DocumentCode :
3722503
Title :
Meta Meta-Analytics for Risk Forecast Using Big Data Meta-Regression in Financial Industry
Author :
Hevel Jean-Baptiste;Meikang Qiu;Keke Gai;Lixin Tao
Author_Institution :
Dept. of Comput. Sci., Pace Univ., New York, NY, USA
fYear :
2015
Firstpage :
272
Lastpage :
277
Abstract :
The growing trend of the e-banking has driven the implementations of big data in financial industry. Data analytic is considered one of the most critical aspects in current economic development, which is broadly accepted in various financial domains, such as risk forecast and risk management. However, gaining an accurate risk prediction is still a challenging issue for current financial service institutions and the hazards can be caused in various perspectives. This paper proposes an approach using meta meta-analytics for risks forecast in big data. The proposed model is Meta Meta-Analytics Risk Forecast Model (MMA-RFM) with a crucial algorithm Regression with Meta Meta-Analytics Algorithm (RMMA). The proposed schema has been examined by the experimental evaluation in which it performs an optimized performance.
Keywords :
"Analytical models","Big data","Mathematical model","Prediction algorithms","Risk management","Predictive models","Reliability"
Publisher :
ieee
Conference_Titel :
Cyber Security and Cloud Computing (CSCloud), 2015 IEEE 2nd International Conference on
Type :
conf
DOI :
10.1109/CSCloud.2015.69
Filename :
7371493
Link To Document :
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