Financial intelligence agency AUSTRAC has produced new products for pubs and clubs with gaming, highlighting the risks of money laundering and financial crimes.
The agency’s powers and approach have been strengthened since the Hayne royal commission, and it has recorded a massive 95 per cent increase in Suspicious Matter Reports (SMR) being filed in 2018/19 versus the previous year.
SMRs are filed by businesses suspecting possible illegal activity, including fraud, money laundering or terrorism. Certain businesses are obliged to submit one if circumstances warrant, and information may be used by Federal authorities or the ATO to investigate crimes.
Rapid advancement in technology-based payment platforms has left some services and retailers susceptible to exploitation by organised offenders, for the purposes of money laundering, terrorism financing, illicit black-market sales and even child sex exploitation, according to AUSTRAC.
Demonstrating its broad authority, AUSTRAC recently ordered US online payment behemoth PayPal to appoint an auditor to investigate issues with its international transaction reporting. This follows its landmark $700 million settlement against CBA, and $45 million case against Tabcorp. Australian ‘buy-now-pay-later’ fintech Afterpay is now believed to be on AUSTRAC’s radar.
AUSTRAC chief executive Nicole Rose says public enforcement will continue to be one of the entity’s key regulatory tools, and its impact is “undeniable”.
The government body is now warning gambling operations such as pubs and clubs, as well as those in the businesses of money remittance and payment services, to strengthen their systems or risk facing enforcement actions.
But while the speed of electronic transactions means punishing penalties can be quickly accumulated – CBA’s error causing over 53k reports from being filed – AUSTRAC suggests its actions are not intended to shut companies down, and it looks carefully at checks and balances carried out by any business found in breach.
AUSTRAC is also working with RMIT to develop machine learning tools to automate much of its data analytics, by studying the flow of transactions to identify anomalies and trigger an alert.