AI and Risk Management - Agenda

Live virtual course | Below agenda timing is in GMT

Respective time GMT / HKT:

Start: 8.30am GMT| 4.30pm HKT
Break: 9.30am GMT | 5.30pm HKT
End: 10.45am GMT | 6.45pm HKT



AI and explainability

14:00 - 15:00

  • No more “black boxes”

  • Different approaches to explainable AI

  • Why explainability helps build better models

  • How explainable models fit into a discretionary investment framework

Mark McDonald

Head of data science and analytics


Mark is Head of Data Science and Analytics for HSBC Global Research. Mark is the lead author of HSBC’s flagship quant publication, Data Matters, and is responsible for HSBC’s proprietary Risk On – Risk Off analysis, Surprise Indices, and the Little Mac FX Valuations. Mark also advises investors on building systematic models and applying machine learning techniques to financial markets. Before joining HSBC in 2006, Mark obtained a DPhil in applied mathematics from the University of Oxford. His doctoral research investigating the dynamics of correlation networks in FX markets was sponsored by the HSBC FX Strategy team.



15:00 - 15:15


Preparing data for AI/ ML

15:15 - 16:15

  • Identifying suitable data types and sources

  • Developing appropriate data foundations for AI

  • Typical challenges when managing data

    • Dataset size and quality

    • Underfitting

    • Ethics

  • Using alternative data

Dan Dixon

Artificial intelligence & machine learning innovation lead



Fraud and AML: managing financial crime with AI solutions

14:00 - 15:00

  • Understanding current evolutions of AI fraud detection and how to leverage this

  • Best practices for mitigating fraud and AML using AI 

  • Application of AI/ML to improve the analytical efficiency of fraud models

  • Identifying areas to focus AI deployment for increased effectiveness

  • Risk based approaches for internal vs. external fraud

Paul Bilokon

Chief executive office & founder




15:00 - 15:15


AI ethics and conduct

15:15 - 16:15

  • Challenges of algorithmic and AI fairness in financial services

  • Possible introduction of bias throughout model development lifecycle

  • Key ethics indicators and calculating trade-offs between objectives

  • Effects of unethical AI models 

    • Reputation

    • Conduct 

  • Mitigating risk through clear practices and safeguards

Jun Xu

Director of machine learning engineering

Standard Chartered Bank


Model risk management for AI

14:00 - 15:00

  • Implication of artificial intelligence on MRM

  • Applying traditional model risk management frameworks to AI applications

  • Model risk governance across the AI model lifecycle

  • Complexity of models and risk awareness

  • Validation processes for AI models

Philipp Rindler

Head of artificial intelligence models validation




15:00 - 15:15


AI and operational risk

14:00 - 15:00

  • Definition and rules

  • Opportunities and risks

  • Principles and approach

  • Governance & controls

David Phan Dinh

Group head of operational risk

Resolution Life


AI implementation roadmap

14:00 - 15:00

  • Matching the use case to the process and scaling across

  • Identifying skill shortages

  • Creating a holistic AI strategy and embedding it in your risk culture

  • Ensuring transparency and accountability at each stage

  • Creating a culture that supports AI adoption and implementation

Dr Juergen Rahmel

Head of digital, technology and innovation, compliance


Dr. Juergen Rahmel received his PhD (Artificial Intelligence) in Germany for research covering various applications of Artificial Intelligence and Machine Learning. Dr. Rahmel has gained extensive experience in the international financial sector, in roles as Director, Head of IT and Programme Manager of global initiatives for multinational banks. He served as Chief Digital Officer for HSBC Germany and currently is the Head of Digital, Technology and Innovation for Compliance APAC, HSBC. Dr. Rahmel holds an MBA in International Management and also lectures on Financial Technology at the University of Hong Kong (HKU).



15:00 - 15:15


Forward looking trends for AI

15:15 - 16:15

  • How AI is changing the face of traditional banking

  • Future trends for AI in financial services

    • Cryptocurrency

    • Green investment

    • Decentralised finance and outside competition

  • Challenges for banks transforming to become AI leading focused

  • Identifying priorities for AI moving forward

  • Encouraging AI innovation within your business

Edmund Situmorang

Chief technology officer



End of course

16:15 - 16:16

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