arbiter
JournalsPricingAccount

AI-driven RegTech and Crypto Laundering: The Dilemmas Between Financial Crime Prevention and Privacy Law

Kharisma Fatmalina Fajri et al.

Journal of Interdisciplinary Economics2026https://doi.org/10.1177/02601079261417007article
AJG 1ABDC C
Weight
0.50

What the paper says

Cryptocurrency, as a transformative financial innovation, has reshaped global financial ecosystems while simultaneously introducing new risks of money laundering. To address these challenges, regulators increasingly employ AI-driven Regulatory Technology (RegTech) to strengthen anti-money laundering (AML) enforcement. Yet, this study reveals that the primary aim of crime prevention through RegTech generates unintended consequences by colliding with personal data protection laws, creating a profound regulatory and ethical paradox. Employing an exploratory qualitative approach, this study integrates semi-structured interviews with RegTech providers and document analysis, analysed through Braun and Clarke’s thematic framework. Findings reveal three central themes: the conflict between RegTech and personal data protection, the imbalance between AML requirements and data subject rights, and the dilemma of the presumption of innocence in RegTech implementation. Theoretically, the study contributes by applying Situational Crime Prevention (SCP) and Solove’s Taxonomy of Privacy to conceptualise how Know Your Data (KYD) mechanisms, while effective in deterring crime, risk infringing individual privacy. Practically, the results emphasise the urgent need for regulators, RegTech developers, and Crypto FinTech institutions to design adaptive governance frameworks that balance AML compliance with data protection principles. This study thus establishes a foundation for future research into privacy-enhancing technologies and equitable data governance, advancing interdisciplinary discourse at the intersection of AI, financial regulation, and digital rights. JEL Codes: G18, G28, K24, O33, K42

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1177/02601079261417007

Or copy a formatted citation

@article{kharisma2026,
  title        = {{AI-driven RegTech and Crypto Laundering: The Dilemmas Between Financial Crime Prevention and Privacy Law}},
  author       = {Kharisma Fatmalina Fajri et al.},
  journal      = {Journal of Interdisciplinary Economics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/02601079261417007},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

AI-driven RegTech and Crypto Laundering: The Dilemmas Between Financial Crime Prevention and Privacy Law

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.