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This article maps the knowledge structure and evolution of bankruptcy/default prediction research in financial institutions using a bibliometric co-citation approach, which identifies works that are often cited together due to the proximity of their theories, methods, or themes. Bibliographic data were collected from the Web of Science (WoS) for the period 1970-2025, then extracted in a complete bibliographic format and prepared for network analysis. The co-citation procedure is carried out by extracting the reference list, normalizing and unifying citation variations, and preparing a co-citation matrix, which is then visualized and classified using VOSviewer with minimum threshold parameters and normalized association strength. The results of the document ranking based on the number of citations and Total Link Strength (TLS) show the development trajectory of the field from the ratio and Z-Score approach to the logit probabilistic model, the market foundation based on the structural theory of credit risk, the governance perspective supported by agency theory, the dynamic panel methodology/GMM for longitudinal data, to computational waves (neural networks and machine learning) to capture nonlinear patterns of credit scoring. The co-citation map uncovers four main clusters: econometrics & banking risk, structural theory, ratios, and computational, with Merton and Altman acting as the cross-cluster binding nodes. These findings support the design of a more comprehensive early warning system (EWS) by integrating ratio signals, market indicators, governance/agency factors, and ML models to improve accuracy and adaptation.    

This study aims to assess the impact of exposure to Carbon Emission Disclosure (CED) and the level of Greenhouse Gas (GHG) emissions on the valuation of companies operating in the Indonesian banking sector. This in-depth study also evaluates the influence of capital structure and intellectual property assets. In addition, this study explicitly examines how financial performance moderates the relationship between these variables and the company's value. Using a quantitative research method, this analysis observed a sample consisting of banking entities listed on the Indonesia Stock Exchange (IDX) from 2020 to 2024. The theoretical framework underpinning this research comprises Legitimacy Theory, Stakeholder Theory, Signal Theory, Preference Order Theory, and the resource-based view (RBV). The results reveal that transparent disclosure of carbon emissions and the accumulation of intellectual capital positively influence the company's value, while GHG emissions and leverage have adverse effects. Crucially, financial performance (ROA) moderates these relationships by weakening the positive impact of carbon disclosure and buffering the negative impact of GHG emissions but does not significantly moderate the effects of capital structure or intellectual capital. These findings offer practical guidelines for banking management to align environmental sustainability practices with financial strategies to enhance corporate value.