Business Portfolio Management, Retail Assets

gradmalaysia.com; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

A financial institution is seeking an experienced professional to enhance business portfolio performance through data analytics. Responsibilities include supporting credit risk initiatives, collaborating across departments, and leveraging analytical insights to ensure portfolio quality. The ideal candidate has over 7 years in banking, with expertise in credit analytics and risk-based pricing, and strong stakeholder engagement skills. This role requires an assertive team player who is results-oriented and skilled in Excel and BI tools.

Qualifications

• More than 7 years’ experience in banking industry, with at least 5 years in Business Portfolio Management.
• Proficiency in credit data analytics and hands-on experience with scorecards.
• Strong business acumen in retail asset products and industry practices.

Responsibilities

• Leverage data and analytics to strengthen business portfolio performance.
• Support Dynamic Credit Risk Score initiative through risk models.
• Collaborate with various departments to operationalise credit scoring models.

Skills

Credit data analytics

Dynamic credit scoring

Risk-based pricing

Stakeholder engagement

Excel

Python/R

Project management

Tools

Business intelligence tools

SAS

Job description

Leverage data and analytics to strengthen business portfolio performance.

• Support Dynamic Credit Risk Score initiative by applying risk models and pricing strategies to improve acquisition quality, portfolio growth, and risk-adjusted pricing across all RAD retail products (Personal Financing, Home & Fixed Asset Financing, Vehicle Financing, Ar-Rahnu).
• Translate analytical insights into business actions, monitor portfolio profitability, and safeguard asset quality to achieve RAD’s objectives.
• Act as the execution arm of business strategy by embedding model outputs into product propositions and driving operational adoption across retail asset products.
• Collaborate with Credit Management Division, Data Analytics & AI Department, and external vendors to operationalise AI/ML-driven credit scoring models.
• Support risk-based pricing structures across retail asset products, ensuring alignment with business strategy and profitability goals.
• Analyse and monitor portfolio performance (PF, HFA, VF, Ar-Rahnu) to provide insights on risk, asset quality, and profitability.
• Prepare dashboards, analytics, and management reports with clear commentary and actionable recommendations.
• Monitor adoption of credit risk models and provide feedback for continuous improvement.
• Review system parameter configurations (pricing tables, scorecards, operational settings) to ensure desired outputs and effective operations.
• Document business requirements (BRDs), coordinate user testing, and facilitate rollout of enhancements or new models.
• Ensure compliance with internal policies, regulatory requirements, and governance standards.
• Contribute to cross-functional collaboration and continuous improvement initiatives to enhance asset quality, portfolio resilience, and operational efficiency.
• Undertake additional assignments, projects, or portfolio-related activities as delegated by management.

Job Requirements

• More than 7 years’ experience in banking industry with at least 5 years’ experience in Business Portfolio Management, particularly in Retail Lending products.
• Proficiency in credit data analytics with hands-on experience in scorecard usage, dynamic credit scoring, and risk-based pricing.
• Ability to translate statistical and Machine Learning (ML) model outputs into practical business strategies.
• Strong business acumen in retail asset products (Personal Financing, Home & Fixed Asset Financing, Vehicle Financing, Ar-Rahnu) and industry practices.
• Solid knowledge of financial and regulatory frameworks, including IFRS9/MFRS9, Probability of Default (PD), Basel standards, compliance, recovery, and finance.
• Advanced proficiency in Excel and BI/visualization tools, with working knowledge of advanced analytics (Python/R, SAS).
• Hands-on experience in project-based initiatives, particularly loan origination system implementation and enhancements, from planning to execution and delivery.
• Assertive, innovative, and highly independent team player; committed, self-motivated, resourceful, and results-oriented.
• Strong stakeholder engagement and influencing skills, with the ability to build effective working relationships.
• Capable of performing diverse functions across multiple levels internally and externally.
• Ability to multi-task, highly numerate with exceptional attention to detail, and skilled in managing expectations while working independently.