Optimizing Fraud Remediation through Cloud-Based Card Replacement and Credit Issuance

In the payment card industry, fraudulent transactions remain a significant risk that seeks to strike a balance between security and process efficiency. Digital payments continue to proliferate, thereby increasing the demand for effective fraud remediation. The aim of this paper is to assess the workings of fraud remediation with a specific focus on the card replacement and credit issuance processes and cloud-based systems. The study will provide best practices, technologies, and workflows adapted to agility and security in fraud claims that eliminate duplicate claims’ exposure. The paper will emphasize the role of automation, cloud-based persistent databases, and real-time fraud-detection systems able to provide scalable, secure, and efficient solutions. The exploration of damages provides a detailed design of the remediation process in financial services. The focus is placed on the operations in finding fraud detection algorithms, system design, and the database.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-27
DOI
https://doi.org/10.5281/zenodo.15318722
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Optimizing Fraud Remediation through Cloud-Based Card Replacement and Credit Issuance

Zenodo (CERN European Organization for Nuclear Research)
Imbalanced Data Classification Techniques
article

Optimizing Fraud Remediation through Cloud-Based Card Replacement and Credit Issuance

article en

Abstract

In the payment card industry, fraudulent transactions remain a significant risk that seeks to strike a balance between security and process efficiency. Digital payments continue to proliferate, thereby increasing the demand for effective fraud remediation. The aim of this paper is to assess the workings of fraud remediation with a specific focus on the card replacement and credit issuance processes and cloud-based systems. The study will provide best practices, technologies, and workflows adapted to agility and security in fraud claims that eliminate duplicate claims’ exposure. The paper will emphasize the role of automation, cloud-based persistent databases, and real-time fraud-detection systems able to provide scalable, secure, and efficient solutions. The exploration of damages provides a detailed design of the remediation process in financial services. The focus is placed on the operations in finding fraud detection algorithms, system design, and the database.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 75%
Imbalanced Data Classification Techniques
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