India’s digital lending market is projected to reach USD 515 billion by 2030 and is increasingly spread by algorithmic credit scoring systems. These are the statistical models that ingest vast datasets and produce a single numerical decision outcome regarding the eligibility of the credit to the person. The convenience offered by these systems is real. However, these systems have raised the problem of the inability to justify adverse credit decisions and the inability of the lender’s own staff to provide meaningful explanations for such decisions. This paper examines the consequential doctrinal question of whether India’s existing legal framework, as provided in the Credit Information Companies (Regulation) Act 2005, the Reserve Bank of India (Digital Lending) Directions 2025, RBI’s Fair Practices Code, and the Digital Personal Data Protection Act, 2023 has efficacy to enforce right to explanation for adverse algorithmic credit decisions. Through this doctrinal analysis of primary legal sources and comparative reference to the European Union’s General Data Protection Regulation and the United States’ Equal Credit Opportunity Act framework, the paper suggests that India suffers from a structural “explanatory deficit”. This gap is between the frequency and consequence of automated credit decisions and the available legal remedy. The paper further argues on the deficit raises constitutional concerns. The denial of an intelligible reason for a credit refusal implicates the guarantee of non-arbitrariness under Article 14 and the right to have economic dignity and livelihood under Article 21 of the Constitution of India. The paper concludes with targeted legislative and regulatory recommendations, which includes the mandatory adverse action notice requirement, sectoral algorithmic auditability standards, and an independent credit grievance adjudicatory mechanism.