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This book examines the structural asymmetries embedded in contemporary consumer credit systems. Trust-essential to economic exchange-is increasingly withheld from borrowers while demanded of them. Lenders operate with minimal visibility or accountability; borrowers must navigate opaque infrastructures, absorb unilateral judgments, and bear the consequences of exclusion. Over the past two decades, credit markets have expanded through algorithmic risk assessment and automated decision-making. Yet the cost of evaluating 'creditworthiness'-and the entrenchment of risk-based pricing-has deepened exclusion for those experiencing financial difficulty. Surveillance-based scoring systems discipline borrower behaviour, obscure hardship, and produce reputational harm that reverberates across households and public institutions. At the centre of the book is the Trust Intelligent framework: a seven-domain model for diagnosing and redesigning trust-power configurations in credit relationships. It operationalises trust to reduce systemic risk, improve decision accuracy, and restore borrower agency. Grounded in empirical evidence, the framework supports practical reforms-integrating contextual data into credit files, rendering lender conduct visible, and establishing multistakeholder oversight of algorithmic systems. Rather than accepting the trajectory of deeper data extraction and one-sided surveillance, the book proposes a reciprocal model of information exchange-one that improves outcomes and embeds mutual accountability. It offers a blueprint for reform that is both conceptually rigorous and institutionally actionable. This is a book for those who design, regulate, and critique credit systems: lenders, credit reference agencies, financial regulators, consumer advocates, and scholars of trust, governance, and institutional design. Drawing on economics, sociology, political science, and organisational studies, it presents a multidisciplinary account of how trust can be rebuilt-within and beyond consumer credit.