Salary
≈ $25k – $61k per year (Estimated)
Location
In office (Kuala Lumpur)
Seniority
Senior
Employment
Full-Time
Overview
Company
Impact
Profile match
Headquartered in Kuala Lumpur, Malaysia, RHB Banking Group is one of the largest fully integrated financial services institutions in Southeast Asia. The group offers a comprehensive suite of conventional and Shariah-compliant financial solutions, including retail and commercial banking, investment banking, asset management, stockbroking, and general insurance. Additionally, it serves retail customers, small businesses, and large corporate clients across Malaysia and multiple regional markets, including Singapore, Indonesia, Thailand, and Cambodia.
Primary Objective :
Lead AI-enabled transformation across the Group, translating business needs into solutions that improve productivity, turnaround time, decision quality and customer experience. Combine applied AI knowledge, process re-engineering and project delivery to achieve measurable business value within the Bank’s governance framework.
Key Responsibilities :
- AI use-case assessment: Identify and prioritise opportunities across banking processes. Assess business value, data readiness, feasibility, implementation costs and risks; develop business cases and delivery roadmaps.
- End-to-end project delivery: Lead assigned AI initiatives from discovery and proof of concept through implementation and stabilisation. Manage scope, budget, milestones, dependencies, issues and change requests in alignment with PMO standards.
- Business requirements and process design: Lead workshops, process mapping and gap analysis. Translate business rules and decision logic into requirements, user stories, data needs, exception workflows and acceptance criteria, including human review checkpoints.
- AI solution and vendor evaluation: Evaluate proposed capabilities, limitations and integration needs with IT and vendors. Challenge solution logic, data assumptions, accuracy claims, scalability and total cost of ownership through evidence-based assessments and proofs of concept.
- Testing and implementation readiness: Lead business UAT and coordinate AI performance evaluation using representative data and exception scenarios. Assess output accuracy, consistency and traceability; track defects and secure relevant acceptance and go-live approvals.
- AI governance and controls: Engage Risk, Compliance, IT Security, Enterprise Architecture and data owners to address data protection, access, explainability, bias and auditability. Coordinate required assessments, independent validation where applicable, approvals and escalation of unresolved risks.
- Stakeholder and management engagement: Coordinate Business, Operations, IT, Finance, Group Procurement and vendors. Prepare clear senior management and committee materials covering recommendations, progress, costs, benefits, risks and decisions required.
- Adoption and operational handover: Drive user engagement, training and process documentation. Coordinate stabilisation and formal handover to designated system and business owners, with agreed support, monitoring and escalation arrangements.
- Benefits and continuous improvement: Establish baselines and track realised savings, capacity released, productivity, turnaround time, quality and adoption. Use performance findings and user feedback to propose controlled enhancements and reusable AI practices.
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