AVP, Digital Credit & Data Analytics

KEY RESPONSIBILITIES

• Responsible in the development, enhancement and driving of bank statement-based credit scorecards for SME customers acquired through digital channels.
• Ensure models are statistically sound, predictive and aligned with risk appetite and business growth.
• Analyse transactional data from SME bank statements to identify key behavioural indicators and derive credit-relevant features.
• Perform segmentation and clustering to improve scorecard accuracy.
• Assist in digitizing and analysing unstructured data (e.g. bank statements) for fraud detection and cashflow analysis.
• On-going monitoring of the portfolio of Digital SME, back-testing of the credit scoring and propensity models being used within Digital SME.
• Execute proof of concept (POC) session and documentation of POC results.
• Support end-to-end automation of underwriting workflows with minimal manual intervention.
• Keep abreast of industry developments in alternative credit scoring and machine learning techniques.
• Recommend enhancements leveraging API banking or third-party data sources & etc.

JOB REQUIREMENTS

• Bachelor’s or Master’s degree in Statistics, Data Science, Economics, Finance or related field.
• At least 5-7 years of experience in credit risk modelling, scorecard development, or SME underwriting.
• Experience with digital SME leading or financial technology platforms is a strong advantage.
• Experience in working on unstructured data e.g. bank statement data or knowledge in SME lending behaviour would be an advantage.
• Experience in working with big data would be an advantage.
• Proficient in SOL, Python, R or SAS for data analysis and model building.
• Strong analytical and problem-solving skills.
• Good communication skills to collaborate with cross-functional teams.
• Detail-oriented with a proactive approach to innovation and improvement.
• Strong business environment awareness and sensitivity to business, compliance and control issues.