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The role leads fraud data analytics within UOB’s Group Compliance function, using transaction data, analytical models, dashboards and investigative insights to identify emerging fraud risks and improve controls. Candidates are expected to hold a degree in data science, statistics, computer science, finance or a related discipline, with substantial experience in fraud analytics, financial crime, risk management or banking. Strong skills in SQL, Python, SAS, visualization tools and data interpretation are likely required, together with knowledge of fraud typologies, regulatory expectations and banking operations. The successful candidate should be comfortable managing senior stakeholders, presenting clear recommendations, leading analytical initiatives and working across technology, operations, compliance and business teams.
United Overseas Bank (UOB) is a major Singapore-headquartered financial group with operations across Singapore, Malaysia, Indonesia, Thailand, Vietnam, China and other international markets. Founded in 1935, the bank provides personal financial services, commercial and corporate banking, transaction banking, wealth management, investment banking and treasury services. UOB serves individuals, businesses, institutions and multinational companies through branches, digital platforms and specialist teams. Its regional strategy focuses on Southeast Asia, supported by investments in digital banking, data capabilities, cybersecurity, risk management and customer experience. The Group Compliance function helps protect the bank from fraud, money laundering, sanctions breaches and other regulatory risks. UOB is a well-established employer for banking, technology, analytics, risk and compliance professionals, offering opportunities in a highly regulated and internationally connected financial-services environment.
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