Social network analytics

Fraud Detection in R

Bart Baesens

Professor Data Science at KU Leuven

Social network components

Nodes (vertices)

customers
companies
products
credit cards
accounts
web pages

Social network components

Edges

Different kind of relationships, e.g. money transfer, call, friendship, transmission of a disease, reference

Social network components

Edges

Different kind of relationships, e.g. money transfer, call, friendship, transmission of a disease, reference
Weighted based on e.g. interaction frequency, importance of information exchange, intimacy, emotional intensity

Social network components

Edges

Different kind of relationships, e.g. money transfer, call, friendship, transmission of a disease, reference
Weighted based on e.g. interaction frequency, importance of information exchange, intimacy, emotional intensity
Directed, e.g. incoming or ougoing

Social network representation

Towards a network

From a transactional data source ...

print(transactions)

   originator beneficiary amount  time benef_country payment_channel
1        ID14        ID16    102 22:47           GBR         CHAN_04
2        ID14        ID15    125 20:21           USA         CHAN_02
3        ID02        ID01   1067 10:45           CAN         CHAN_04
4        ID05        ID06     59 15:40           USA         CHAN_02

... towards a network with function graph_from_data_frame()

library(igraph)
network <- graph_from_data_frame(transactions, directed = FALSE)

plot(network)

plain_network

E(network)

+ 16/16 edges from 297af3c (vertex names):
 [1] ID02--ID01 ID11--ID04 ID04--ID01 ID04--ID03 ID03--ID01 ID08--ID09
 [7] ID14--ID15 ID03--ID14 ID05--ID06 ID11--ID12 ID02--ID05 ID11--ID13
[13] ID02--ID08 ID14--ID16 ID08--ID10 ID05--ID07

V(network)

+ 16/16 vertices, named, from 297af3c:
ID02 ID11 ID04 ID03 ID08 ID14 ID05 ID01 ID09 ID15 ID06 ID12 ID13 ID16 ID10 ID07

V(network)$name

"ID02" "ID11" "ID04" "ID03" "ID08" "ID14" "ID05" ... "ID16" "ID10" "ID07"

Overlapping edges

plot(net)

E(net)$width <- count.multiple(net)

edge_attr(net)

$width
7 7 7 7 7 7 7 1 1 1 4 4 4 4 1 1

Overlapping edges

E(net)$curved <- FALSE
plot(net)

Let's practice!

Fraud Detection in R