Diederick Potgieter

英格兰银行

Diederick Potgieter是英格兰银行的保诚法规管理局的风险专家。他的职责包括ICAAP评估，压力测试和资本管理技术评论。他拥有博士学位。在数学统计数据中，他的专业包括信用风险，运营风险，集中风险，压力测试和经济资本框架。在2011年加入FSA/PRA之前，他曾担任巴克莱银行的资本建模总监。

乔斯·马丁

MathWorks

乔斯·马丁（Jos Martin）是Mathworks并行计算工具的主要架构师。在扮演数学工作中的发展角色之前，他曾在英国担任顾问，撰写了大规模的MATLAB应用程序，尤其是在金融和汽车部门中。在2000年加入Mathworks之前，他在新西兰奥塔哥大学举行了皇家学会博士后奖学金。他的研究领域是实验性玻色网凝结（BEC），这是低温原子物理学的一个分支。

Manoj Bhaskar

HSBC

Manoj Bhaskar是汇丰银行全球风险分析功能的负责人，他领导了一个负责管理整个小组风险和合规功能分析的团队。在他的角色中，他是该集团的模型风险管家，并领导了银行内部模型的各种监管启动的参与。在过去的几年中，他一直是各个行业论坛的积极参与者，也是与全球监管机构进行各种讨论的一部分。

Model Risk Management Principles for Stress Testing

In December 2017, the Prudential Regulation Authority brought forward a consultation document highlighting themes around effective model management to further initial communications in the 2017 annual concurrent stress tests. The consultation document outlines four principles, which address the need for a comprehensive governance framework, including clear identification of models and purpose, an appropriate governance structure, defined roles of stakeholders, model developers, model owners, and control functions. For model lifecycle management, key themes include development, validation, independent review, use of judgement, implementation, and the use of models supported by adequate documentation, IT systems, and appropriate levels of reporting to senior management.

在这次演讲中，Diederick Potgieter讨论了咨询文件中概述的压力测试模型风险管理的四个原则，并更广泛地提供了有关模型风险管理和治理结构的想法。

简化财务建模：从开发到批准到与MATLAB的生产

In 2018, financial institutions face significant demands to generate a multitude of models for managing risk and generating returns across diverse activities and markets. Furthermore, internal reviewers and external regulators are scrutinizing the associated model governance and management processes ever more closely. In this context, overall time to implementation has become a point of competitive advantage.

本演讲描述了Matlab^®is being used to reduce end-to-end model development time and risk through:

• Supporting smooth data preparation and modelling workflows from exploration to automation
• 实现机器学习和优化技术的实际应用
• 将自动生成的模型文档与专家见解和反馈相结合
• Bundling data, models, and documentation for internal and external review
• 简化模型部署到生产中
• Orchestrating the ongoing validation of models in service

云环境的好处：运营风险资本模型的一个例子

Giles Spungin will discuss recent work on improving and extending HSBC’s Pillar 2 operational risk model from a desktop-based process to a dynamically scalable cloud-based solution. He will examine how the model was scaled, first in serial by translating the legacy model into MATLAB^®and then in parallel running the application on the cloud, reducing the model execution time from days to hours. He will provide his thoughts on the opportunities that cloud implementation can offer financial modellers running MATLAB applications.