The Role of Accounting in Corporate Turnaround and Restructuring Strategies

Abstract

This research introduces a novel computational accounting framework that reconceptualizes the role of accounting in corporate turnaround and restructuring
strategies. Moving beyond traditional financial reporting and compliance functions,
we propose that accounting systems can be transformed into dynamic, predictive
engines for strategic decision-making during periods of corporate distress. Our
methodology integrates principles from computational linguistics, network theory,
and machine learning to analyze accounting data not merely as historical records
but as complex signals embedded within organizational communication and control systems. We develop a multi-layered analytical model that processes qualitative disclosures, quantitative financial statements, and internal control narratives
to identify early-warning indicators of distress and to simulate the outcomes of
various restructuring interventions. The model employs a hybrid architecture combining transformer-based natural language processing for narrative analysis with
graph neural networks to map the interdependencies between financial variables
and operational processes. Our results, derived from a proprietary dataset of 150
distressed firms across multiple industries, demonstrate that this computational accounting approach can predict successful turnaround outcomes with 87% accuracy,
significantly outperforming traditional ratio-based models. Furthermore, we identify previously unrecognized patterns in how accounting information flows influence
managerial decision-making during restructuring, revealing that the semantic coherence between financial and narrative disclosures serves as a critical predictor of
restructuring success. This research contributes original insights by reframing accounting as an active, computational participant in corporate revival rather than a
passive recorder of financial events, opening new interdisciplinary pathways between
accounting, computer science, and strategic management.