Abstract:
This study examines the contribution of financial forensics in determining manipulation, distress, and recovery trends in Pakistan International Airlines (PIA) following major market crashes. Based on a panel dataset for 2018, 2020, and 2022, the study examines how forensic accounting techniques can be used to identify financial anomalies and determine the genuineness of recovery plans purported by the airline. The study utilizes a quantitative, forensic-oriented approach, implementing three main models: Benford's Law for the identification of anomalies in distributions of financial data; the Beneish M-Score for the detection of potential earnings manipulation; and the Altman Z-Score for the evaluation of bankruptcy risk and long-term solvency. These forensic analytical tools are augmented by financial ratio analysis and investor sentiment assessment in order to understand how the marketplace participants reacted to PIA's financial reports or their absence amidst times of turmoil like the COVID-19 pandemic. Evidence shows consistent symptoms of financial distress overall years, with Altman Z-Scores well below the threshold of safety (e.g., 0.06 in 2020), and M-Scores above the risk of manipulation threshold in 2020 and 2022. Conformations to Benford's Law also indicate unusual patterns in reported revenues and expenses. Investor behavior, on the other hand, tended to show emotional decision-making, more driven by speculative news and bailout hopes than by forensic signs or financial fundamentals. The research concludes that forensic accounting models are not merely essential in identifying potential manipulation and insolvency but also fundamental tools for regulatory bodies, investors, and policymakers in ascertaining the actual health of state-owned enterprises. Also, the divergence between investor conduct and financial reality underscores the call for increased transparency, investor education, and forensic supervision. Finally, the research provides both analytical findings and policy-level suggestions that are intended to enhance governance, financial reporting integrity, and market trust in public sector institutions.
