Manager, Threat Intelligence & Analytics

To strengthen the organisation’s defence against fraud and scams through data-driven threat intelligence and analytics. This role is pivotal in shaping an intelligence-led fraud management strategy, providing actionable insights to anticipate, prevent, and detect emerging threats, and ensuring the bank maintains a robust defense against increasingly sophisticated financial crimes. Job Responsibilities:Drive the transition to an intelligence-led, data-driven approach to fraud prevention, detection, and responseIdentification, analysis, and disruption of emerging mule networks, scam typologies and new fraud vectors Design and develop models to detect fraud in collaboration with data science and analytics teamTranslate intelligence and typology insights into actionable risk indicators and detection logic Collaborate with law enforcement, industry groups and regulators to exchange intelligence and strengthen the bank’s threat postureReview and optimise fraud rule policies/parameters across systems for CASA and Cards to effectively identify potential fraud or scam activities.Conduct regular rule performance reviews, ensuring thresholds and parameters remain calibrated to evolving risk typologies.Collaborate with relevant teams and to ensure rules alignment with industry standard and regulatory expectationsCompile accurate, timely and insightful fraud reports to regulators and senior managementJob Requirements:Degree in Cybersecurity/Fraud-related/Compliance, Data Science/Analytics, Banking/Finance, Business IT or other relevant degreeAt least 5 years of experience in fraud risk management, intelligence or analytics, preferably in banking or financial services Experience working with regulatory bodies (e.g. MAS), law enforcement agencies and cross-industry fraud intelligence networks Strategic thinker with strong analytical and investigative mindsetDeep understanding of fraud ecosystems, scam networks, and digital threatsExcellent stakeholder management and communication skillsProficiency in data analytics tools (e.g., Python, SQL, Power BI, SAS) and knowledge of AI/ML model governance *Only shortlisted candidate will be notified.