A SCALABLE FRAMEWORK FOR INTEGRATING SUBJECT-TO AGREEMENTS IN AUTOMOTIVE TRANSACTIONS
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Abstract
Purpose. This research investigates an innovative approach to the management of distressed assets within the U.S. automotive finance market amidst macroeconomic instability. The author proposes a scalable model for the integration of “Subject-to” transactions with short-term peer-to-peer (P2P) rental ecosystems (Turo, Getaround). Methodology. The study provides a granular analysis of the interest rate arbitrage mechanism, preserving existing low interest rates on current loans, thereby enabling the transformation of default obligations into high-yield rental assets. Particular attention is devoted to operational transparency through the utilization of third-party services and predictive AI analytics. Results. The research findings demonstrate that the Subject2 model provides a manifold increase in ROI (up to 590%) compared to traditional financing and contributes to the stabilization of the financial sector, preventing mass repossessions and protecting borrowers’ credit ratings. Practical implications. Beyond individual profitability, the research positions the Subject2 model as a strategic instrument for “Restructuring-as-a-Service”, transforming imminent defaults into stabilizing factors for the U.S. financial ecosystem. The framework addresses a matter of national economic security by preventing the systemic degradation of household creditworthiness. Value / originality. Schematic contract templates and a framework illustrating the protective attributes of the proposed model are also presented.
How to Cite
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automotive financing, Subject-to transactions, sharing economy, peer-to-peer (P2P) rentals, Turo, risk management, credit default
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