Analytical models for financial risk assessment based on behavioral finance

In the context of increasing instability in financial markets and the influence of psychological factors on financial deci-sion-making, traditional risk assessment methods prove to be insufficiently effective. Behavioral finance, which integrates psy-chological aspects into financial models, allows for a deeper understanding of the mechanisms behind risk formation and ena-bles the prediction of market participants' behavior. The aim of the article is to analyze modern analytical models for financial risk assessment based on the principles of behavioral finance and to develop an integrated model that combines key indicators of behavioral biases to improve forecasting accuracy in unstable market conditions.The research employs the following meth-ods: dialectical method, systems analysis, comparative analysis, and economic modeling. The article substantiates the necessity of incorporating behavioral indicators into risk assessment models, such as overconfidence, loss aversion, emotional instability, and other cognitive biases. The study confirmed that models augmented with cognitive bias indicators more adequately reflect the actual level of risk compared to classical approaches, especially under conditions of high market volatility.