What it does
A Machine Learning model, leveraging banking transactions data to detect fraudulent activities. The system first detects the potential fraudulent bank account and then it provides data visualization tool to manually investigate whether the bank account labelled as suspicious is really suspicious (i.e. whether it is true positive). This is quite important since the costs to check a suspicious bank account are very high, so it is not worth spending a lot of money on false positive examples.
How we built it
Challenges we ran into
To make effective data preprocessing and data exploration and then to find the most suitable hyperparameters.