FEATURES OF USING VBA IN TEACHING ACTUARIAL MATHEMATICS by Volodymyr Zubchenko, Rostyslav Yamnenko

“…This demand is being driven by new fintech trends in banking and insurance, such as smart payments, real-time credit risk assessment, automated reputation management, customer analytics, fraud detection and cryptocurrency trading. As a result, the training of future actuaries must meet high standards to ensure they are equipped to handle the sophisticated mathematical calculations required by insurance companies and other financial institutions. …”
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METHODOLOGY FOR EVALUATING THE EFFECTIVENESS OF ANTI-CORRUPTION ACTIVITIES IN THE MILITARY SECTOR UNDER CONDITIONS OF ENSURING FINANCIAL SECURITY by Myroslav Kryshtanovych, Oleksandr Nazarenko, Serhii Bazyka, Oleksii Vasyliev, Anna Munko, Yaroslav Panas

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Sobriété numérique et traitement des données massives : vers des stratégies d’innovation plus durables by Robert VISEUR

“…Finally, the article investigates the relationship between digital sobriety and the nature of technological platforms, highlighting the specific challenges posed by cryptocurrencies and advertising platforms. The study concludes with a set of recommendations regarding information, training, incentives, and regulation to foster a more digitally sober sector.…”
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STL-ELM: A computationally efficient hybrid approach for predicting high volatility stock market by Temitope Olubanjo Kehinde, Oluyinka J. Adedokun, Morenikeji Kabirat Kareem, Joseph Akpan, Oludolapo A. Olanrewaju

“…By decomposing stock data into trend, seasonal, and residual components, STL-ELM isolates multiscale features, while ELM’s lightweight architecture ensures rapid training and robust generalization, outperforming advanced techniques such as LSTM, GRU, and transformer variants in both prediction and trading simulations. …”
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Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent. by Alejandra de-la-Rica-Escudero, Eduardo C Garrido-Merchán, María Coronado-Vaca

“…In particular, DRL algorithms train an agent by estimating the distribution of the expected reward of every action performed by an agent given any financial state in a simulator, also called gymnasium. …”
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