Abstract

The aim of this article is to identify resource management issues related to the operational goal of the internal control system and to provide effective operational goal management methods with machine learning models. Machine learning algorithms were utilised to develop prediction models of capital, liabilities, income and profit based on the interdependencies of the indicators. Based on the intended profit/income ratio and the numerical quantities of assets, the optimal balance of credit organisations was predicted as a consequence of the models that were generated and used to solve the problem of financial indicator optimisation. The model proposed by us allows for the identification and avoidance of unnecessary concentrations of assets and liabilities, allowing both supervisory authorities and business owners to understand the alignment of the business with its vision, as well as identify problems and implement appropriate solutions, define new ambitious plans, and use resources more effectively.

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