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Springer JBFT 2021 : Journal of Banking and Financial Technology: Special issue on AI/ML Technologies in Banking and Finance


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Submission Deadline Aug 25, 2021
Categories    artificial intelligence   machine learning   finance   economics

Call For Papers

Journal of Banking and Financial Technology: Special issue on AI/ML Technologies in Banking and Finance

## ABOUT ##
We solicit original and high quality articles for a special issue on ‘AI/ML Technologies in banking and finance’ in the Journal of Banking and Financial Technology published by Institute for Development and Research in Banking Technology (IDRBT) and Springer. This special issue aims at providing a platform for the dissemination of the theoretical foundations and the state-of-the-art applications of AI/ML (subsuming computational intelligence, deep learning and reinforcement learning) in banking and finance. Original studies, empirical research articles as well as survey & position articles welcome. The articles should be of general interest to professors, researchers, students, cyber security & marketing professionals and practioners.

Submissions that are extensions of the works published elsewhere must have a major update to the extent of 50% of new material. Authors are requested to attach the previously published articles and a document detailing the enhancements, improvements made in the journal’s version. All submitted papers will be subject to a rigorous peer-review process that looks into the relevance, scientific quality, significance, originality, style and clarity.

Paper Submission Deadline August 25, 2021

Topics of this special issue include but are not limited to:

- Customer relationship applications such as customer segmentation, credit scoring, loan default modelling, loan collections modelling, customer churn prediction, market basket analysis (aka crosssell/up-sell), customer lifetime value modelling, customer sentiment analysis, anti-money laundering etc.
- Non-CRM applications including bankruptcy prediction, New branch/ATM establishment, ranking of banks, stock exchanges and insurance companies w.r.t profitability, productivity and financial health.
- AI/ML in RegTech and SupTech
- Offline and cyber fraud detection (including card fraud, insurance claim fraud detection, spam, phishing, malware, ransomware, DDoS, insider threat detection)
- Stock Market manipulation detection
- Stock market trading strategies using AI/ML
- High frequency/Algorithmic trading with AI/ML
- Symbiotic relationship between AI/ML in cloud technologies
- Financial forecasting including interest rate/old price/crude oil/macroeconomic variables/FOREX/cryptocurrency price/ATM cash withdrawal forecasting
- Deep learning for banking, finance and insurance applications
- Interplay between big data analytics and AI/ML (subsuming deep learning)
- Role of AI/ML in financial inclusion
- AI/ML and FinTechs
- Fairness, Ethics, Accountability, Trust in AI/ML
- Adversarial ML and applications in BFSI
- Developing human interpretable, explainable AI/ML algorithms
- Federated Learning and applications in BFSI
- End-to-end ML lifecycle and applications
- Barriers to AI/ML implementation and other managerial issues

## Guest Editors ##
- Vadlamani Ravi, IDRBT, Hyderabad, India;
- Ruppa Thulasiram, University of Manitoba, Canada;
- Periklis Gogas, Democritus University of Thrace, Greece;
- Natraj Raman, JP Morgan AI Research, London, UK;
- Chilukuri Mohan, Syracuse University, USA


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