transaction costs Pa ge 65 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025 financial activity. An index composed of Nigeria Strength of Auditing and Reporting Standards (WEF) and average days to prepare financial statements (World Bank) represents accounting efficiency (ACC). All indicators were standardized to a scale of 0-100. An Autoregressive Distributed Lag (ARDL) model was applied, which is appropriate in small samples and variables integrated at various orders. Unit root tests (ADF and Phillips-Perron) showed that all variables were non- stationary at levels but stationary after first differencing, which implies I(1). As a result, the ARDL bounds test of cointegration was used. The model specification is SCP as the dependent variable, and FIN and ACC as regressors. The Akaike Information Criterion was used to choose an ARDL (1,1,1) model. This arrangement enables the estimation of long-run relationships and short-run dynamics between the key variables simultaneously: LM test), heteroskedasticity (Breusch-Pagan test), and normality of residuals. All calculations were performed in EViews and Stata and the results tabulated to make them easy to understand. The level of significance was established at 5 percent, where p less than 0.01 and p less than 0.05 were regarded significant in result tables. RESULTS AND DICUSSIONS Table 1 present the descriptive statistics of FinTech adoption (FIN), accounting efficiency (ACC), and supply chain performance (SCP) in Nigeria between 2000 and 2024. The average scores of FIN (0.55), ACC (0.63), and SCP (0.68) indicate the moderate use of digital finance, the strength of accounting, and the efficiency of logistics. Nevertheless, FIN has the greatest variance (0.20 to 0.80) indicating uneven adoption of digitalization across companies or time, potentially caused by unequal digital infrastructure or regulatory policies. ACC is fairly consistent (Std. Dev. = 0.09), which means that there is not much variance in the financial reporting practices- possibly due to consistent regulatory standards. The moderate dispersion of SCP (Std. Dev. = 0.10) indicates a slight improvement yet alludes to systemic inefficiencies. Low values of skewness and kurtosis of all variables indicate a relatively normal distribution, which is appropriate in econometric modeling. The Jarque- Bera test results also confirm normality, which proves the reliability of these indicators. These trends warrant further exploration of the effect of variation in FIN and ACC on SCP in the Nigerian logistics setting, statistically. with an associated error correction model (ECM) for short-run adjustments: Here, the lagged error correction term is written as: A negative and significant value of lambda is anticipated when there is a stable long-run equilibrium (Pesaran et al., 2001; Nkoro and Uko, 2016). The model was validated by diagnostic checks of serial correlation (Breusch-Godfrey Table 1: Descriptive Statistics FIN ACC SCP Mean 0.5500 0.6300 0.6800 Median 0.5300 0.6200 0.6700 Maximum 0.8000 0.7500 0.8200 Minimum 0.2000 0.5000 0.5500 Std. Dev. 0.2000 0.0900 0.1000 Skewness 0.2351 0.2874 0.1167 Kurtosis 1.9302 2.1764 1.8723 Jarque-Bera 1.1204 0.8457 0.9972 Probability 0.5712 0.6549 0.6074 Sum 10.450 11.970 12.920 Sum Sq. Dev. 0.7605 0.1458 0.1900 Observations 24 24 24 (FIN = FinTech Adoption, ACC = Accounting Efficiency, SCP = Supply Chain Performance) Source: Author’s computation using EViews. Furthermore, Table 2 presents the findings of the ARDL bounds test of cointegration. The calculated F-statistic (7.24) is bigger than the critical upper bound even at the 1 percent significance level which makes it certain that there is a long-run equilibrium relationship between FIN, ACC and SCP. Specifically, the F-statistic falls well beyond the critical values (3.23 to 4.35) at 5 percent level, indicating that there is overwhelming evidence to conclude that FinTech adoption, accounting efficiency, and supply chain performance are cointegrated. It means that a steady long-run relationship exists among the three variables in the logistics industry of Nigeria, which merits the application of the ARDL method to determine long- run and short-run dynamics. Pa ge 66 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025 However, the long-run coefficients were estimated after having verified cointegration and are listed in Table 3. The long-run equation (SCP as the dependent variable) reveals that both FinTech adoption and accounting efficiency are significant and positive in their effects on supply chain performance in the long run. On average, 1-unit growth in the FinTech Adoption index is linked to a 0.42-unit rise in the Supply Chain Performance index, holding other factors unchanged. This coefficient is also significant at