Application of Artificial Intelligence Models in Finance (on the example of the UCO in RA)
DOI:
https://doi.org/10.46991/BYSU:G/2021.12.3.073Keywords:
artificial intelligence, machine learning, feature discretization, dimensionality reduction, pattern recognition, latent spaceAbstract
Evolving technologies and state-of-the-art machine learning algorithms have brought new opportunities for microfinance organizations. In this paper, we present the methodologies that can be used for better financial planning for such organizations and show the application for a UCO operation in RA.
Such methodologies allow obtaining cost-optimized and high-accuracy prediction models. Moreover, we showed that suggested techniques solve the problem of model interpretability and provide feature explanations for binary classification problems. Also, we demonstrated an algorithm that creates a latent space of features for data visualization and application segmentation.
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