scholarly journals News and Narratives in Financial Systems: Exploiting Big Data for Systemic Risk Assessment

2018 ◽  
Author(s):  
Rickard mname Nyman ◽  
Sujit mname Kapadia ◽  
David mname Tuckett ◽  
David mname Gregory ◽  
Paul mname Ormerod ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Big Data ◽  
Systemic Risk ◽  
Financial Systems

scholarly journals News and Narratives in Financial Systems: Exploiting Big Data for Systemic Risk Assessment

2018 ◽  
Author(s):  
Rickard Nyman ◽  
Sujit Kapadia ◽  
David Tuckett ◽  
David Gregory ◽  
Paul Ormerod ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Big Data ◽  
Systemic Risk ◽  
Financial Systems

Big Data and Risk Assessment

Big Data ◽  
2014 ◽  
pp. 79-90 ◽  
Author(s):  
Eileen Ridley
Keyword(s):  
Risk Assessment ◽  
Big Data

scholarly journals International standards for combating money laundering with reference to the Republic of Serbia

2020 ◽  
Vol 62 (3) ◽  
pp. 87-104
Author(s):  
Radojica Lazić
Keyword(s):  
Risk Assessment ◽  
Money Laundering ◽  
International Standards ◽  
Financial Systems ◽  
Criminal Offenses ◽  
The Republic ◽  
Favorable Conditions ◽  
High Degree ◽  
The Impact ◽  
National Systems

Money laundering is increasingly becoming an issue of concern to the international community, as the states have realized that the harmonious activity of all international actors through the observance of the foreseen international standards is the most effective way of combating this type of crime. International documents have established a basic framework of activities for combating money laundering. This paper is focused on the analysis of the activities of international entities and their role in creating international standards in this field, as well as the impact of money laundering on various aspects of society and countries. In this connection, the paper first explains the international entities, then states their roles and all the most important international documents and then the results of the money laundering risk assessment in the Republic of Serbia with special emphasis on the criminal offenses with high degree threats for money laundering. Furthermore, it points to the importance of international entities and standards for the establishment of national systems that will be able to respond to the effects of money laundering and thereby create a successful financial system. Finally, the paper concludes that without the existence of international standards and activities of the international entities, appropriate conditions for effective combating of money laundering cannot be created, thereby providing more favorable conditions for the free flow of people and capital, as well as easier management of financial systems.

scholarly journals Security and Privacy Risk Assessment of Energy Big Data in Cloud Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhiru Li ◽  
Wei Xu ◽  
Huibin Shi ◽  
Yuanyuan Zhang ◽  
Yan Yan
Keyword(s):  
Neural Network ◽  
Risk Factors ◽  
Risk Assessment ◽  
Big Data ◽  
Data Storage ◽  
Bp Neural Network ◽  
Security And Privacy ◽  
Cloud Environment ◽  
Privacy Risk ◽  
Whole Life Cycle

Considering the importance of energy in our lives and its impact on other critical infrastructures, this paper starts from the whole life cycle of big data and divides the security and privacy risk factors of energy big data into five stages: data collection, data transmission, data storage, data use, and data destruction. Integrating into the consideration of cloud environment, this paper fully analyzes the risk factors of each stage and establishes a risk assessment index system for the security and privacy of energy big data. According to the different degrees of risk impact, AHP method is used to give indexes weights, genetic algorithm is used to optimize the initial weights and thresholds of BP neural network, and then the optimized weights and thresholds are given to BP neural network, and the evaluation samples in the database are used to train it. Then, the trained model is used to evaluate a case to verify the applicability of the model.

Systemic Risk in Financial Systems

2001 ◽  
Vol 47 (2) ◽  
pp. 236-249 ◽  
Author(s):  
Larry Eisenberg ◽  
Thomas H. Noe
Keyword(s):  
Systemic Risk ◽  
Financial Systems

Conclusion

2020 ◽  
pp. 97-102
Author(s):  
Benjamin Wiggins
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Machine Learning ◽  
Risk Assessment ◽  
Big Data ◽  
The United States ◽  
Blaise Pascal ◽  
Division Problem ◽  
The World

Can risk assessment be made fair? The conclusion of Calculating Race returns to actuarial science’s foundations in probability. The roots of probability rest in a pair of problems posed to Blaise Pascal and Pierre de Fermat in the summer of 1654: “the Dice Problem” and “the Division Problem.” From their very foundation, the mathematics of probability offered the potential not only to be used to gain an advantage (as in the case of the Dice Problem), but also to divide material fairly (as in the case of the Division Problem). As the United States and the world enter an age driven by Big Data, algorithms, artificial intelligence, and machine learning and characterized by an actuarialization of everything, we must remember that risk assessment need not be put to use for individual, corporate, or government advantage but, rather, that it has always been capable of guiding how to distribute risk equitably instead.

Sign in / Sign up

Export Citation Format

Share Document