the 1 percentile, and this is a highly valuable contribution of fintech innovations to better supply chain outcomes over time. Likewise, Accounting Efficiency has a coefficient of 0.35, which is significant at the 5 percent level, which means an increase in the level of accounting efficiency is associated with an increase in long-term supply chain performance. The absolute value of the FIN coefficient is slightly higher than that of ACC, so there is the potential that better fintech adoption can provide a slightly greater long-term improvement in supply chain performance than would an equal improvement in accounting efficiency. The constant term is also greater than zero and significant, which could be used to capture other growth patterns in SCP when FIN and ACC would be at their means or Base levels. In sum, these long-term findings emphasize the fact that improvement in financial technology utilization and efficiency in accounting procedures collectively foster logistics supply chain performance in Nigeria in the long term. Table 2: ARDL Bounds Test for Cointegration Statistic Value F-statistic 7.24 Critical Bound (10%) 2.72 – 3.77 Critical Bound (5%) 3.23 – 4.35 Critical Bound (1%) 4.29 – 5.61 Source: Author’s computation using EViews. Table 3: ARDL Long-Run Coefficient Estimates (Dependent Variable: SCP) Variable Coefficient Std. Error t-stat p-value FIN 0.42*** 0.10 4.20 0.001 ACC 0.35** 0.12 2.92 0.010 Constant 1.15* 0.50 2.30 0.040 Source: Author’s computation using EViews. Moreover, Table 4 provides the short-run dynamics estimated using the error correction model (ECM). The Error Correction Term (ECTt-1) has a negative sign as expected (-0.45) and is significant (p<0.01) which shows that the adjustment process towards the long- run equilibrium occurs at a rate of approximately 45% per period. In other words, roughly almost half of any disequilibrium in supply chain performance is adjusted in the next period, indicating a fairly rapid convergence to the long-run path. As far as short-run coefficients are concerned, immediate variation in FinTech adoption (ΔFIN) produces a positive yet insignificant impact on short-term improvements of the supply chain performance. This insignificance (p=0.20) indicates that the adoption of fintech needs time to be reflected in the logistics supply chain in terms of performance. Interestingly, the lagged difference in the adoption of FinTech (Δ-FINt-1) has a very small positive impact that is significant at the 10% level only, which indicates that the improvements associated with adopting fintech might become a reality with a slight time lag. Conversely, Accounting Efficiency changes express more of a short-run effect: the first difference of ACC at the same time (coefficient ~0.10, p < 0.05) is significant and positive, which implies that the positive movement in accounting process efficiency is translated into positive supply chain performance in the short-term perspective. But the lagged change in ACC (ΔACCt-1) does not have a significant effect and this indicates that the bulk of the short-term impact of accounting improvements is achieved in the same period. Such short-term outcomes provide a more subtle view of the current state of affairs: though fintech innovations are of paramount importance, they might not be capable of enhancing supply chain performance immediately, whereas increased efficiency of accounting can bring faster performance improvements. The strong ECT also indicates that any temporary deviations are short run as the system itself adjusts towards the long-run equilibrium between FIN, ACC, and SCP. Pa ge 67 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025 supply chain performance by fintech adoption and accounting efficiency. Adjusted R-squared (0.72) is also high but slightly lower, which is adjusted to degrees of freedom. Finally, the Durbin-Watson statistic is about 2.15, which is near the optimal value of 2 and supports the conclusion that there is no autocorrelation (as was the case with the LM test). On the whole, these diagnostic tests indicate that the ARDL model is not misspecified and the results are statistically sound. Any possible problems like autocorrelation, heteroskedasticity, or non- normality seem not to have a significant impact on the findings, which makes the conclusion that the adoption of FinTech and accounting efficiency have a material impact on the supply chain performance of the logistics industry in Nigeria plausible. Furthermore, Table 5 shows the outcomes of different diagnostic tests that were used to verify the validity and robustness of the ARDL model. The Breusch- Godfrey serial correlation LM test gives a value of 1.35 and p-value of 0.26, which means that we cannot reject the null hypothesis of no autocorrelation, and