Setup Environment

Set up environment for data processing and input credentials

Load Up Party Details for Matching

The source data for matching can be found here. There are 4,000 parties for matching (way to many to do manually). In this step we also structure our search requests based on what is considered a matching. I.e. all of the following are considered matches:

Name and Address hit
Name and Account hit
Name and Identification hit
Address and Account hit
Identification and Address hit.

Basically if two of the key attributes hit then we consider that as a match.

👍️ Excel file loaded with 4001 records

👍️ Formatted 4001 requests ready for submission to API

👍️ Sample submission looks like this -->
{
    'party': [
        {'name': [{'fullName': 'KONE'}], 'address': [{'generalSearch': '51 The Grange Picton NSW'}]},
        {'name': [{'fullName': 'KONE'}], 'account': [{'number': '780357572', 'network': 'swift'}]},
        {'name': [{'fullName': 'KONE'}], 'identification': [{'identifier': '1959-04-12'}]},
        {
            'account': [{'number': '780357572', 'network': 'swift'}],
            'identification': [{'identifier': '1959-04-12'}]
        },
        {
            'account': [{'number': '780357572', 'network': 'swift'}],
            'address': [{'generalSearch': '51 The Grange Picton NSW'}]
        }
    ]
}

Submit Matching Requests

Submit the lists of parties for matching sequentially and generate two dataframes of results. One dataframe is broken down by request and the other is broken down by hit geolocation.

Matching Runtime is: 1274.1  seconds

Input Parties That Matched: 26

Total Report Hits: 38

Total Party Hits: 39

Total Amount Hits: $24772

Review Matched Results

The below table identifies the the requests that found matching reported parties within the transaction reports dataset.

Produce Chart of Matched Results

The below table provides a graphical representation of the data matching results.

View Location of Matches

The below map identifies the location of hits.

Competition Unstructured Extension

Competition participants are required to identify the complete financial footprint of the network associated with the party with the greatest value of total transactions identified above. Please use the consolidated party and network API end points to perform this analysis. Then extract the reported transactions from the redtongue API for disemination as evidentiary(raw) data.

requestId	name	partyIdCount	took	reports	totalAmount
3696	Mrs M MILROY	1	3	1	$15150.00
1316	Mrs C HEUANGVILA	2	1	2	$6271.00
1467	Mrs A GETZOFF	2	1	2	$882.00
703	Mrs E BECKOR	2	1	2	$714.00
823	Mrs L GLAZIK	3	1	3	$517.50