Scholarlink

This article analyses the Dewan Housing Finance Corporation Ltd. (DHFL) ₹34,000-crore scam by a mixed-methods case-study method combining quantitative financial forensics and qualitative document analysis. We construct a panel dataset (2010–11 to 2020–21) of DHFL and eight peer NBFCs/HFCs to calculate liquidity, leverage, and asset-quality ratios and apply ANOVA and stress-testing to segregate DHFL’s anomalies. NVivo-aided thematic coding of regulatory notices, forensic audit reports (notably the 2019 draft by KPMG), and media investigations brings to light patterns of shell-company lending, overrides of audits, and lagging enforcement. Patterns of findings reflect extreme liquidity volatility (CV > 160%), unsustainable debt-equity levels, and a spike in NPAs in FY2017–18, temporally coincident with fraudulent routing of loans. We cover implications for NBFC risk management—dynamic dashboards of liquidity, strict due diligence on counterparties, and compulsory forensic audits—and suggest policy reforms: automatic outlier detection, regulator data-sharing across borders, and greater whistle-blower protection. This research adds a replicable framework for fraud detection in early stages in NBFCs in emerging markets and feeds into structural reforms to pre-empt future mega-frauds.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A Mixed‐Methods Case Study of the DHFL ₹34,000-Crore Scam: Governance Failures, Financial Forensics, and Regulatory Implications

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Elija Borkute,
  • Deepak S. Sharma,
  • Kajal Salampuriya

摘要

This article analyses the Dewan Housing Finance Corporation Ltd. (DHFL) ₹34,000-crore scam by a mixed-methods case-study method combining quantitative financial forensics and qualitative document analysis. We construct a panel dataset (2010–11 to 2020–21) of DHFL and eight peer NBFCs/HFCs to calculate liquidity, leverage, and asset-quality ratios and apply ANOVA and stress-testing to segregate DHFL’s anomalies. NVivo-aided thematic coding of regulatory notices, forensic audit reports (notably the 2019 draft by KPMG), and media investigations brings to light patterns of shell-company lending, overrides of audits, and lagging enforcement. Patterns of findings reflect extreme liquidity volatility (CV > 160%), unsustainable debt-equity levels, and a spike in NPAs in FY2017–18, temporally coincident with fraudulent routing of loans. We cover implications for NBFC risk management—dynamic dashboards of liquidity, strict due diligence on counterparties, and compulsory forensic audits—and suggest policy reforms: automatic outlier detection, regulator data-sharing across borders, and greater whistle-blower protection. This research adds a replicable framework for fraud detection in early stages in NBFCs in emerging markets and feeds into structural reforms to pre-empt future mega-frauds.