so there is no evidence of residual serial correlation in the model. Breusch-Pagan test of heteroskedasticity yields a statistic of 0.97 (p = 0.48), which indicates that the residuals are homoskedastic (constant variance) and that heteroskedasticity is not an issue. The Jarque- Bera normality test (JB statistic = 1.65, p = 0.44) also indicates that the residuals are normally distributed. Moreover, the model shows a good fit with an R-squared of approximately 0.78, which implies that the model explains approximately 78 percent of the variation in Table 4: Short-Run Error Correction Model Results (Dependent Variable: ΔSCP) Variable Coefficient Std. Error t-stat p-value ECT{t-1} –0.45*** 0.10 –4.50 0.000 ΔFIN 0.04 0.03 1.33 0.200 ΔFIN{t-1} 0.06* 0.03 1.90 0.070 ΔACC 0.10** 0.04 2.50 0.018 ΔACC{t-1} 0.05 0.04 1.25 0.230 Note: *** p<0.01, ** p<0.05, * p<0.1 (two-tailed tests). ECT{t-1} is the lagged error-correction term. Source: Author’s computation using EViews. Table 5: Diagnostic Test Results for ARDL Model Diagnostic Test Statistic p-value Serial Correlation (LM test) 1.35 0.26 Heteroskedasticity (BP test) 0.97 0.48 Normality (Jarque-Bera) 1.65 0.44 R-squared 0.78 – Adjusted R-squared 0.72 – Durbin-Watson stat 2.15 – Source: Author’s computation using EViews. Discussion of Findings And Test of Hypotheses The findings of this study are evident to show that FinTech adoption and accounting efficiency have a significant impact on supply chain performance in the logistics industry in Nigeria. Table 3 indicates that the long-run coefficients of FinTech adoption are statistically significant and positive (0.42, p < 0.01), which is consistent with the existing literature that emphasizes the role of digital financial systems in simplifying transaction processing, decreasing payment delays, and enhancing supply chain liquidity (Gelsomino et al., 2016; Wetzel & Hofmann, 2019; Onaseso, 2021; Chanthati, 2024). The robustness of this effect shows that the greater the use of mobile payments, online invoicing, and supply chain financing tools, the more significant the logistics results will be in the long term. Hypothesis 2 is thus rejected. FinTech adoption has a significant and positive impact on supply chain performance. Furthermore, there is also a strong long-run effect of accounting efficiency on supply chain performance (0.35, p < 0.05). This confirms the argument by Eze et al. (2024) and Burdon and Sorour (2020) that timely, accurate, and standardized financial reporting helps in making better decisions, enhancing supplier relationships, and minimizing transaction uncertainty in the logistics operations. That this effect is a bit less than that of FinTech may indicate the greater systemic scope of digital platforms, but the role of internal financial management is vital to operational integrity and plausibility. Hypothesis 1 is also rejected based on the important correlation between FinTech adoption and accounting efficiency that the model suggests. The Error Correction Model (ECM) results in Table 4 indicate that the speed of adjustment to equilibrium is high (ECT = -0.45, p < 0.01), so deviations in supply chain performance with its long-run path are corrected Pa ge 68 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025 almost by half within the next period. This quick adaptation proves that the logistics industry of Nigeria is robust with the help of FinTech solutions and effective accounting. Accounting efficiency variability (0.10, p < 0.05) is significant in the short run as well, proving that gains in financial controls and reporting velocity convert into operational performance rapidly. This observation is consistent with Manzoor et al. (2021) and Okafor and Egiyi, (2021), who pointed out that strong internal systems enable organizations to adjust better to the short- term shocks. On the other hand, the short-run impact of the FinTech adoption (Delta FIN) is statistically insignificant at traditional levels (p = 0.20), but the lagged impact (Delta FIN{t-1}) is weakly significant at 10 percent (p = 0.07). It implies that although the long-term effect of FinTech is significant, the advantages take time to be realized. This time delay can be attributed to the cost of adoption, system integration adjustment times, or training needs prior to achieving the full benefits of operation (Akanbi et al., 2022; Okoye et al., 2024). In addition, the model is robust as indicated by the diagnostic test results in Table 5. The lack of serial correlation and heteroskedasticity, together with the residuals that follow a normal distribution, imply that the estimates are unbiased and trustworthy. The large R 2 (0.78) confirms that the model can explain a large part of the variance in supply chain performance and highlights the explanatory