Setup Environment

Set up environment for data processing and input credentials


👍️ Configuration loaded

Extract Threshold Transactions From API

Pull all Threshold transactions for the period. The transaction reports search endpoint is required to be used to extract this subset of the data. An example of how to search for a report type is included in the openAPI schema (i.e. on the swagger UI page).


Current Extraction Runtime:  1.05 minutes, 10000 records extracted so far (continuing ....)
Current Extraction Runtime:  2.07 minutes, 20000 records extracted so far (continuing ....)
Current Extraction Runtime:  2.83 minutes, 30000 records extracted so far (continuing ....)
👍️ Reports Extracted : 34391
👍️ Extraction Runtime is: 3.07 minutes

Count and Total Amount of Threshold Transactions Per Day

Perform a little analysis into the pattern of threshold transactions over the year.


Institution Breakdown For Threshold Transactions

We can also review the institutions breakdown of threshold transactions.


Extract Parties from Reports

Now that the reports have been identified, we can extract all of the parties linked to these reports (with a role of customer).


👍️ Parties Extracted From Threshold Reports : 34391
👇️ Example Party Below
[
    {
        'partyId': 'be312525e5fbc04377226474ddd5446eb5783266b6c918dde9f787910c16fea9',
        'partyType': 'individual',
        'name': 'JAIME ILTIS',
        'addressState': 'NSW',
        'addressSuburb': 'Tweed Heads South',
        'addressCountry': 'AU',
        'amount': 29898.0,
        'accountInstitutionCode': 'CBA',
        'gender': 'FEMALE'
    }
]

Party Address Suburb For Threshold Transactions

We can now visualise the data to get an understanding of where customers are coming from that are performing threshold transactions.


Here we need to leverages the consolidated party endpoint. Given a specific partyId it returns all party Ids with slightly different reported characteristics, that are considered similar enough to be consolidated into the same real world party. For example James Brown and Mr J. Brown living at the same address are linked together.

This process will create a larger list of partyIds.






👌️ All 34391 Threshold Parties Processed in: 4.3 minutes. Total unique parties identified: 82146

Identify Higher Risk IFTI Transactions

Now we have a list of all partyIds linked to threshold transations we can identify higher risk IFTI transactions assoicated to these parties.

Specifically parties linked to outgoing reports over $100 dollars.






👌️ All 82146 Linked Parties Processed in: 33.16 minutes. Total reports identified: 6700

List Identified Transaction Details

The below table identifies top 10 IFTIs by total amount linked to parties on threshold transactions. These transactions and the associated parties would be considered higher risk and may warrant further manual investigation.


report.processedDatetime report.reportNumber orderingCustomerName report.reporter transaction.direction transaction.amount
2020-02-09T09:16:38+00:00
259860396466
M. PRENOSIL
paypal
outgoing
$900000.00
2020-10-08T16:18:13+00:00
173710811628
Mr W KILSON
paypal
outgoing
$449999.00
2020-10-30T03:15:06+00:00
891054379590
YEN CARRELLI
paypal
outgoing
$445000.00
2020-01-05T14:35:51+00:00
519565181192
S. DANIHER
paypal
outgoing
$269995.00
2020-01-13T10:09:14+00:00
286330714668
Mrs D MCCLEAD
paypal
outgoing
$198995.00
2020-07-11T05:56:41+00:00
319862242787
BRIAN COLLMANN
paypal
outgoing
$194999.00
2020-09-25T00:29:11+00:00
310899446795
Mrs P MARTORELL
paypal
outgoing
$187995.00
2020-01-28T04:18:23+00:00
894302575966
MICHAL KEISS
paypal
outgoing
$179500.00
2020-05-11T07:37:30+00:00
161118455629
Mrs J RIEGERT
paypal
outgoing
$164950.00
2020-05-28T15:57:25+00:00
895892863623
Mrs J HAIKAL
paypal
outgoing
$162000.00

Competition Unstructured Extension

Competition participants are required to identify parties associated to suspicious matter reports related to "cuckoo" smurfing and are linked to a international fund transfer over $10,000. The transaction-reports search endpoint should be used to identify the SMRs using a query string search (e.g. reports that mention the behaviour).