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Peer to Peer Anti-Money Laundering Resource Allocation Based on Semi-Markov Decision Process

The multimedia communication technologies have been widely used in the anti-money laundering (AML) field to improve the efficiency and security of the business transactions. To reduce the cost of massive multimedia processing and communications, it is desirable to allow multiple financial industries (FIs) to share the AML resources, including human, computation, communication, and storage resources, and cooperate with each other to complete the transaction tasks. In this paper, the optimal AML resource management among peer FIs towards the maximal AML rewards is studied. Specifically, an AML resource allocation model (AMLRAM) based on semi-Markov decision process(SMDP) is proposed, where the system state is represented by a tuple, i.e., the number of High-Risk Operation (HRO), the number of Low or Moderate Risk Operation (L/MRO), and the current event type (i.e., the arrival of HRO or L/MRO suspicious transaction report which needs to be further checked, and the departure of HRO or L/MRO suspicious transaction report which has been checked and releases the occupied AML resource) in the AML field. The maximal long-term rewards of the system is derived, and the optimal AML resource allocation decision among peer FIs is made to achieve the maximal system rewards. Extensive simulations validate our analysis.