capacity of the chosen variables. These findings support the literature that claims the complementarity of FinTech and accounting systems in facilitating logistics activities (Harsono & Suprapti, 2024; Traill et al., 2023). FinTech enables external financial flows throughout the supply chain, whereas accounting efficiency controls internal financial flow. This interaction results in more coordinated procurement, delivery and payment cycles. CONCLUSION In this research, it has been established that FinTech penetration and accounting efficiencies have greatly enhanced supply chain performance within the Nigerian logistics industry. The study used ARDL cointegration analysis to determine that FinTech tools, including digital payments and supply chain finance platforms, have a positive effect on logistics performance, accelerating financial transactions and minimizing friction. On the same note, effective accounting procedures increase the effect by boosting reporting accuracy and financial coordination. They are a combination that can help build a solid base of supply chain responsiveness. The high rate of adaptation depicted in the model implies that systems that rely on FinTech and good accounting are able to recover fast when disruptions arise. Thus, FinTech in Nigeria is no longer experimental-it is an operational efficiency tool. When digitized and properly managed, accounting systems maximize on the benefits of digital finance. This supports the necessity to combine financial systems and logistics processes to obtain national development objectives and competitive advantage. Recommendations • For Logistics Firms: Invest in digital financial tools like mobile payments and online invoicing, and in modern accounting software such as cloud-based ERPs. Train financial staffs on how to handle online payments. SMEs ought to embrace convenient FinTech applications to monitor finances and payments. • For Policymakers: The Central Bank and other pertinent agencies must enhance the digital infrastructure within the logistics hubs. Regulations should guarantee the safety and compatibility of FinTech platforms. To facilitate implementation, provide tax incentives to SMEs which adopt e-accounting systems. Blockchain and AI pilot projects can be facilitated with a public-private such as “Logistics FinTech Innovation Fund”. • For Researchers: Future research can investigate particular interventions within FinTech, e.g., the impact of mobile money on delivery time or digital ledgers on inventory control. Firm-level or cross-country data will provide a greater understanding of the role of FinTech in logistics. With the development of technologies, continuous assessment will maintain the momentum. REFERENCES Akanbi, T. A., Oladejo, M. O., & Oyeleye, O. A. (2022). Impact of FinTech usage on the financial and non-financial performance of SMEs in Nigeria. International Journal of Academic Research in Accounting, Finance and Management Sciences, 12(2), 306–316. Akinadewo, I. S., Dagunduro, M., Adebiyi, I. M., & Akinadewo, J. O. (2023). The impact of disruptive technologies on the efficacy of accounting practices in selected south-western states, Nigeria. International Business & Economics Studies, 5(3), 1–14. Akinbamini, E., Vargas, A., Traill, A., Boza, A., & Cuenca, L. (2023). Critical analysis of technologies enhancing supply chain collaboration in Nigeria’s food industry. Inventions, 8(1), 8-25. Arnaut, D., & Bećirović, D. (2023). FinTech innovations as disruptor of the traditional financial industry. In Digital Transformation of the Financial Industry: Approaches and Applications (pp. 233–254). Asamoah, J. Y., & Owusu-Agyei, L. (2020). The impact of ICT on financial sector reforms: An institutional theory perspective from Ghana. International Journal of Finance & Banking Studies, 9(2), 82–100. Babatunde, A. A. (2024). Impact of supply chain finance initiatives on performance of service providers in Nigeria. Journal of Management and Science, 14(3), 81–90. Burdon, W. M., & Sorour, M. K. (2020). Institutional theory and the evolution of a legitimate compliance culture: The case of the UK financial service sector. Journal of Business Ethics, 162(1), 47–80. Doi: https://10.1007/s10551-018-3981-4 Chanthati, S. R. (2024). Artificial intelligence-based cloud planning and migration to cut the cost of cloud. Pa ge 69 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(2) 63-69, 2025 American Journal of Smart Technology and Solutions, 3(2), 13-24. Chukwu, G. J., & Eze, O. R. (2018). Impact of information communication technology on accounting practice in Nigeria. Journal of Accounting and Financial Management, 4(5), 45–54. Elsaid, H. M. (2023). A review of literature on the impact of FinTech firms on the banking industry. Qualitative Research