Template-Type: ReDIF-Article 1.0 Author-Name: Muhammad Tofeeq Author-Workplace-Name: Lasbella, University, Pakistan. Title: Evaluating The Impact of Machine Learning and Alternative Data on Credit Precision and Fair Lending in Emerging Markets Publication-Status: Published Abstract: This study looks at how Artificial Intelligence can improve credit scoring for borrowers in Pakistan, especially those who struggle to get loans because they lack formal credit histories. Traditional lending still depends on collateral and old repayment records, which leaves out a large part of the population. With the rise of mobile banking and digital payments, new digital footprints such as telecom usage, mobile-wallet activity, and online transactions can now offer useful signals about a borrower’s behaviour. The research tests whether AI can turn this data into fair and accurate credit decisions. Using a dataset of 10,000 borrowers that reflects real microfinance clients in Islamabad, three models, Logistic Regression, Random Forest, and XG-Boost were developed and compared. The models were trained on both traditional variables (income, loan history, debt ratio) and alternative data (telecom activity, wallet usage, digital purchase patterns). Their performance was checked through accuracy, calibration, and fairness metrics. The results show that AI-based models clearly outperform the traditional approach. XG-Boost achieved the highest accuracy (AUC 0.943), followed by Random Forest, while Logistic Regression showed the weakest performance. Adding alternative data improved prediction accuracy by nearly 18%, making it easier to identify reliable borrowers who would otherwise remain “credit invisible.” Fairness tests also showed that AI models, when properly tuned, reduced gender-based bias and produced more balanced decisions. SHAP analysis confirmed that income, credit history, telecom usage, mobile-wallet activity, and loan size were the strongest predictors of default. The study concludes that AI-powered credit scoring can support financial inclusion in Pakistan by making lending decisions more accurate, transparent, and fair. It recommends that financial institutions adopt explainable AI tools, regulators strengthen data privacy frameworks, and pilot programs be used before full-scale deployment. While the study relies on simulated data, it provides a practical pathway for responsible AI adoption in Pakistan’s credit markets. Keywords: Artificial Intelligence; Machine Learning; Digital Footprints; XGBoost; Credit Invisible Journal: iRASD Journal of Finance Pages: 01 - 07 Volume: 3 Issue: 1 Year: 2024 Month: December DOI: 10.52131/jof.2024.0301.0011 File-URL: https://journals.internationalrasd.org/index.php/jof/article/view/3018 File-Function: Abstract page File-Format: text/html File-URL: https://journals.internationalrasd.org/index.php/jof/article/download/3018/1955 File-Function: Full text File-Format: application/pdf Handle: RePEc:rad:irdjof:v:3:y:2024:i:1:id:3018 Template-Type: ReDIF-Article 1.0 Author-Name: Muhammad Ayub Author-Workplace-Name: University of Peshawar, Pakistan. Author-Name: Shazia Kabeer Author-Workplace-Name: University of Peshawar, Pakistan. Title: The Role of Managerial Accounting in Enhancing Financial Performance and Sustainability of Small and Medium Enterprises in Pakistan Publication-Status: Published Abstract: The principal objective of the study is to examine the impacts of financial and sustainable performance of small and medium-sized businesses (SMEs) and how management accounting practices influence them. The quantitative research design was used and the primary data was obtained among 412 participants working in agriculture sector of Pakistan. The analysis of results was carried out on the SMART PLS software. The analysis by reliability showed that there was acceptable internal consistency as the values of Cronbach alpha varied between 0.62 and 0.89. Confirmatory factor analysis showed the adequacy of the model with a rather large chi-square/df ratio, and discriminating validity presence demonstrated that the constructs differed. In further regression results, costing practices were found to have the highest impact on financial performance (beta =0.754; p < 0.001) and sustainability (beta = 0.771; p < 0.001), and then budgeting practices, which were also statistically significant with positive coefficients. The impact of decision support systems on financial performance was also positive (? = 0.575, p = 0.013) though not significant on sustainability (p = 0.131). All in all, the findings indicate a small but still positive and important correlation between the management accounting practices and small and medium business performance. This study is important because SMEs constitute about 90 percent of businesses in the world and it is one of the biggest employers. Implementation of the management accounting in the SMEs will not only improve financial results, it will also help make sustainability viable in the long term improvements in efficiency and resilience. Keywords: Sustainable Performance; Costing Practices; Financial Performance; Budgeting Practices; Sustainability Journal: iRASD Journal of Finance Pages: 08 - 14 Volume: 3 Issue: 1 Year: 2024 Month: December DOI: 10.52131/jof.2024.0301.0012 File-URL: https://journals.internationalrasd.org/index.php/jof/article/view/3019 File-Function: Abstract page File-Format: text/html File-URL: https://journals.internationalrasd.org/index.php/jof/article/download/3019/1956 File-Function: Full text File-Format: application/pdf Handle: RePEc:rad:irdjof:v:3:y:2024:i:1:id:3019 Template-Type: ReDIF-Article 1.0 Author-Name: Md.Hassan Murad Author-Workplace-Name: King Abdul Aziz University Saudia Arabia. Author-Name: Md Umer Islam Author-Workplace-Name: King Abdul Aziz University Saudia Arabia. Author-Name: ABDEL Hamad Wahid Author-Workplace-Name: King Abdul Aziz University Saudia Arabia. Title: E-Commerce Adoption for MSME Performance in Saudi Arabia: Drivers, Outcomes, and Policy Implications Publication-Status: Published Abstract: COVID-19 turned business upside down for micro, small, and medium-sized enterprises (MSMEs) everywhere, and Saudi Arabia was no exception. Faced with disruption, these businesses scrambled to adapt, trying out new strategies just to stay afloat. In this study, I take a close look at how adopting e-commerce shaped MSME performance during the pandemic, and what drove these businesses to go digital in the first place. The study gathered data from 513 MSMEs across Saudi Arabia’s diverse regions. Using partial least squares-structural equation modelling (PLS-SEM), I examined the links between e-commerce adoption and business outcomes. The findings are clear: technology resources, technical infrastructure, and company size all play a huge role in whether an MSME adopts e-commerce. And when they do make the leap? Their financial and non-financial performance picks up noticeably. Another interesting point—MSMEs themselves serve as a bridge between e-commerce adoption and financial performance, amplifying the benefits of going online. These results add a new layer to what we know about technology adoption. They show how specific factors shape success during a crisis, and just how vital e-commerce can be for both survival and growth. For MSME managers and policymakers, these insights matter. Embracing e-commerce isn’t just a trend; it’s a lifeline for growth and resilience. Policymakers can use this research to design smarter strategies that encourage digital transformation in Saudi Arabia. On a broader level, the study sharpens the Technology-Organization-Environment (TOE) framework, giving MSMEs real-world guidance for navigating digital change, especially in turbulent times. Keywords: Small And Medium-Sized Enterprises; E-Commerce; Saudi Arabia; Financial Performance; Non-Financial Performance; Growth Journal: iRASD Journal of Finance Pages: 15 - 21 Volume: 3 Issue: 1 Year: 2024 Month: December DOI: 10.52131/jof.2024.0301.0013 File-URL: https://journals.internationalrasd.org/index.php/jof/article/view/3020 File-Function: Abstract page File-Format: text/html File-URL: https://journals.internationalrasd.org/index.php/jof/article/download/3020/1957 File-Function: Full text File-Format: application/pdf Handle: RePEc:rad:irdjof:v:3:y:2024:i:1:id:3020 Template-Type: ReDIF-Article 1.0 Author-Name: Manzar Waseem Author-Workplace-Name: The Comsats University, Vehari Campus. Title: Determinants of Cryptocurrency Volatility and its Linkages with The Stock Market Publication-Status: Published Abstract: This study analysed the certain features of cryptocurrencies connect to their ups and downs alongside traditional assets. It assessed how specific traits of some cryptos shape their volatility and how they move in synchronize with stock markets. To get a clear picture, the research compares the top 100 cryptocurrencies with eight major stock markets. Cointegration analysis and Granger causality tests had been applied to find hedge effects and co-movement. The logistic regression models found out the crypto-specific features really drive their dynamics. This research found that consensus and scarcity powerfully impact the co-movements. This study also highlighted the features and potential of cryptocurrencies that can dramatically alter the demand or perception towards them. These characteristics are rooted in finance theory and may alter the flexibility of cryptocurrencies, which has implications for demand, price, hedging efficiency and return relative to stocks’ return. Keywords: Cryptocurrency Volatility; Stock Market Co-movement; Hedge Effectiveness; Volatility Spillover; Logistic Regression Journal: iRASD Journal of Finance Pages: 22 - 28 Volume: 3 Issue: 1 Year: 2024 Month: December DOI: 10.52131/jof.2024.0301.0014 File-URL: https://journals.internationalrasd.org/index.php/jof/article/view/3021 File-Function: Abstract page File-Format: text/html File-URL: https://journals.internationalrasd.org/index.php/jof/article/download/3021/1958 File-Function: Full text File-Format: application/pdf Handle: RePEc:rad:irdjof:v:3:y:2024:i:1:id:3021 Template-Type: ReDIF-Article 1.0 Author-Name: Khazir Abbas Author-Workplace-Name: University of Abdul Wali Khan University Mardan. Title: Financial Literacy, Risk Perception, and the Effectiveness of Digital Tools in Investment Decision-Making Publication-Status: Published Abstract: This study analyzed the impact of digital influence on financial decision-making, especially looking at how financial literacy and risk perception come into play. To figure out what investors know and how they feel about risk mixes with digital tools to affect their investment results. The team gathered data from 350 individual investors using structured questionnaires and ran the numbers with Structural Equation Modeling. Here’s what stood out: when investors used digital tools, their investment outcomes improved a lot, but only when they already had strong financial knowledge. So, digital works best for people who understand finance. On top of that, risk perception made a difference. Investors who worried more about risk didn’t get as much out of digital-driven advice, even if they were financially literate. Basically, digital tools can’t guarantee you’ll make smart investments unless you know what you’re doing and you’re not too risk averse. This research adds a new layer to behavioral finance and fintech by combining how people think and feel with the impact of digital. The study also offers something practical: if policymakers and financial institutions want people to thrive with these new tools, they need to build better financial literacy programs and encourage smart, responsible use of digital tools in finance. Keywords: Investment Performance; Portfolio Management; Digital tools Influence; Investor Behavior; Financial Results Journal: iRASD Journal of Finance Pages: 29 - 35 Volume: 3 Issue: 1 Year: 2024 Month: December DOI: 10.52131/jof.2024.0301.0015 File-URL: https://journals.internationalrasd.org/index.php/jof/article/view/3022 File-Function: Abstract page File-Format: text/html File-URL: https://journals.internationalrasd.org/index.php/jof/article/download/3022/1959 File-Function: Full text File-Format: application/pdf Handle: RePEc:rad:irdjof:v:3:y:2024:i:1:id:3022