Identifying those responsible for stealing the credit cards

Having identified the affected parties and seeing how much they lost, let's now find out who is responsible for this.

Getting ready

To execute this recipe, you will need NetworkX, collections, and NumPy. No other prerequisites are required.

How to do it…

In this recipe, we will attempt to find the merchant that all the affected parties shopped at before the first fraudulent transaction occurred (the graph_fraudOrigin.py file):

import networkx as nx
import numpy as np
import collections as c

# import the graph
graph_file = '../../Data/Chapter08/fraud.gz'
fraud = nx.read_graphml(graph_file)

# identify customers with stolen credit cards
people_scammed = c.defaultdict(list)

for (person, merchant, data) in fraud.edges(data=True):
    if data['disputed']:
        people_scammed[person].append(data['time'])

print('\nTotal number of people scammed: {0}' \
    .format(len(people_scammed)))

# what was the time of the first disputed transaction...