Financial Analysis with Artificial Intelligence, Machine Learning, Cybersecurity, and Big Data

Dear Colleagues,

Artificial intelligence, machine learning, and cybersecurity are wide-ranging branches of computer science and fast-growing fields. Artificial intelligence (AI) is the machine-powered intelligence and tasks that enable machines to learn from human experience and intelligence and also to be capable of adjusting to new inputs and to execute human-like tasks. Cybersecurity refers to the practice and set of preventative techniques used to protect the organization’s security systems, networks, data, and programs to safeguard its data against digital attacks, damage, or unauthorized access. Big Data is a concept used to describe and analyse huge amounts of structured, semi-structured, or unstructured data that comes from various sources that are vast and complex. In addition, it requires advanced analytics applications and sophisticated data-processing software. Financial crimes are crimes that involve the illegitimate conversion of the ownership of property of an individual, corporations, or governments for the personal benefit of the criminal or criminals. Financial crimes ranging from simple actions carried out by one person or small groups to large-scale operations conceived by organized criminals, criminal enterprises, or terrorism. The most common financial crimes are money laundering and terrorist financing. Financial crimes also include fraud (cheque fraud, credit card fraud, mortgage fraud, medical fraud, corporate fraud, securities fraud, insider trading, bank fraud, insurance fraud, market manipulation, payment fraud, point of sale fraud, health care fraud, etc.), tax evasion, embezzlement, forgery, counterfeiting, bribery, corruption, electric crimes, and identity theft. This Special Issue is devoted to publishing high-quality papers that involve theoretical and practical aspects related to fighting financial crime with artificial intelligence, machine learning, cybersecurity, and big data.

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

• The use of Artificial Intelligence in fighting against financial crime
• The use of machine learning in fighting against financial crime
• The use of cybersecurity in fighting against financial crime
• The use of Big Data in fighting against financial crime
• Applying Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in anti-money laundering initiatives
• Applying Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in anti-terrorist financing initiatives
• Applying Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in anti-bribery, fraud, and corruption initiatives
• Applying Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in credit analysis initiatives
• Applying Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in fighting against financial crime in banks
• Applying Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in fighting against financial crime in insurance companies
• Applying Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in fighting against financial crime and their influence on investment and financial decisions
• Applications of Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in fighting against financial crime and their influence on firms’ performance and value
• Applications of Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in fighting against financial crime in financial markets and their influence on stock price liquidity and volatility
• Applications of Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in fighting against financial crime in financial insinuations and their influence on market stability
• Applications of Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in fighting against financial crime and dynamic advertisement
• Applications of Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in fighting against financial crime and customer engagement
• Applications of Artificial Intelligence techniques, machine learning methods, cybersecurity programs, and Big Data analysis in fighting against financial crime in corporations and financial insinuations and their influence on internal efficiency
• The use of Artificial Intelligence, machine learning, cybersecurity, and Big Data in fighting against financial Crime and their influence on competing, capturing, innovating, and improving competitive advantage
• The use of Artificial Intelligence, machine learning, cybersecurity, and Big Data in fighting against financial crime and their influence on creating new revenue streams

Dr. Haitham Nobanee
Dr. Mohamed Elhoseny
Dr. Xiaohui Yuan
Dr. Noura Metawa
Guest Editors

Manuscript Submission Information

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