Modern approaches to accounts receivable management
Abstract
Under conditions of market competition and economic instability, effective accounts receivable management is a key factor of financial stability for business entities. As the business environment evolves, approaches to accounts receivable management are also undergoing transformation and refinement.
Problem statement. Despite substantial academic research, Ukrainian enterprises face excessive accumulation of accounts receivable — up to 40–60% of current assets. At the same time, traditional management methods do not fully capture the specifics of extended delivery timelines and currency fluctuations characteristic of the domestic business environment. This calls for continuous revision and refinement of established management models, as well as the adaptation of relevant international experience.
Unresolved aspects. A systematic comparative analysis of modern accounts receivable management models — considering their applicability across industries and business types — is lacking. The role of staged payment schemes as a preventive tool for mitigating credit and currency risks has not been sufficiently substantiated.
Purpose. To systematize and compare five key accounts receivable management models, examine their real-world applications under different market conditions, and develop industry-differentiated recommendations for the optimal combination of individual models.
Main material. A comparative analysis is conducted of the traditional credit model, ABC/XYZ analysis, factoring, the AI/machine-learning-based model, and the staged payments model. For each model, the mechanism of action, advantages, limitations, and actual practice of application are described. A matrix of optimal model combinations by enterprise type is developed.
Conclusions. No single model, taken in isolation, provides comprehensive management of accounts receivable. The most effective approach is a hybrid strategy combining the credit model as a foundation, ABC/XYZ analysis for prioritization, and the situational use of staged payments, factoring, or AI-based tools depending on the industry and scale of business.
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References
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