We are seeking a highly motivated Summer Intern – Data Analytics to support our Financial Crime Compliance team, covering Anti-Money Laundering (AML), Fraud Risk, as well as, broader regulatory compliance analytics.
This internship provides exposure to how data analytics and technology are used to detect financial crime, enhance risk monitoring, and improve compliance controls in a digital banking environment. The intern will work closely with AML, fraud, and compliance specialists and gain hands-on experience to analyze customer profile attributes and transaction data, identify trends, develop insights. These activities will go towards projects that will reinforce the robustness of the Bank's control framework, thereby safeguarding the bank's reputation and securing customer trust.
Key Responsibilities
Data Analysis & Insights
- Analyze large datasets to identify and link profile attributes, behavioural traits and transactional patterns to detect anomalies and criminal modus operandi
- Conduct exploratory analysis to improve alert quality and reduce false positives
Analytics & Visualization
- Develop dashboards and visualizations to support monitoring of AML, fraud, and compliance metrics
- Produce data-driven reports for internal stakeholders
Automation & Efficiency
- Assist in developing data scripts, queries, or automation tools to streamline compliance reporting
- Leverage data analytics to create efficiencies for risk review and assessment
Regulatory & Risk Insights
- Support research into emerging financial crime typologies
- Assist in analyzing trends in suspicious activity, fraud cases, and regulatory reporting
Projects
- Contribute to special projects such as:
- AML alert optimisation
- Fraud detection analytics
- Risk dashboard development
- Data-driven compliance insights
Requirement:
Education
- Currently pursuing a degree in: Data Analytics, Data Science, Computer Science, Statistics, Finance / Risk with strong analytics focus
Technical Skills
- Knowledge of SQL or Python/R
- Familiarity with data visualization tools (Tableau, Power BI, or similar)
- Strong proficiency in Excel
Key Attributes
- Strong analytical and problem-solving skills
- Curiosity and a healthy level of skepticism to challenge conventional wisdom
- Ability to translate data insights into practical risk insights
- Strong communication and presentation skills
Good to Have:
- Keen interest in financial crime, AML, fraud detection, or regulatory compliance
- Exposure to machine learning, anomaly detection, or data modelling
What We Offer:
- Opportunity to work with an experienced team
- Exposure to real-world financial crime analytics in a digital bank
- Understanding of AML, fraud detection, and regulatory compliance frameworks
- Opportunity to contribute to data-driven financial crime prevention
