Page 43 - CCFA Journal - Third Issue
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风控大讲堂 Risk Management Forum                      加中金融


        四．机遇与挑战                                                   4. Opportunity and Challenge

        FRTB 为定价、风控、对冲和优化风险加权资产(RWA)提                             FRTB motivates an integrated analytics platform for pricing,
        供了一个综合的平台。现在的趋势是前台(F.O.）的定价交                              risk, hedging and risk weighted asset (RWA) optimization. The
                                                                  trend  is  front  office  (F.O.)  pricing  quants  and  middle  office
        易员和中台(M.O.)的风控，产控专员将展开更紧密地合作
                                                                  (M.O.) risk quants will work more closely to deliver efficiency.
        以提高效率。此外，FRTB IMA PLA 测试将风险和财务损                           Further, FRTB IMA PLA test connects risk and finance P&L
        益分析更紧密地联系在一起。未来风控经理们可能可以借                                 more closely. In the future, risk managers will likely focus on
        助量化工具，提高合规管理的质量，减少在合格管理方面                                 less regulatory compliance related issues, but more on value-
        的人力投入，而将精力放在能使风控增值的思路和管理上。                                added risk insights and management.
        FRTB 还推动了大数据基础设施的完善，从而为下游利益                               FRTB  also  promotes  big  data  infrastructure,  which  provides
        相关者提供透明和一致的数据。这也将为未来的高级分析                                 transparent  and consistent  data for downstream  stakeholders.
                                                                  This will also potentially open many opportunities for future
        (如机器学习)的应用提供许多潜在的机会。然而，大规模
                                                                  advanced  analytics  (e.g.,  machine  learning)  applications.
        的系统集成可能会增加与大数据相关的技术风险。另外，
                                                                  However,  large  scale  system  integration  potentially  raises
        如何能时刻保持数据的质量也是一个挑战。
                                                                  technology risk related to big data. Also how to maintain data
                                                                  quality at an ongoing-basis is another challenge.
        在未来，大数据、超级计算能力、高级分析(如人工智能)
        和应用场景将推动银行基础设施和风险管理的发展。                                   In  the  future,  big  data,  super  computing  power,  advanced
                                                                  analytics (e.g., AI) and use cases will drive bank’s development

                                                                  of infrastructures and risk management.
        声明：
                                                                  Disclaimer
        本文中所表达的观点是作者观点，并不反映加拿大皇家银                                 Opinions expressed in this paper are those of the author, and do
        行(RBC)和多伦多大学（University of Toronto）的观点。                   not necessarily reflect the views of Royal Bank of Canada (RBC)
                                                                  and University of Toronto.




















                                                                  FRTB and



                                                                  Financial Crisis




                                                                  Prevention



























                                              CCFA JOURNAL OF FINANCE   DECEMBER 2020
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