Exploring Cognitive Patterns in Credit Default Risk Management

Abstract

The study aims to encapsulate methodologies for implementing cognitive models, focusing on tactics and strategies to predict financial risks. The methodology employs general scientific methods: analysis, synthesis, classification, and bibliographic review. The topic’s significance arises from complex economic transactions, stricter banking supervision, and the need to enhance risk management. Traditional risk assessment methods are insufficient amid global financial uncertainty and the rapid flow of information. Thus, innovative frameworks that autonomously process large datasets, predict risks, and provide mitigation strategies are needed. Incorporating cognitive models marks a shift towards adaptive, predictive risk management, promising better decision-making but remaining underexplored. The research’s applied value lies in mitigating risks in volatile markets.