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This paper seeks to provide a textual analysis of the anti money laundering practices of the central banks of Australia (Reserve Bank of Australia (RBA)) and Ukraine (National Bank of Ukraine (NBU)).

The analysis is performed two ways by both calculating a disclosure index and through use of textual analysis.

The results show very low levels of anti money laundering disclosures by both NBU and RBA with NBU usually showing more. Textual analysis reveals that the NBU is prepared to internalise its discussion on anti‐money laundering discussing wide‐ranging topics. There appears to be a concerted communication effort by NBU to tackle the issues of money laundering head‐on. Textual analysis of the RBA's four annual reports show a clipped discourse on anti‐money laundering, treating it as if it were a distant concern. Over the four year period, there is little acknowledgement in the way of RBA textual discourse that Australia is a jurisdiction of primary concern.

The value of this paper is that, it emphasizes that, if the globalised activity of money laundering is to be crushed further energies are needed to woo central banks from varied backgrounds into exerting their considerable resources toward anti‐money laundering enforcement.

Nowadays, most of our activities and personal details are recorded by one entity or another. These data are used for many applications that fundamentally enrich our lives, such as navigation systems, social networks, search engines, and health monitoring. On the darker side of data collection lie usages that can harm us and threaten our sense of privacy. Marketing, as an academic field and corporate practice, has benefited tremendously from this era of data abundance, but has concurrently heightened the risk of associated harms.

In this chapter, we discuss both the great advantages and potential harms ushered in by this era of data collection, as well as ways to mitigate the harms while maintaining the benefits. Specifically, we propose and discuss classes of potential solutions: methods for collecting less data overall, transparency of code and models, federated learning, and identity management tools, among others. Some of these solutions can be implemented now, others require a longer horizon, but all can begin through the advocacy of marketing research. We also discuss possible ways to improve on the benefits of data collection – by developing methods to assist individuals pursue their long-term goals while advocating for privacy in such pursuits.