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Title: The Role of Artificial Intelligence in Enhancing Financial Forecasting Accuracy
Authors: Dr. Shahan Zeb Khan, Dr. Israfil , Muhammad Shahzad Gul , Fahad Asghar
Journal: Advance Journal of Econometrics and Finance (AJEAF)
| Category | From | To |
|---|---|---|
| Y | 2024-10-01 | 2025-12-31 |
Publisher: SCHOLAR CRAFT EDUCATION & RESEARCH HUB
Country: Pakistan
Year: 2025
Volume: 3
Issue: 3
Language: en
Keywords: Artificial IntelligenceFinancial ForecastingMachine LearningPakistan Stock Market
This study investigates the role of artificial intelligence (AI) in enhancing the financial forecasting accuracy of listed firms in Pakistan, with a specific focus on the mediating effect of financial performance. Using data collected from 100 firms listed on the Pakistan Stock Exchange, the research examines how AI-driven tools and techniques influence the precision of financial forecasts related to revenues, costs, and profitability. The findings reveal that AI significantly improves forecasting accuracy by enabling firms to process large and complex datasets, detect non-linear patterns, and adjust predictions in response to dynamic market conditions. Furthermore, the study demonstrates that financial performance partially mediates this relationship, as firms with stronger profitability and operational efficiency are more capable of investing in advanced AI technologies, thereby achieving even more accurate forecasts. Sectorial differences indicate that banking and manufacturing firms have higher AI adoption levels compared to service-oriented firms. The study contributes to financial management literature by empirically validating the direct and indirect effects of AI on forecasting accuracy and offers practical insights for corporate managers and policymakers seeking to enhance decision-making, investor confidence, and market competitiveness through technological integration.
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