Management Consultant - Centre of GenAI AML/KYC job opportunity at Accenture Plc.

Bachelor's (B.Sc.)

Singapore, Singapore

Singapore....Singapore

summarize with Ai

Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services—all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners, and communities. What will you do? About the Role Join our Risk & Compliance practice to help clients transform their Financial Crime and Fraud functions. You will design, implement, and optimize AML, CLM, and fraud management solutions leveraging advanced technology and AI/ML transformation. We are seeking a new talent to join the Consulting team where you will have the opportunity to collaborate in the Centre of GenAI setup project. Key Responsibilities Business Process Expertise & Validation Validate Functional Design Against Business Reality: Ensure that AI agent functionalities (e.g., SoW summarization, document ingestion, risk flagging) align with actual operational needs. Refine Target-State Workflows: Collaborate with BAs and design teams to iterate and validate "to-be" workflows, focusing on how the agentic AI will operate within or alongside existing teams. Exception & Edge Case Scenarios: Identify non-standard cases that require human intervention, policy exceptions, or represent high risk - essential for guiding agent behavior and fallback design. Process & Control Design Input Participate in Design Reviews: Actively contribute to changes that may be required for system/process designs agreed during workshop sessions - due to limitations in solutioning/tech architecture, and achieving balance on operational feasibility, control points, and compliance alignment. Define Business Rules & Tolerances: Help define thresholds, red flags, or business rules that the AI system will use for decisioning or escalating discrepancies. Data, Document, and Use Case Input Review and Curate SoW Examples: Provide input in generating representative SoW cases, documents, and commentary that reflect a range of real-life scenarios (e.g., creating synthetic data - coverage of scenarios that represent production data cases). Support AI Training Data Quality: Work with the AI/ML team to validate labelled data, suggest refinements, or highlight nuances in language, structure, or tone that indicate compliance issues or legitimacy concerns. Continuous Validation and Feedback Loop Participate in fine-tuning / hypercare: Provide domain feedback on early prototypes or AI behavior or evaluation results in these phases. Bridge for UAT Design: Support the definition of meaningful UAT scenarios by providing business-relevant test cases and validation expectations. Stakeholder Engagement & Communication Maintain Communication with Operations Teams: Act as the voice of end users - ensuring their pain points, regulatory constraints, and priorities are understood throughout the build process. AML Domain SME: provide insights to SoW industry practices to assist FBA and Tech team, as well as to BU.