Meta Meta-Analytics for Risk Forecast Using Big Data Meta-Regression in Financial Industry

Hevel Jean-Baptiste, Meikang Qiu, Keke Gai, Lixin Tao
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引用次数: 11

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.
金融行业大数据元回归风险预测的元分析
电子银行的发展趋势推动了金融行业大数据的实施。数据分析被认为是当前经济发展中最关键的方面之一,在风险预测和风险管理等各个金融领域被广泛接受。然而,对当前的金融服务机构进行准确的风险预测仍然是一个具有挑战性的问题,风险的产生可能是多方面的。本文提出了一种基于元分析的大数据风险预测方法。本文提出的模型是Meta- Meta分析风险预测模型(MMA-RFM),该模型的关键算法是回归与Meta- Meta分析算法(RMMA)。所提出的模式已通过实验评估进行了检验,并取得了较好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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