Airstar Bank Limited, a jointly established entity between Xiaomi Corporation and AMTD Group, is a virtual bank licensed by the Hong Kong Monetary Authority.
Role Summary:
We are seeking a highly analytical and experienced Senior Manager, Risk Analytics to lead the quantitative risk management and data analytics framework for our SFC Type 1 and Type 4 regulated businesses. The successful candidate will play a pivotal role in developing risk models, designing stress testing methodologies, and automating risk reporting for our Securities Margin Financing (SMF) and Lombard Lending portfolios. This role requires a strong blend of data science capabilities, credit risk domain knowledge, and a deep understanding of HKMA and SFC regulatory requirements.
Key Responsibilities:
- Quantitative Modeling & Methodology :
- Develop, validate, and maintain quantitative models for Collateral Haircuts, Loan-to-Value (LTV) ratios, and Margin Ratios for various asset classes (equities, fixed income, funds, etc.).
- Design and implement liquidity discount models and concentration risk frameworks for the securities financing portfolio.
- Stress Testing & Scenario Analysis:
- Lead the design and execution of rigorous stress testing programs for the Margin Financing and Lombard Lending portfolios, ensuring strict compliance with the SFC’s Guidelines for Securities Margin Financing Activities .
- Perform ad-hoc scenario analysis to assess portfolio vulnerabilities during periods of extreme market volatility.
- Data Analytics & MIS Reporting :
- Drive the automation of daily/monthly credit risk reporting, margin shortfall monitoring, and portfolio health dashboards using Python, SQL, and BI tools (e.g., Tableau, Power BI).
- Transform complex risk data into actionable insights for Senior Management, ALCO, and the Risk Management Committee.
- IFRS 9 & Capital Analytics:
- Oversee the Expected Credit Loss (ECL) calculation and provisioning process for the margin loan portfolio under IFRS 9 standards.
- Support the calculation and optimization of Risk-Weighted Assets (RWA) and regulatory capital for Type 1 business exposures in accordance with HKMA Basel requirements.
- Risk System & Infrastructure Enhancement :
- Act as the business owner/project lead for the enhancement of credit risk engines and margin management systems.
- Collaborate closely with IT and Data Architecture teams to ensure data integrity, streamline data pipelines, and implement advanced risk analytics solutions.
Qualifications & Requirements:
- Education:
- Master’s or Bachelor’s degree in a quantitative discipline such as Financial Engineering, Mathematics, Statistics, Computer Science, Data Science, or Quantitative Finance. FRM, CFA, or CQF designation is highly preferred.
- Experience:
- Minimum of 8 years of relevant experience in risk analytics, quantitative credit risk, or portfolio risk management within a bank, top-tier brokerage, or financial institution.
- Proven experience in managing risk analytics for Securities Margin Financing, Lombard Lending, or Prime Brokerage businesses.
- Technical Skills:
- Advanced programming skills in Python or R for data manipulation and statistical modeling.
- Proficiency in data visualization tools.
- Familiarity with database management and large-scale data processing.
- Domain Knowledge:
- In-depth understanding of HKMA (e.g., SPM CR-G-14) and SFC regulations regarding credit risk, stress testing, and margin financing.
- Solid knowledge of financial products (equities, derivatives, fixed income) and IFRS 9 ECL modeling.
- Soft Skills:
- Strong leadership and project management skills, with the ability to lead cross-functional initiatives.
- Excellent communication and presentation skills in English and Chinese (Mandarin/Cantonese), capable of explaining complex quantitative concepts to non-technical stakeholders.
We offer competitive package to the right candidates. Interested parties please send your resume with current and expected salary by clicking the “Apply Now” button.
All information provided by applicants will be treated in strict confidence and handled confidentially for recruitment purposes only. Applicants who are not contacted within 8 weeks may consider their application unsuccessful and their data will be destroyed within 12 months.