Sammy Wong

Sammy Wong

Assiantant Manager, Loan Management Asp @ HSBC

About Sammy Wong

Sammy Wong serves as the Assistant Manager of Loan Management Asp at HSBC Asia Pacific Risk, where he evaluates risk-weighted assets and expected loss for wholesale credit portfolios. With a Master's Degree in Financial Risk Management from The University of Glasgow, he has over nine years of experience in credit risk analytics.

Work at HSBC

Currently, Sammy Wong holds the position of Assistant Manager in Loan Management ASP at HSBC Asia Pacific Risk. He has been with HSBC since 2014, accumulating 10 years of experience in this role. His responsibilities include evaluating risk-weighted assets and expected loss for wholesale credit portfolios, ensuring compliance with group and regulatory requirements. Previously, he worked as a Performance Analyst at HSBC Asia Pacific Risk for 11 months from 2013 to 2014, where he contributed to performance analysis within the organization.

Current Role at Hang Seng Bank

Sammy Wong has been serving as the Assistant Wholesale Credit Risk Analytics Manager at Hang Seng Bank since 2015. In this role, he evaluates risk-weighted assets and expected loss for wholesale credit portfolios, ensuring adherence to both group and regulatory requirements. His expertise in credit risk analytics plays a crucial role in the bank's risk management strategies.

Education and Expertise

Sammy Wong earned a Master's Degree in Financial Risk Management from The University of Glasgow, completing his studies from 2010 to 2011. This educational background has equipped him with the necessary skills and knowledge to excel in the field of credit risk management and analytics.

Responsibilities in Credit Risk Management

In his current role at HSBC, Sammy Wong assists in preparing guidelines and conducting impact analysis on credit risk model-related issues for businesses in Hong Kong and China. He is involved in compiling regulatory reports for both internal and external monitoring purposes. Additionally, he coordinates projects related to regional credit risk models and risk rating systems, which includes defining user requirements and conducting user acceptance testing.

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