Datacuration
Objective:
- Understand the whole process of machine learning for Fraud Detection in Barclays
- Understand everything there is to data involved in the workflow
- Develop frameworks and tools for automation of data pre-processing and relevant data pipelines
- Improve the efficiency of the whole process as much as possible
Approach:
- Learnt about several data sources involved in fraud detection
- Developed a system for automation processing and reporting on data.
- Consisted of several modular subcomponents
- Scalable and time-tested on large datasets
- Works on both bigdata and smalldata
- Generated automated reports for different uses and purposes
- Dashboard for better visualization
Results:
- Removed manual efforts in several key work pieces
- Improved completion timeline from months to hours
- Automated workflows for better maintenance