HK - GCB - Risk Manager (Card Risk)

HK - GCB - Risk Manager (Card Risk)

  • Primary Location: HK,Hong Kong,Hong Kong
  • Education: Bachelor's Degree
  • Job Function: Risk Management
  • Schedule: Full-time
  • Shift: Day Job
  • Employee Status: Regular
  • Travel Time: No
  • Job ID: 16039889


Description

  • Report to the Unsecured Portfolio Risk Manager to monitor and manage Unsecured portfolios performance, including Credit Card & Personal Loans 
  • Develop and formulate acquisition/ portfolio policies and conduct analysis to fine-tune the acquisition / portfolio management strategies in order to optimize risk & reward trade-off 
  • Conduct portfolio and collection management actions, such as line management, account renewal, authorization, early warning alerts, stress test and loan loss forecast 
  • Develop, monitor and optimize utilization of various credit decision tools such as Credit Scorecards, Segmentation Models, Credit Bureau attributes, Decision Engine, Basel model etc.. 
  • Participate and drive critical regulatory initiatives such as Stress Test Model development with the global modeling unit, regular stress testing & result documentation, global retail data automation project 
  • Ensure all credit processes are in compliance with company policies and requirements set out by the local as well as lead regulator through effective execution of control programs such as self-assessment, quality assurance, application audit 
  • Build and maintain high level of engagement in the unsecured portfolio risk team


Qualifications

  • Bachelor or Post-graduate degree in Business, Statistics or other related quantitative disciplines
  • Minimum 6-7 years of portfolio risk and analytics management experience in Cards and Unsecured Lending Products
  • Strong knowledge and experience in managing credit scorecards, stress testing, segmentation and Basel models
  • Self-initiative, effective communication and interpersonal skills as well as the ability to motivate others, strong sense of compliance awareness
  • Sound knowledge in SAS programming, data mining and MS word/excel/access/power-point is a basic