The financial security model of Kazakhstan's second-tier banks in the digital era

Abstract

In the digital era, Kazakhstan's second-tier banks face compound threats such as cyberattack penetration, vulnerable authentication systems, and liquidity imbalances triggered by high-frequency trading. To address the above risks, this study constructs a hierarchical suspicious transaction detection mechanism based on recursive least squares and clustering, embeds distributed ledgers to ensure transaction immutability, and adopts machine learning dynamic thresholds to accommodate behavioral heterogeneity. With a focus on digital resilience, this study proposes the principles of network segmentation and micro-segmentation under a zero-trust architecture, plans a migration roadmap toward post-quantum cryptography, and presents a convergence paradigm of anti-money laundering rules and smart contracts in cross-border payment scenarios.