AI/ML Applications in Payments Risk Management for the SMB Finance Sector

The integration of Artificial Intelligence and Machine Learning technologies is fundamentally reshaping risk management in the Small and Medium-sized Business (SMB) payments sector. Traditional risk assessment methods are being replaced by intelligent AI-driven systems that offer greater accuracy, adaptability, and operational efficiency. These AI-driven solutions enable superior fraud detection, streamlined KYC/AML processes, and real-time anomaly detection by processing large volumes of transaction data instantaneously. Beyond enhanced security, they deliver measurable improvements in operational efficiency and regulatory compliance. Implementation challenges are addressed through strategic data architecture design, model selection, and integration frameworks. As AI/ML technologies continue to evolve, they promise to further advance risk detection capabilities, regulatory alignment, and scalable security within SMB payments.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-12
DOI
https://doi.org/10.5281/zenodo.15870359
Primary Topic
Financial Distress and Bankruptcy Prediction
Type
article
Field-Weighted Citation Impact
0.00
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article

AI/ML Applications in Payments Risk Management for the SMB Finance Sector

Zenodo (CERN European Organization for Nuclear Research)
Financial Distress and Bankruptcy Prediction
article

AI/ML Applications in Payments Risk Management for the SMB Finance Sector

article en

Abstract

The integration of Artificial Intelligence and Machine Learning technologies is fundamentally reshaping risk management in the Small and Medium-sized Business (SMB) payments sector. Traditional risk assessment methods are being replaced by intelligent AI-driven systems that offer greater accuracy, adaptability, and operational efficiency. These AI-driven solutions enable superior fraud detection, streamlined KYC/AML processes, and real-time anomaly detection by processing large volumes of transaction data instantaneously. Beyond enhanced security, they deliver measurable improvements in operational efficiency and regulatory compliance. Implementation challenges are addressed through strategic data architecture design, model selection, and integration frameworks. As AI/ML technologies continue to evolve, they promise to further advance risk detection capabilities, regulatory alignment, and scalable security within SMB payments.

Zenodo (CERN European Organization for Nuclear Research)
Indian School of Business (IN)
Peace, Justice and strong institutions
Openalex Percentile: Top 42%
Financial Distress and Bankruptcy Prediction
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