Exploratory analysis of transaction data to identify fraud-risk patterns across clients, merchants, transaction types and time periods.
Financial institutions and FinTech firms need to monitor unusual transaction behaviour. This project uses exploratory analysis to identify where analysts should focus further fraud investigation.
- Python data analysis
- Data cleaning and preprocessing
- Exploratory data analysis
- Transaction pattern analysis
- Risk segmentation
- Business interpretation
- Visual storytelling
- Cleaned and explored transaction data
- Analysed transaction trends by month and year
- Identified high-value merchants and clients
- Reviewed transaction types across customer segments
- Created high-risk client categories using behavioural indicators
- Produced visual outputs to support interpretation