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1. Artificially Intelligent Electronic Money

   https://doi.org/10.1109/MCE.2020.3024512  

   Fragkos, Georgios; Minwalla, Cyrus; Plusquellic, Jim; Tsiropoulou, Eirini Eleni (January 2020, IEEE Consumer Electronics Magazine)

   null (Ed.)

   Electronic money or e-Cash is becoming increasingly popular as the preferred strategy for making purchases, both on- and off-line. Several unique attributes of e-Cash are appealing to customers, including the convenience of always having "cash-on-hand" without the need to periodically visit the ATM, the ability to perform peer-to-peer transactions without an intermediary, and the peace of mind associated in conducting those transactions privately. Equally important is that paper money provides customers with an anonymous method of payment, which is highly valued by many individuals. Although anonymity is implicit with fiat money, it is a difficult property to preserve within e-Cash schemes. In this paper, we investigate several artificial intelligence (AI) approaches for improving performance and privacy within a previously proposed e-Cash scheme called PUF-Cash. PUF-Cash utilizes physical unclonable functions (PUFs) for authentication and encryption operations between Alice, the Bank and multiple trusted third parties (mTTPs). The AI methods select a subset of the TTPs and distribute withdrawal amounts to maximize the performance and privacy associated with Alice's e-Cash tokens. Simulation results show the effectiveness of the various AI approaches using a large test-bed architecture. 

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2. Let's Talk Money Wiki

   Marchetti, Carol; Bennett, Jessica; Blackwell, Gloria; Bailey, Margaret; Litzler, Liz; Patrick, Annie (May 2025, Open Science Framework)

   Repository of project information, including resources and toolkit. DOI 10.17605/OSF.IO/AR8WG 

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3. SoK: Money Laundering in Cryptocurrencies

   https://doi.org/10.1145/3465481.3465774  

   Kolachala, Kartick; Simsek, Ecem; Ababneh, Mohammed; Vishwanathan, Roopa (August 2021, ARES 2021: The 16th International Conference on Availability, Reliability and Security)

   null (Ed.)

   Money laundering using cryptocurrencies has become increasingly prevalent, and global and national regulatory authorities have announced plans to implement stringent anti-money laundering regulations. In this paper, we examine current anti-money laundering (AML) mechanisms in cryptocurrencies and payment networks from a technical and policy perspective, and point out practical challenges in implementing and enforcing them. We first discuss blacklisting, a recently proposed technique to combat money laundering, which seems appealing, but leaves several unanswered questions and challenges with regard to its enforcement. We then discuss payment networks and find that there are unique problems in the payment network domain that might require custom-designed AML solutions, as opposed to general cryptocurrency AML techniques. Finally, we examine the regulatory guidelines and recommendations as laid out by the global Financial Action Task Force (FATF), and the U.S. based Financial Crimes Enforcement Network (FinCEN), and find that there are several ambiguities in their interpretation and implementation. To quantify the effects of money laundering, we conduct experiments on real-world transaction datasets. Our goal in this paper is to survey the landscape of existing AML mechanisms, and focus the attention of the research community on this issue. Our findings indicate the community must endeavor to treat AML regulations and technical methods as an integral part of the systems they build and must strive to design solutions from the ground up that respect AML regulatory frameworks. We hope that this paper will serve as a point of reference for researchers that wish to build systems with AML mechanisms, and will help them understand the challenges that lie ahead. 

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4. Nonequilibrium statistical mechanics of money/energy exchange models

   https://doi.org/10.1088/1751-8121/ad369b  

   Miao, Maggie; Makarov, Dmitrii E.; Blom, Kristian (April 2024, Journal of Physics A: Mathematical and Theoretical)

   Abstract Many-body dynamical models in which Boltzmann statistics can be derived directly from the underlying dynamical laws without invoking the fundamental postulates of statistical mechanics are scarce. Interestingly, one such model is found in econophysics and in chemistry classrooms: the money game, in which players exchange money randomly in a process that resembles elastic intermolecular collisions in a gas, giving rise to the Boltzmann distribution of money owned by each player. Although this model offers a pedagogical example that demonstrates the origins of Boltzmann statistics, such demonstrations usually rely on computer simulations. In fact, a proof of the exponential steady-state distribution in this model has only become available in recent years. Here, we study this random money/energy exchange model and its extensions using a simple mean-field-type approach that examines the properties of the one-dimensional random walk performed by one of its participants. We give a simple derivation of the Boltzmann steady-state distribution in this model. Breaking the time-reversal symmetry of the game by modifying its rules results in non-Boltzmann steady-state statistics. In particular, introducing ‘unfair’ exchange rules in which a poorer player is more likely to give money to a richer player than to receive money from that richer player, results in an analytically provable Pareto-type power-law distribution of the money in the limit where the number of players is infinite, with a finite fraction of players in the ‘ground state’ (i.e. with zero money). For a finite number of players, however, the game may give rise to a bimodal distribution of money and to bistable dynamics, in which a participant’s wealth jumps between poor and rich states. The latter corresponds to a scenario where the player accumulates nearly all the available money in the game. The time evolution of a player’s wealth in this case can be thought of as a ‘chemical reaction’, where a transition between ‘reactants’ (rich state) and ‘products’ (poor state) involves crossing a large free energy barrier. We thus analyze the trajectories generated from the game using ideas from the theory of transition paths and highlight non-Markovian effects in the barrier crossing dynamics. 

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5. Derivation of wealth distributions from biased exchange of money

   https://doi.org/10.3934/krm.2023007  

   Cao, Fei; Motsch, Sebastien (January 2023, Kinetic and Related Models)