Apply now »

Vice President, Fraud Analytics, Group Compliance

Posting Date:  25 May 2023

Raffles (City Area), Singapore, 048624

Company:  United Overseas Bank Ltd

About UOB

United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values – Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers.

About the Department

The Compliance function is a strategic partner and a trusted business enabler to the Board and senior management. It is our responsibility to ensure that the Group continuously fulfils its regulatory obligations in today’s tight and dynamic regulatory landscape. To do that, we work closely with internal stakeholders to identify and to assess regulatory risks. This collaboration also includes developing practical solutions that integrate regulations into operational requirements as well as actively shaping and promoting stronger compliance culture and literacy in the Bank.

Job Responsibilities

We are seeking an experienced and highly motivated Fraud Analytics Specialist to join our Group Compliance department. The ideal candidate will have a strong background in data analysis, risk management, and financial services, with a focus on fraud detection and prevention. Experience with Python and big data analytics tools such as Hive, Spark, and Impala is essential.

  • Support the development and implementation of a comprehensive fraud analytics strategy to identify, assess, and mitigate fraud risks across the organization.
  • Design and implement advanced fraud detection models, rules, algorithms and dashboards using big data analytics tools such as Python, Hive, Spark, and Impala.
  • Collaborate with various internal and external stakeholders to identify, evaluate and monitor emerging fraud trends and risks.
  • Monitor, analyze, and report on fraud-related data to drive continuous improvement in fraud detection and prevention efforts.
  • Assist in compliance with applicable laws, regulations, and industry good practices related to fraud prevention and detection by leveraging advanced data analytics techniques and solutions.


Job Requirements

  • Bachelor's degree in Data Science, Statistics, Finance, or a related field; a Master's degree or relevant professional certifications are a plus.
  • Minimum of 7 years of experience in the financial services industry, with at least 4 years in a fraud analytics or risk management role.
  • Proven experience in developing and implementing fraud analytics solutions
  • Able to instill strong Model Governance throughout the model development cycle.
  • Proficiency in data analysis tools and software, such as SQL, R, Python, or SAS.
  • Experience with big data analytics tools and frameworks, including Hive, Spark, and Impala.
  • Excellent analytical, problem-solving, and decision-making skills.
  • Strong communication and interpersonal skills, with the ability to collaborate effectively across various business units and functions.

Be a part of UOB Family

UOB is an equal opportunity employer. UOB does not discriminate on the basis of a candidate's age, race, gender, color, religion, sexual orientation, physical or mental disability, or other non-merit factors. All employment decisions at UOB are based on business needs, job requirements and qualifications. If you require any assistance or accommodations to be made for the recruitment process, please inform us when you submit your online application.

Apply now and make a difference.


1. Strategise
2. Engage
3. Execute
4. Develop
5. Skills
6. Experience
Apply now »