Abstract
In this paper, we investigate various areas of financial risk management, reveal theoretical foundations, model implementation, verification processes, and advanced technologies for increasing the risk for financial risk mitigation. From the basic overview of probability and statistical analysis, we investigate an important role in quantitative management of uncertainty in financial portfolios. Discussing, optimizing, and validating financial risk models, emphasizing the importance of data integrity in the model implementation. The discussion focuses on the integration of asset diversification, compliance, capital adequacy, machine learning and block chain technology. By discussing these factors, this paper provides a comprehensive overview of the current financial risk management field, emphasizing the importance of mathematical models such as var and CVaR, and the impact of technological changes to the practice of traditional risk management. Through this exploration, we are insisting on a balanced approach that combines classical theories and innovative technical solutions for the purpose of contributing to strategic decisions and supervisory management in financial risk management.
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