Digital Transformation of Anti-Money Laundering Business Processes: A Capability-Oriented Perspective on Analytics-Driven AML

Ajša Lutar; Simona Sternad Zabukovšek

doi:10.2478/ngoe-2026-0018

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Digital Transformation of Anti-Money Laundering Business Processes: A Capability-Oriented Perspective on Analytics-Driven AML

Naše gospodarstvo/Our economy

Volume 72 (2026): Issue 3 (September 2026)

By: Ajša Lutar and Simona Sternad Zabukovšek

Open Access

|Oct 2026

Abstract

Anti-money laundering (AML) is becoming an increasingly information-intensive business process requiring advanced analytical support for effective organisational decision-making. Although previous research has extensively investigated machine learning, graph analytics, and other analytical methods, existing studies largely examine these approaches as isolated technological solutions. This conceptual study adopts a business process perspective. It develops a capability-oriented framework for analytics-driven AML by synthesizing digital transformation, business process management, business analytics, and AML literature. This perspective conceptualises the digital transformation of AML as the coordinated development of interconnected organisational analytical capabilities embedded within business processes. The study contributes by integrating previously fragmented research streams into a coherent, management-oriented perspective. It provides a conceptual foundation for future empirical research and practical guidance for financial institutions pursuing analytics-driven AML transformation.

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Articles in this issue

DOI: https://doi.org/10.2478/ngoe-2026-0018 | Journal eISSN: 2385-8052 | Journal ISSN: 0547-3101

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Language: English

Page range: 113 - 136

Submitted on: Jul 1, 2026

Accepted on: Aug 1, 2026

Published online: Oct 8, 2026

Published in print: Sep 1, 2026

Published by: University of Maribor

In partnership with: Paradigm Publishing Services

Keywords:

Anti-money laundering (AML),

Digital transformation,

Business process management (BPM),

Business analytics,

Organisational analytical capabilities Analytics-driven AML

JEL:

M15,

G21,

G28

Related subjects:

Business and economics,

Political economics,

Economic policy,

Business management,

Management, organization, corporate governance,

Mathematics and statistics for economists,

Statistics

© 2026 Ajša Lutar, Simona Sternad Zabukovšek, published by University of Maribor
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 72 (2026): Issue 3 (September 2026)