It is important to adopt a comprehensive approach to data migration, including a thorough analysis of the data and systems involved, careful planning and testing of the migration process and ongoing monitoring and review to ensure the accuracy and completeness of the data when it is implemented in the new system.

As a first step, our client was looking to streamline their operations and accelerate efficiencies. This called for a purpose-built solution that could be automated and customised to meet their organisations data quality needs. Another requirement was the ability to have a real-time, dashboard view of all the data discrepancies across multiple systems and data points within the organisation.

Our client would then use the rich data to inform organisational growth through data analytics, strategic decision making, digital transformation initiatives, automation and investment in artificial intelligence and machine learning.

As part of AUSTRAC Customer identification and verification obligations, Financial Institutions must identify any customers present on several, centralised-Government managed and issued customer listings. ​

Historically, organisations would meet this obligation by providing a significant volume of customer-sensitive data to an external party, who would assess the data and provide potential findings back to the organisation. ​

This presented not only a significant data security risk to organisations but also, an inability to keep pace with a rapidly changing political climate, such as the sanctions that were imposed due to the conflict in Ukraine.

Heavily regulated industries are required to monitor for financial crime and other related activities as a part of Anti-Money Laundering (AML) and Counter-Terrorism Financing (CTF). This includes activities such as transaction monitoring, fraudulent behaviour and screening of customers on a regular basis. Our client, a large superannuation fund, wanted a way to securely manage their fraud prevention and transaction monitoring.

InvestigateDQ was integrated into everyday BAU processes across multiple teams with 160 staff members in the production environment using it daily and the intention to push it out across the entire company. These are staff members from all aspects of the business, using it for everything from day-today work queues to report generation and risk management. Before transitioning, the InvestigateDQ team were able to train a few staff members, who in turn trained everyone else; a testament to the usability of the system