Abstract
In the finance field, anti-money laundering has been deeply studied and formed a series of theories. If we apply these theories and methods directly to police investigation cases, the actual results may not be satisfactory. From the perspective of police reconnaissance, this paper proposed a capital flow hierarchical model based on anti-money laundering suspicious data, according to the direction of capital flow, the model divided each account in data into levels, and simplified the large-scale network, to find out how money flowed in the process of money laundering. Besides of this, we used the entropy-weight method to evaluated each account entity, and analyzed the importance of each entity in the money laundering network. Finally, we experiment with the simulated data set and plot the capital flow graph after layering, which confirms the effectiveness of the hierarchical model.
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