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AI and Financial Technology

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FinTech (Financial Technology) means "technology-enabled financial innovation." There is a strong need to improve the competitiveness of the European FinTech sector, creating a common regulatory approach across all countries. This can help encourage innovations in big data, artificial intelligence, and ...

FinTech (Financial Technology) means "technology-enabled financial innovation." There is a strong need to improve the competitiveness of the European FinTech sector, creating a common regulatory approach across all countries. This can help encourage innovations in big data, artificial intelligence, and blockchain technologies, while authorities and researchers assess their risks and potential.

Europe has a broad mosaic of regulatory landscapes and technological innovation in finance. Innovative companies and their regulating agencies must move quickly and make important decisions about emerging scientific and business opportunities, without stifling their economic potential.

Three research workshops aim to pave the way for the kick-off of a recently approved EU Horizon2020 funding scheme, which is coordinated by Prof. Paolo Giudici of the University of Pavia and aims to create a more unified European FinTech environment. To this end, the project will develop a common knowledge sharing platform that will be dynamically updated and aligned with state-of-the art R&D in financial technology, and with the evolving regulation.

The project will be delivered jointly to regulators and fintech hubs by a group of independent experts from universities that have leading research expertise in big data, artificial intelligence, blockchain technologies; leading applied expertise in risk measurement models and, specifically, in credit risk, market risk and cyber risk, along with selected fintech companies, that have distinctive professional experience in peer to peer banking, robo-advice, crypto assets, to name a few.

The present Article Collection will feature the best talks presented during the below three conferences, as well as the best papers submitted after the Call for Participation. In addition, we welcome submissions from authors writing on related topics.

1. Artificial Intelligence in Industry and Finance (3rd European COST Conference on Mathematics for Industry in Switzerland). September 6, 2018 – ZHAW Winterthur
2. The International Conference on Data Science in Finance with R. September 13-14, 2018 – WU Vienna
3. Frankfurt Summit on Network Analysis. October 25, 2018 - Frankfurt School of Finance & Management

Papers will be selected by a scientific committee formed by Paolo Giudici, Jochen Papenbrock, Peter Schwendner, Joerg Osterrieder and Ronald Hochreiter. This Article Collection is the inaugural Research Topic of the newly launched Frontiers in Artificial Intelligence journal with the specialty section "Artificial Intelligence in Finance". The authors of each selected paper will be asked to submit their papers via the Frontiers in Artificial Intelligence platform by 30 October 2018. Note that being selected is not a guarantee for subsequent publication; there will be a thorough referee process aimed at selecting high-quality papers, in line with the scopes of the journal.

We encourage all speakers of the three conferences, where the paper scope falls within at least one of the below categories, to prepare a solid paper for a potential selection for the journal.

Key words:
- Data pre processing
- Exploratory data analysis
- Visualisation tools
- Unsupervised models
- Distance models
- Cluster analysis
- Network models
- Community detection
- Generalised regression models
- Classification trees and random forests
- Neural networks and deep learning
- Model comparison tools
- AI decision making
- Explainable decisions
- Financial risk management
- Regtech and automatic compliance
- Suptech and automatic supervision
- Peer to peer lending
- Rating models
- Robot advisory
- Cognitive finance
- Price and returns prediction
- Portfolio asset management
- Volatility analysis
- Behavioral customer analysis
- Chatbot customer interaction detection
- Initial Coin Offerings
- Crypto asset management
- AI on blockchain data
- Fraud detection and prevention
- Cyber risk management
- Deep Learning and Quantitative Finance
- Combining Deep Learning and Machine Learning for Financial Data Analysis
- Contemporary Financial Feature Engineering for Investment Management
- Dependence and Influence in Financial Transaction Data: - Investment and Credit Portfolio, Fraud Detection
- XAI ("explainable AI") and Visualisation
- Topological, Graphical Models, Bayesian Networks, Dimensionality Reduction (TSNE), Correlations, Hierarchies, Clustering, Complex Information Filtering
- Deep Learning Graph Architectures
- Open Source, R, Python, R-Shiny, Javascript


Keywords: fintech, finance, AI, deep learning, risk


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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