Developing an Intelligent Model for Assessing Corporate Financial Sustainability with Emphasis on ESG Indicators, Climate Risk, and Economic Performance
Keywords:
Financial sustainability, ESG, climate risk, economic performance, intelligent model, sustainability reporting, thematic analysis.Abstract
This study aimed to develop an intelligent model for assessing corporate financial sustainability with an emphasis on ESG indicators, climate risk, and economic performance. This qualitative study was conducted using thematic analysis. The research population consisted of financial experts, accounting and reporting managers, investment analysts, risk management specialists, ESG consultants, and board-level professionals from companies located in Tehran. Participants were selected through purposive and snowball sampling, and data collection continued until theoretical saturation was achieved. A total of 21 in-depth semi-structured interviews were conducted. After obtaining informed consent, the interviews were recorded, transcribed verbatim, and imported into NVivo software for coding and analysis. Data analysis followed the six-phase thematic analysis procedure, including familiarization with the data, generating initial codes, searching for themes, reviewing themes, defining and naming themes, and producing the final report. Member checking, peer debriefing, audit trail documentation, and constant comparison were used to enhance the trustworthiness of the findings. The analysis resulted in five main categories: ESG data infrastructure and measurability, integration of climate risk into financial assessment, linkage between sustainability and economic performance, governance, transparency and assurance of sustainability reporting, and the architecture of an intelligent financial sustainability assessment model. The findings indicated that financial sustainability assessment becomes analytically meaningful when non-financial ESG indicators are translated into financial implications, climate-related risks are incorporated through scenario-based and measurable approaches, and model outputs are interpretable for investors, creditors, and corporate decision-makers. The findings suggest that an intelligent financial sustainability assessment model should move beyond formal ESG scoring and combine financial data, ESG indicators, climate risk exposure, governance quality, and economic performance to provide a multidimensional picture of corporate resilience, risk, and value-creation capacity. Such a model can improve investment decision-making, enhance sustainability reporting quality, reduce information asymmetry, and strengthen corporate accountability.
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