Artificial Intelligence and Machine Learning Applications in Financial Services Industry – Illustrative Case Studies

CFP
Journal
online
SUBMISSION DEADLINE
31/07/2026
JOURNAL
Managerial Finance
PUBLISHER
Emerald Publishing
GUEST EDITORS
Krishnan Dandapani, Vaidyanathan Jayarman
POSTED ON
30/03/2026

DETAILS

CALL FOR PAPERS

Artificial Intelligence and Machine Learning Applications in Financial Services Industry – Illustrative Case Studies

Journal: Managerial Finance

Publisher: Emerald Publishing

Submission Opens: 16 March 2026

Abstract Submission Deadline: 30 April 2026

Full Paper Submission Deadline: 31 July 2026


Introduction

The financial services industry is going through an extraordinary transition due to developments in Artificial Intelligence (AI) and Machine Learning (ML) models. Many new products and processes have led to enhanced efficiency across the sector. This Special Issue aims to document several of these applications as illustrative case studies so that others may learn, gain a competitive edge, and promote responsible management.

The special issue will serve as an educational and learning guide for managers, practitioners, and researchers working at the intersection of AI, ML, and financial services.


Scope & Significance

As AI and ML continue to reshape the financial services landscape, there is a growing need to capture real-world applications through well-documented case studies. This Special Issue bridges the gap between theoretical advancements and practical implementation — offering concrete, illustrative examples of how AI and ML are being deployed across financial institutions, fintech firms, and related sectors.

Contributions are welcomed from academics, industry practitioners, and researchers who can offer empirically grounded, practice-oriented insights into the transformative role of AI and ML in financial services.


List of Topic Areas

Manuscripts are invited on themes including, but not limited to:

  1. Artificial Intelligence and its impact on the economy

  2. Machine Learning's impact on finance and financial decision-making

  3. The future of financial services in the AI era

  4. Financial industry innovation and infrastructure transformation

  5. Enhancing global wealth through AI and ML applications

  6. AI and ML in risk management and fraud detection

  7. Algorithmic trading and AI-driven investment strategies

  8. AI applications in credit scoring, lending, and underwriting

  9. Regulatory technology (RegTech) and AI-driven compliance

  10. Customer experience and personalization in financial services through AI

  11. Case studies of responsible AI and ethical ML deployment in finance


Guest Editors

Dr. Krishnan Dandapani Florida International University, Miami, FL, USA 📧 Dandapan@fiu.edu

Dr. Vaidyanathan Jayarman University of Texas – Dallas, Texas, USA 📧 Vaidy@UTDallas.edu


Key Deadlines

📅 Manuscript Submission Opens: 16 March 2026

📝 Abstract Submission Deadline: 30 April 2026

⏰ Full Paper Submission Deadline: 31 July 2026


Submission Guidelines

Submissions are made through ScholarOne Manuscripts, the official submission platform of Emerald Publishing. Authors must strictly follow the journal's author guidelines.

When submitting, select "Artificial Intelligence and Machine Learning Applications in Financial Services Industry" from the special issue drop-down menu at the appropriate step in the submission process.

⚠️ Submitted articles must not have been previously published, nor should they be under consideration for publication elsewhere while under review for this journal.

For author guidelines and to submit your manuscript, visit the official journal page on the Emerald Publishing website and access via ScholarOne Manuscripts.


About the Journal

Managerial Finance, published by Emerald Publishing, is a leading peer-reviewed journal focusing on the theory and practice of finance and financial management. It provides a platform for academics and practitioners to share research on financial decision-making, corporate finance, investment, and related areas across global markets.


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