Job Responsibilities:

• Provide leadership in the first line of defence for the end-to-end financial crime transformation strategy and multi-year roadmap across AML, Sanctions and KYC/CDD and collaborate with the controls teams to contribute to the assessment of current controls, data, systems and operating model; define target state and prioritized delivery plan.

• Sponsor and drive the delivery of AI/technology-enabled controls, automation/robotics use cases and oversee the technology implementation lifecycle requirements, data readiness, model development, validation, testing, deployment, adoption, and continuous performance optimization.

• Provide senior oversight of financial crime risks across high-risk corridors and complex cross-border payment flows.

• Collaborate with the Payments teams to lead the enhancement of controls for crypto/digital asset-related activity (e.g., wallet risk, on/off-ramp typologies, Travel Rule considerations).

• Scope risk and control expectations for FinTech partners, platform models, and correspondent banking relationships.

• Partner with the Business and Global Financial Crime Compliance to simplify and streamline the financial crime framework and Financial Crime Committee governance (structure and content), acting as a central intermediary to enable a more efficient, sustainable financial crime operating environment.

• Collaborate with Sanctions, Transaction Monitoring, Fraud Operations and Compliance to strengthen key elements of the Financial Crime Compliance framework and enhance consistency across the firm.

• Define and maintain financial crime governance frameworks, support the development of business risk guidelines, KRIs/KPIs, MI dashboards, and reporting to senior management committees; deliver continuous modernization of policy and standards across AML/CTF, sanctions and KYC/CDD — explicitly incorporating AI/automation governance (e.g., transparency, accountability, human-in-the-loop).

• Act as a senior point of contact for regulators, auditors, and internal assurance functions, as required; ensure robust documentation and explainability of models and automation decisions, including ongoing monitoring and change control.

• Set performance expectations and drive measurable improvements in effectiveness and efficiency of the financial crime operations models (e.g., detection quality, false positives, case cycle times, etc.) and ensure strong integration between KYC/CDD data, monitoring, screening, investigations, and reporting workflows; influence resource allocation and target operating model design to optimize effectiveness and efficiency, focusing human effort on highest-value of investigative work.

• Lead and develop high-performing, multi-disciplinary teams (including operations, data science, technology, product) and build organizational AI/ML capability and embed a culture of robust proactive financial crime risk management; provide thought leadership internally and externally (governance forums, industry groups, working groups), including horizon scanning for typologies, regulation and technology.

Required qualifications, capabilities, and skills

• Previous experience in financial crime risk roles within regulated financial services, payments, FinTech, or relevant advisory/consulting — including senior leadership accountability.

• Deep expertise across AML, sanctions, fraud, and KYC/CDD, including transaction monitoring and screening design/oversight.

• Strong, practical understanding of cross-border payments risk, high-risk corridors and typologies.

• Proven experience engaging with regulators and auditors, including leading examinations, preparing senior governance reports, and delivering remediation.

• Demonstrable experience in designing and implementing risk appetite, governance, and control frameworks across multiple jurisdictions.

• Clear evidence of delivering complex change programmes, including designing/building/deploying/scaling of new controls or platforms.

• Strong working literacy in AI/ML, advanced analytics, and automation as applied to financial crime risk (model performance, thresholds, monitoring, validation, controls and documentation).

• Experience partnering with technology, data science, and product teams to translate risk requirements into scalable systems and operating processes.

• Clear communicator, able to explain complex typologies and AI/ML concepts to technical and non-technical audiences.

• Adaptive execution with robust controls, resilient, adaptable, and effective in ambiguity and pace, balancing innovation with robust control design.