In democracies, financial surveillance legislation attempts to balance the rights to privacy of customers, the strategic need to prevent the tipping-off of wrongdoers, and the policy objectives to ensure the integrity of the financial system. The trade-offs in this regard in Australia’s anti-money laundering and counter terrorist and proliferation financing (AML/CTF) regime limit the effectiveness of the AML/CTF measures. In practice, for example, privacy concerns resulted in limiting Australia’s financial intelligence unit, AUSTRAC (2024) (the Australian Transaction Reports and Analysis Centre AUSTRAC), to receiving information that either relates to money entering or exiting the Australian financial system or around which prior suspicion already exists. They further limit the ability of financial institutions to share information between each other, even regarding suspicious matters that they are required to detect and report to AUSTRAC. This chapter considers whether privacy-preserving data analytics can be used to close financial intelligence gaps while protecting the privacy of customers behaving lawfully. It focuses on initiatives in Australia to improve information-sharing among regulated institutions and between these institutions and AUSTRAC, which explore technological innovations that address the fundamental privacy constraints underlying the traditional AML/CTF model. In particular, AUSTRAC supported the development of privacy-preserving analytical technologies that allow mass analysis of financial data without any data collection. The technology, FinTracer, applies homomorphic encryption to enable financial institutions to discover and to report to AUSTRAC suspicious actors in their data, even when this suspicion is based on behaviour of actors that spans multiple financial institutions of a kind that would have traditionally been impossible to detect without extensive information-sharing. AUSTRAC subsequently released the technology as open source, enabling further innovation. This chapter considers the international, AUSTRAC and technological contexts within which FinTracer technologies were developed, describes the technology, and highlights how it navigates some of the pitfalls of applying privacy-preserving data analytical technologies in this space.