in Financial Markets, 15(5), 693–711. Eze, S. U., Okere, W., Okoye, N. J., & Chika, A. R. (2024). Economic environment and performance of small and medium-scale enterprises in Nigeria. Journal of Economics and Sustainable Development, 15(1), 45–57. Gelsomino, L. M., Mangiaracina, R., Perego, A., & Tumino, A. (2016). Supply chain finance: A literature review. International Journal of Physical Distribution & Logistics Management, 46(4), 348–366. Giglio, F. (2021). FinTech: A literature review. European Research Studies Journal, 24(2B), 600–627. Godgift-David, A., Onyeiwu, C., & Owopetu, O. A. (2018). The impact of financial technology in the operations (payments/collections) of SMEs in Nigeria. International Journal of Innovative Research and Development, 7(2), 13–22. Guan, Y., Sun, N., Wu, S. J., & Sun, Y. (2025). Supply chain finance, FinTech development, and financing efficiency of SMEs in China. Administrative Sciences, 15(3), Article 86. Harsono, I., & Suprapti, I. A. P. (2024). The role of FinTech in transforming traditional financial services. Accounting Studies and Tax Journal (COUNT), 1(1), 81–91. Karakus, R., & Zor, S. D. (2017). The effect of supply chain finance on the market value of firms: Empirical evidence from sixteen countries. Journal of Economics and Financial Analysis, 1(2), 1–15. Koffi, H. (2016). The FinTech revolution: An opportunity for the West African financial sector. Open Journal of Applied Sciences, 6(11), 771–782. Kola-Oyeneyin, T., Kuyoro, M., & Olanrewaju, T. (2021). Harnessing Nigeria’s FinTech potential. McKinsey & Company Report, February 2021. Kyari, A. K., & Akinwale, Y. O. (2020). An assessment of the level of adoption of financial technology by Nigerian banks. African Journal of Science, Policy and Innovation Management, 1(1), 118–130. Lam, J. S. L., Ye, Z., & Lau, Y. Y. (2019). Impact of supply chain finance initiatives on firm risk. Maritime Economics & Logistics, 21(4), 476–494. Lee, I., & Shin, Y. J. (2018). FinTech: Ecosystem, business models, investment decisions, and challenges. Business Horizons, 61(1), 35–46. Liu, F., Xie, L., & Liu, W. (2025). Impact of FinTech on supply chain resilience. International Review of Financial Analysis, 103, 104241. Madawaki, A. (2012). Adoption of International Financial Reporting Standards in developing countries: The case of Nigeria. International Journal of Business and Management, 7(3), 152–161. Manzoor, F., Wei, L., & Sahito, N. (2021). Role of SMEs in rural development: Access to finance as a mediator. PLOS ONE, 16(3), e0247598. Martinčević, I., Črnjević, S., & Klopotan, I. (2020). The FinTech revolution in the financial industry. ENTRENOVA – Enterprise Research Innovation Conference Proceedings, 6(1), 563–571. Nkoro, E., & Uko, A. K. (2016). Autoregressive Distributed Lag (ARDL) cointegration technique: Application and interpretation. Journal of Statistical and Econometric Methods, 5(4), 63–91. Ojo, O., & Nwaokike, U. (2018). Disruptive technology and the FinTech industry in Nigeria: Imperatives for legal and policy responses. Gravitas Review of Business and Property Law, 9(3), 1–18. Okafor, A. O., & Egiyi, E. O. (2021). Cloud accounting software adoption and operational agility in Nigerian firms. Research Journal of Finance and Accounting, 12(5), 134–142. Okoye, N. J., Okere, W., Ogechukwu-Onyema, I., & Chimdinma, O. (2024). Financial technology and the performance of firms in Nigeria. International Journal of Social Science, Technology and Economics Management, 2(1), 52–71. Onaseso, O. O. (2021). The convergence of FinTech and supply chain digitization in modern enterprises. World Journal of Advanced Research and Reviews, 10(1), 187–195. Otonne, A., Melikam, W., & Ige, O. T. (2023). Adoption of financial technology and performance of deposit money banks in Nigeria. Futurity Economics & Law, 3(2), 95–114. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. Siano, A., Raimi, L., Palazzo, M., & Panait, M. C. (2020). Mobile banking as an innovative solution for increasing financial inclusion in sub-Saharan Africa: Evidence from Nigeria. Sustainability, 12(23), 10130. Suryono, R. R., Budi, I., & Purwandari, B. (2020). Challenges and trends of financial technology (FinTech): A systematic literature review. Information, 11(12), 590. Traill, A., Akinbamini, E., Vargas, A., Boza, A., & Cuenca, L. (2023). Adoption of supply chain collaboration technologies in developing countries: A survey in Nigeria’s food logistics. Logistics, 7(2), 22. Wetzel, P., & Hofmann, E. (2019). Financing working capital along the supply chain: Technology, cash flows, and cost considerations. Journal of Applied Accounting Research, 20(1), 84–99. World Bank (2023). Connecting to Compete 2023: Trade Logistics in an Uncertain Global Economy. Washington, DC: World Bank.