Accountability and Liability in AI-Related Financial Regulatory Sandboxes: A Comparative Legal Analysis

Regulatory sandboxes have evolved from specialised FinTech tools into broader mechanisms of regulatory experimentation. As artificial intelligence (AI) applications become embedded in credit decisioning, payment-fraud detection, identity verification, crypto-asset compliance, customer-facing advice and supervisory analytics, sandbox design increasingly affects how legal and institutional responsibility is allocated among regulators, participating firms, technology vendors and users. This article provides a comparative doctrinal and institutional analysis of accountability and liability in AI-related financial regulatory sandboxes. It clarifies the relevant AI modalities, distinguishes accountability (answerability and enforceability during sandbox participation) from liability (contractual, tort/product and regulatory/public law responsibility after harm), and maps framework-level safeguards across the European Union, the United Kingdom, Singapore, Norway and Hungary. The analysis does not seek to measure sandbox effectiveness empirically. Instead, it examines how publicly available legal and regulatory materials structure the allocation of duties before, during and after sandbox testing. The article shows that sandboxes generally do not operate as liability shields. Their legal significance lies in reallocating ex ante accountability duties—documentation, disclosure, monitoring, human oversight and exit planning—while preserving baseline liability rules. An Accountability and Liability Protocol is proposed to clarify roles, protect baseline consumer rights, support evidentiary traceability and connect sandbox learning to enforceable post-sandbox obligations.