EXPLAINABLE ARTIFICIAL INTELLIGENCE FOR SME FINANCIAL RESILIENCE: AN INTEGRATED SIGNALLING FRAMEWORK FROM UTTAR PRADESH

Abstract

Small and Medium Enterprises (SMEs) constitute a crucial segment of Uttar Pradesh’s economic ecosystem, yet they often operate under significant financial uncertainty. This study investigates how Explainable Artificial Intelligence (XAI) can strengthen financial forecasting practices within these enterprises by offering transparent, data-driven insights. Drawing on responses from 325 SMEs across major industrial clusters, the research employed rigorous reliability assessments and descriptive analyses to evaluate the performance and relevance of XAI-based tools in predicting financial health.

The results demonstrate that the integration of XAI meaningfully enhances the overall quality of financial decision-making. By providing clear justifications for its predictions, XAI improves stakeholder confidence and reduces ambiguity associated with conventional “black-box” AI models. This transparency also supports better regulatory compliance, as decision-makers are able to trace and justify automated financial assessments. A key finding of the study highlights the strong influence of Financial Distress Indicators (FDI) on strengthening SME financial resilience. Firms that systematically monitor distress signals—such as declining sales or liquidity challenges—show greater preparedness and adaptability when supported by XAI-enabled forecasting frameworks.

Beyond empirical insights, the study offers several practical contributions. It underscores the need for ethical and responsible AI adoption, ensuring fairness and accountability in financial prediction systems. The findings advocate for the development of user-friendly and context-appropriate XAI tools that SMEs can easily integrate into their existing operational workflows. Moreover, targeted training programmes and digital literacy initiatives are essential to empower SME owners, financial managers, and operational staff to effectively interpret and utilise these tools. Policymakers and technology developers are also encouraged to collaborate in creating supportive regulatory mechanisms that foster trust, safeguard SME interests, and promote sustainable technological innovation.
Overall, the study positions XAI as a transformative enabler for improving financial forecasting accuracy and strengthening the long-term resilience of SMEs in Uttar Pradesh