Algorithmic Blockchain Tax Rebates via Central Bank Digital Currencies (CBDC) Automation

Authors

  • Dipti S. Lopes
  • Rohan Suryaprakash Tripathi
  • Ayush Vikas Singh
  • Vansh Prasanna Ail
  • Hardik Hitesh Patil
  • Om Pramod Kadam

Keywords:

Algorithmic framework, Blockchain technology, Central bank digital currency (CBDC), Distributed ledger technology (DLT), Hybrid confidential financial data sharing framework (HC-FDSF), Smart contracts

Abstract

India’s agricultural sector is the backbone of its economy, yet the current system for distributing subsidies is often plagued by corruption, “ghost farmers,” and long delays. To solve this, the research proposes a system that combines the security of blockchain with India’s new Central Bank Digital Currency (CBDC). Instead of waiting months for paperwork to be processed, this framework uses smart contracts essentially self-executing digital rules to automatically verify a farmer’s eligibility and send money directly to their digital wallet in under 15 minutes. It introduces the Hybrid Confidential Financial Data Sharing Framework (HC-FDSF), which uses advanced math to keep personal details like Aadhaar and land records private while still allowing the government to audit transactions for fairness. By removing middlemen and automating the math behind tax rebates and payouts, the system could cut fund leakages by over 95%. Although challenges like digital literacy and technological integration remain, this study provides a blueprint for a faster, more transparent financial ecosystem. Ultimately, this research shows how technology can ensure that every eligible farmer receives their entitled benefits instantly and securely.

Published

2026-07-04

How to Cite

Dipti S. Lopes, Rohan Suryaprakash Tripathi, Ayush Vikas Singh, Vansh Prasanna Ail, Hardik Hitesh Patil, & Om Pramod Kadam. (2026). Algorithmic Blockchain Tax Rebates via Central Bank Digital Currencies (CBDC) Automation. Recent Trends in Data Mining and Business Forecasting (P-ISSN: 3139-3888), 7(2), 1–13. Retrieved from https://matjournals.net/engineering/index.php/JTDMBF/article/view/3824