Beyond profitability: Do cash flow management indicators forecast SMEs business failure in the long run?

Purpose: The study examines whether cash flow management indicators can serve as reliable early predictors of small and medium-sized enterprise (SME) business failure. Specifically, it investigates the ability of cash flow-based indicators to forecast business failure three years before the initiation of formal bankruptcy proceedings. Methodology: A multilayer perceptron (MLP) neural network with two hidden layers is applied to analyze a dataset of Serbian SMEs operating in the Trade and Manufacturing sectors. The model relies exclusively on cash flow indicators and is evaluated using a training-test data split and classification metrics derived from the confusion matrix. Findings: The results indicate that cash flow indicators provide early signals of SME business failure three years in advance. The model demonstrates high predictive performance, achieving an area under the ROC curve (AUC) of 0.895. Indicators related to operating cash flow generation and debt-servicing capacity emerge as the most influential predictors in this sample, highlighting the importance of liquidity and sustainable cash flow management for long-term business survival. Originality/value: The study contributes to the literature by focusing exclusively on cash flow indicators and applying a neural network approach to predict SME failure three years in advance. It represents one of the first regional studies combining a cash flow-centered perspective with machine learning methods and long prediction horizon, while analyzing firms within specific industry segments. Practical implications: The findings offer early warning signals that can support credit risk assessment, financial monitoring, and timely interventions by managers, lenders, and policymakers. Limitations: The study is limited by a relatively small sample size. While the sector-specific focus reduces structural heterogeneity, it may limit generalizability. Future research could extend the dataset across Balkan economies and incorporate additional or dynamic cash flow indicators capturing year-to-year changes.