Digital Payments and Fraud Risk: Technological Innovations and Global Regulatory Responses

Title

Digital Payments and Fraud Risk: Technological Innovations and Global Regulatory Responses

Creator

Krishna E S, Anuram; Varghese James, Blesson

Description

In the digital age, financial crime has increased in magnitude and complexity because of high-velocity digital payments, cross-platform financial systems, and due to new forms of threat, like deepfakes and synthetic identities. Due to the increasing failure of the conventional, more rules-based methods of fraud control to detect these more sophisticated behaviours, there has arisen the need to adopt more sophisticated, technology-driven prevention methods. This paper discusses how financial-crime detection and AML/CFT processes are changing with the use of innovative tools, namely AI and machine learning analytics, privacy-preserving federated models, blockchain-based identity mechanism, and real-time digital-payment intelligence. The chapter methodologically follows the comparative case-based approach to analysis synthesising the evidence presented in regulatory publications, industry reports, and documented cases of technological deployments to define general trends, advantages, and shortcomings. The results indicate that technology-enabled systems are much more effective in detecting fraud, presenting few false positives, enhancing identity assurance, and sharing across institution intelligence at a faster rate as compared to traditional systems. This paper concludes that responsible AI architecture, real-time data network integration, and regulatory cooperation are essential to establishing resilient, future-ready models that will be able to defend financial ecosystems against the changing threats of the digital era. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Source

Contributions to Finance and Accounting;Volume;Part F2026;pp.55-82

Date

01-01-2026

Publisher

Springer Nature

Subject

Anti-money laundering (AML); Artificial intelligence (AI); Counter-terrorist financing (CFT); Digital fraud; Financial crime detection; Machine learning analytics

Coverage

Krishna E S A., Department of Global Finance & Analytics, Christ University, Pune, India; Varghese James B., Department of Commerce, Christ University, Pune, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 27306038;

Format

online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1007/978-3-032-20198-0_3

https://www.scopus.com/pages/publications/105040173217?origin=resultslist