Conducting world-class research

Linkage Project

Aims

Crime prevention

- Interruption of victimisation with specific focus on individuals who are wittingly or unwittingly recruited as money mules- Role of banks/financial institutions in education, interruption and response

Pillars

1. What is ‘current state of play’ and working?

• Mapping of crime prevention strategies across banks and financial institutions
• What data is available and does it inform our knowledge of approach effectiveness?
• Data from banks/ financial institution
• Survey and interviews with community members – how it is perceived, is it working, what can be learnt by banks/financial institutions?

2. What ‘might’ work? Development & testing of innovative approaches

• Focus: on ‘soft’ crime prevention approaches; the weakest link is the ‘individual’
• How they can be used in conjunction with ‘hard’ crime prevention approaches
• Development of independent, standalone approaches to crime prevention built on ‘soft’ crime prevention methodologies.

Team

Associate Professor Jacqueline Drew, Deputy Director - Academy of Excellence in Financial Crime Investigation and Compliance, Griffith University

Professor Benoit Leclerc, Griffith Criminology Institute, School of Criminology and Criminal Justice, Griffith University

Aims & Objectives

• Because criminals spend the proceeds of crime, an easy way to estimate the shadow economy is to examine how this is reflected in consumption data.
• “Customers living beyond their means” is a typical indicator of suspicious activity. Among investigation teams, there are many instances in which assessments need to be made about how observed consumer expenditure patterns align with self-reported income levels.
• Using empirical insights into how the composition of consumption patterns changes with income, this project aims to develop a suite of new tools that enables the CBA and ATO to harness data on consumption to deliver better empirical basis to investigate unusual expenditure that should deliver efficiencies,

Outputs & Deliverables

1. Create new estimates of the size of the Australian shadow economy using publicly available consumption data and produce a dashboard that delivers up to date trends on the size and geographic spread of activity .

2. Deliver consumption benchmarks and tools that help CBA investigators assess what is “normal” and whether customers are living “beyond their means” & new potential indicators of tax evasion could be used in transaction monitoring. This can also be used in risk assessment exercises.

3. Use behavioural insights to how public information campaigns can be designed

Team

Professor Andreas Chai, Director - Academy of Excellence in Financial Crime Investigation and Compliance, Griffith University

Associate Professor Nicholas Rohde, Department of Accounting, Finance and Economics, Griffith University

Professor Benno Torgler, School of Economics and Finance, QUT

Objectives

The objectives of this research is threefold:

1. To conduct a comparative analysis of AML frameworks, practices and compliance across Designated Non-Financial Business Professionals (DNFBPs) in the accounting, legal, and real estate sectors across several jurisdictions like NZ, UK, Canada, EU etc.
2. To investigate the extent of readiness, challenges and opportunities AML Tranche II regulations might present for accounting, legal and real estate firms in Australia
3. To investigate the perceptions of financial institutions of the benefits and challenges of Tranche II (simplified process and additional regulated DNFBPs)For 30 years, Bernie Madoff ran one of the world’s most famous Ponzi schemes, defrauding his clients for total of $65 billion. But how did he persuade otherwise sophisticated investors to forgo due diligence and ignore obvious red flags?

Team

Professor Shireenjit Johl, Deputy Director - Academy of Excellence in Financial Crime Investigation and Compliance, Griffith University

Dr Ingrid Millar, Department of Accounting, Finance and Economics, Griffith University.

Associate Professor DaiFei Yao, Department of Accounting, Finance and Economics, Griffith University.

Aims and Objectives

• A practical automated framework for detecting money laundering
• Provides a tool to assist human analysts by detecting suspicious activities
• Integration of customer and business information to money laundering detection
• Allow for analysis of data from heterogeneous sources of information – one screen user interface for human analysts instead of logging into multiple systems
• Uses AI techniques but still requires final human intervention and decision making
• If the system is used across the industry, it allows sharing of money laundering techniques while providing privacy for each banking entity.

Team

Professor Ernest Foo, Deputy Director - Academy of Excellence in Financial Crime Investigation and Compliance, Griffith University\

Dr Zhe Hou, School of Information and Communication Technology, Griffith University

Dr Zahra Jadidi, School of Information and Communication Technology, Griffith University