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Smart-Contracts In Earnouts And Escrows: Reimagining M&A Dispute Mechanisms




Vidhi Gupta, LL.M., The London School of Economics and Political Science B.A. LL.B., Guru Gobind Singh Indraprastha University, India.


ABSTRACT


Earnouts and escrows are central risk-allocation mechanisms in mergers and acquisitions, yet they remain among the most litigated features of transactional practice. Recent advances in blockchain technology have prompted claims that smart contracts can automate these mechanisms, reduce post-closing disputes, and deliver a frictionless deal execution. This article critically examines these claims. It analyses the functional operation of smart contracts in the context of earnouts and escrows and evaluates their compatibility with existing principles of contract law and arbitration. Drawing on comparative jurisprudence from the United States, the United Kingdom, and Singapore, and situating the analysis within the Indian legal framework where appropriate, the article demonstrates that automation does not eliminate legal complexity but instead redistributes it. The article focusses on the challenges arising from data reliability, coding errors, jurisdictional uncertainty, and the irreversibility of on-chain execution. It argues that fully automated transactional structures are neither legally nor commercially viable in complex M&A transactions and suggests a hybrid contractual model in which smart contracts operate as subordinate performance tools within traditional legal agreements. By reframing the role of smart contracts in M&A, this article offers a realistic pathway for integrating technological innovation without undermining legal accountability and transactional certainty.



Indian Journal of Law and Legal Research

Abbreviation: IJLLR

ISSN: 2582-8878

Website: www.ijllr.com

Accessibility: Open Access

License: Creative Commons 4.0

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All research articles published in The Indian Journal of Law and Legal Research are fully open access. i.e. immediately freely available to read, download and share. Articles are published under the terms of a Creative Commons license which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

 

Disclaimer:

The opinions expressed in this publication are those of the authors. They do not purport to reflect the opinions or views of the IJLLR or its members. The designations employed in this publication and the presentation of material therein do not imply the expression of any opinion whatsoever on the part of the IJLLR.

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