Accounting Information Usefulness in Credit Risk Evaluation by Financial Institutions (gjstudies, 2019)
This research presents a novel, cross-disciplinary framework that re-conceptualizes the utility of accounting information in credit risk evaluation by integrating principles from computational linguistics,network theory, and behavioral finance. Moving beyond traditional ratio analysis and conventional financial statement evaluation, we propose a methodology that treats accounting disclosures as a complex,multi-layered semantic network. This network is analyzed not only for its explicit numerical content butalso for its implicit narrative structures, temporal consistency patterns, and inter-statement relationaldynamics. Our approach employs a hybrid technique combining transformer-based natural languageprocessing models, specifically fine-tuned for financial discourse, with graph neural networks to mapthe latent connections between accounting line items, management discussion narratives, and footnotedisclosures. This creates a holistic ’Accounting Information Coherence Score’ (AICS). We formulate andaddress the unconventional research question: To what extent does the semantic and structural coherenceof accounting information, as a system, predict credit risk more accurately than the information’s individual quantitative components? Using a unique dataset of corporate loan applications and subsequentdefault events from a consortium of mid-sized U.S. financial institutions, we demonstrate that the AICSprovides a statistically significant improvement in default prediction accuracy (AUC-ROC improvementof 0.12) over models relying solely on traditional financial ratios and credit scores. Furthermore, themodel reveals that specific patterns of narrative-quantitative dissonance and footnote network fragmentation are strong, early indicators of financial distress often missed by human analysts and standardmodels. The findings challenge the prevailing reductionist view of accounting data in credit analysisand advocate for a systemic, integrative evaluation paradigm. This research contributes original insightsto accounting information systems, risk management, and fintech, proposing a shift from informationextraction to system coherence assessment in financial decision-making.