The financial market stress of 2008, triggered by the collapse of Lehman Brothers, underscored the critical need for efficient collateral management in financial transactions. This research focuses on developing and simulating a blockchain platform designed to automate the collateral value adjustment in securities lending transactions, where the key stakeholders include financial institutions, market participants, and regulatory bodies. The platform proposes innovative transaction flows and algorithms to manage collateral automatically, significantly making risk management more effective and reducing administrative costs. The study’s methodology includes 1) designing a blockchain platform for automated collateral management, 2) developing and testing collateral value adjustment algorithms, and 3) conducting case studies with real stock and bond price data to evaluate the platform’s effectiveness. A notable outcome of this research is the reduced credit risk and liquidity compared to traditional procedures, based on the benefit of collateral diversification enabled by the automated algorithms employing multiple tokens as collaterals. This research contributes to the field of transdisciplinary engineering by integrating financial and technological disciplines, particularly in leveraging blockchain technology for financial applications. Furthermore, the study reflects on broader societal impacts, such as improving the efficiency and security of financial transactions, potentially stabilizing market volatility, and offering insights for policy-making in sound and robust settlement systems.